@agora alternative or complementary definition: whoever contributes [[work]] for the community on a given recurring basis, in the format of their choice :)
RT @flancian@social.coop
agora alternative or complementary definition: whoever contributes [[work]] for the community on a given recurring basis, in the format of their choice :)
https://t.co/o7IqwuFsBQ
layout: post
title: Running your own social network
created: 1073243340
categories:
Social Media
Doc Searls pointed out a nice rant from Om Malik: he wants to manage hisw own social network, not rely on trapping his information in Tribe.net or LinkedIn or whatever.
Here’s Om’s idea for this application:
A special application, which allows me to set up my own private Tribe.net. As these “private
layout: post
title: TunesAtWork
created: 1074136200
categories:
Application
Mac
Music
Requires Java 1.4. Is installed on your Mac at home, which then runs a web server on a specified port (so you need to port-forward if you have a router, firewall, or other NAT device in between your broadband connection and your Mac).
TunesAtWork lets you listen to your personal iTunes music collection while at your office or lab, even though your iTunes collection resides at home.
TunesAtWork is a specialized web server that runs on your home Macintosh and serves web pages that present your music collection (including playlists) organized visually much the same as in iTunes itself. This makes it easy to find what you’re looking for.
Clicking the various links in the web page will cause MP3 files to be streamed from your home Mac to the computer where your browser is running. As long as that computer (where the browser is running) has a helper application that can play streamed MP3 files (e.g., WinAmp on Windows, MacAmp or iTunes itself on Macintosh), you will hear your music on that computer.
This analysis examines nine firms in the industry, exploring their similarities and differences. Each firm brings a new perspective or feature to the mix. The users, members, and customers decide which are valuable and which are not.
The actual analysis is quite “light”, but it was interesting to see 22 different companies identified as “social networking sites”. I never really considered Classmates.com to be one, but really it is — it doesn’t matter that I don’t like their business model and haven’t found any useful features…
Zerendipity wasn’t included, but that’s likely because of its (to date) exclusivity and geographic base/bias in Vancouver.
layout: post
title: "Media appearance: Is Microsoft doing enough to reinvent itself? on Business News Network"
created: 1193332932
categories:
BNN
Business News Network
Facebook
Fred Vogelstein
Canada
Microsoft
I’m going to be on Business News Network this afternoon, 4pm PST / 7pm EST, talking about if Microsoft is still innovating? This is, of course, related in part to earnings announcements from a bunch of companies, and more directly, the Microsoft investment in Facebook. I’ll be on a mini-panel with Fred Vogelstein.
Some related links / thoughts below, I’ll clean this up after the interview:
Do you believe that Microsoft knows its own strategic interests, and that it can act rationally and appropriately in their defense? Ten years ago I might have said yes, but today I have a much harder time. So when it comes to defending a large strategic premium over a credible competitor with a better basis for economic valuation, I have a hard time.
Recent interview with Steve Ballmer at the Web 2.0 Summit — from Ballmer on Windows Live search, “it’s like a 6 year old playing hoops with the 12 year olds”
Did Microsoft pay too much for Facebook? Well, Facebook might be overvalued, but it’s small dollars for Microsoft and gives them potential insite into profile / social based advertising
MSFT failures — Zune, Windows Mobile (failure outside of the US), search
MSFT wins and/or in progress — Silverlight, an Adobe Flash competitor, casual gaming and home based social networks (XBox Live Arcade, Windows Media Center, etc.)
innovation? Microsoft Research (PhotoSynth), new offices and working environments down in Redmond and elsewhere
closing thought: competition is good, Microsoft isn’t going anywhere; they *should* compete more on innovation rather than dollars and marketing
layout: post
title: Testing Ad Bard, a FOSS friendly ad network
created: 1211847230
categories:
Ad Bard
ad.module
advertising network
Jeremy Andrews
Drupal
Open Source
I’m testing out a new advertising network built by Jeremy Andrews. Jeremy is a long time contributor to the Drupal project, mainly through switching his site KernelTrap over to it many years ago, and then being involved with many other Drupal businesses — architecting major portions of CivicSpace among other things. Jeremy’s current “day job” aside from KernelTrap is Tag1 Consulting, who are Drupal performance experts. He also happens to have built the Drupal Advertising module.
The new advertising network I’m testing is Ad Bard. I’ll excerpt the “what” from the about page:
Ad Bard’s mission is to foster a friendly and useful advertising community. As a fellow Ad Bard, you will help to ensure that the advertisements in our network are useful, relevant, and non-obnoxious.
I’ve currently got the ad block running in the upper right hand corner of the sidebar. Yes, it doesn’t look too different from any of a number of usual banner ad rotations. The current schtick is that Ad Bard is “Free and Open Source” (FOSS) friendly. It has categories of advertisers and websites in the network related to a variety of open source topics, so at this point both the advertisements and websites should be relevant to people interested in those topics. The whole site / system is
Just to throw another concept into the mix, Jeremy recently put up a post advocating that Drupal.org should join Ad Bard. The Drupal Association has been testing ads on some of the forum pages on drupal.org for a while now, as a way to generate revenue to support the project. Google ads have been tested and are running now in the right sidebar of the hosting forum (itself now hotly contested because of some of the content from hosting providers). This really brings up the issue of whether ads are appropriate for open source projects at all. If ads do have to be there, I’m much more in favor of daily / weekly / monthly sponsorship ads: they seem to be much less painful to end users, and I think more effective for advertisers, too.
One of the thought experiments / questions that I often pose people is “How relevant does an ad have to be before it is no longer an ad?” One specific example would be someone looking to buy a Canon S5 IS from my review — is an ad on that page on a place to buy them an ad … or a useful, in context piece of information? All a matter of relevance, I believe.
If you’re an open source advocate (or project), you might want to kick the tires on Ad Bard — I’ll let you know what I think after I’ve had ads up for a while.
Disclosure: Raincity Studios does work with Tag1, and I’m a big fan of Jeremy. I’ve also shoved over a boatload of ideas that I have around advertising networks that I’ve been itching to experiment with. We’ll see :P
Basically, it allows you to drop in a members system / social network onto any site. It doesn’t need to be a CMS or a dynamic system at all, since it consists of just some Javascript that gets inserted wherever you like. You create a new network / site at the Friend Connect home, and then go on to upload a couple of files to your server. Select some widget options, copy and paste code, and you’ve got a place where visitors to your site can join your site’s network.
Now, as opposed to creating yet-another-profile, visitors use their (presumably existing) Google Account to login. Google Accounts have Profiles attached to them (since about December 2007, although it’s only recently that they are being talked about more). Here’s my Google Profile.
There aren’t really any built in "friends" in your everyday Google Account / Profile (in fact, in Google Reader it’s really hard — I enjoy Brendon Wilson’s rant on this), so you can also activate several other networks to automatically connect with "friends" from those systems. Twitter and Plaxo are two that I experimented with. Orkut is also supported … but when was the last time you signed into Orkut?
Twitter does that oh-so-lovable enter your username and password trick that leaves me feeling more than a bit queasy, but since I have a good size network, it seems pretty useful. You can then post to Twitter from within the widget to invite other people to join the network you’ve just entered. Plaxo does the better looking remote authentication and works just fine … except I don’t really use Plaxo all that much anymore.
OK, so now you’re a "member" of a local "network"! What next? Well, on to the world of "Social Gadgets". There are ratings and a comment wall, and also support for OpenSocial apps. The OpenSocial apps are, I guess, the interesting part of this in the future, sort of allowing bridging of different data with mashups unique to the members on your own site. Except there’s not much there today. Comments and ratings are fairly uninteresting when dynamic sites powered by Drupal or WordPress either do these things out of the box or can add them easily with a couple of plugins.
But….I’m not completely down on this system. In fact, I’ve been talking to Anthony of Farmstead Wines, who is a heavy Twitter user, about adding Friend Connect to his website. He can use his large Twitter network to build a social network around his website. It doesn’t do a lot of interesting things *today* … but you can already see how member profiles on Google Maps and other mashups will be trivial to implement in the future. Adding full network functionality to his website would cost a lot of money and time if needing to be "built in" directly, whereas the Friend Connect route lets Anthony build his network today, centered around the permalink of his own website (as opposed to some other system like ye old Ning).
I’ve included a Google Friend Connect network widget and wall widget after the jump. Jim Pick has also created one for the Vancouver Freebase.
Will you be adding Google Friend Connect to your site? Do you find it useful? Where is this heading?
Below is the Google "Wall Gadget" — it lets you post comments and post YouTube links. The scope of this wall is the "entire site" — you can make one of these that apply to a particular page or a unique id.
So far, I continue to be underwhelmed. Come on Google, ride on top of OpenID, and plug this directly into a site’s existing user account system…
Update:Jim Pick left a comment that went so far as including a screencast showing OpenID support in Google Friend Connect. So, my bad, Google Friend Connect does support OpenID directly. More correctly what I meant with my closing commentary was that, rather than logging into Google’s infrastructure, that this should be tied into my sites existing account system. Which already supports OpenID.
As TechCrunch says, it’s a bit like "MyBlogLog on steroids". The concept of followers etc. is now more widely known from both MyBlogLog, Twitter, and so on. The "asymmetric follow" concept — where people can be fans / followers / etc. is a good one, as it actually allows scale … as opposed to Facebook, where both sides have to confirm a connection (and why they have groups and pages which are asymmetric).
Like the other systems, it’s currently widget / plugin based. Here is the widget embbeded in this post — I may end up adding it to a sidebar on the site here as I experiment with Google and Facebook’s offerings. MyBlogLog? Yeah, that widget is gone (another Yahoo early lead squandered…). Does anyone actively use MyBlogLog these days?
<script language=”JavaScript” type=”text/javascript”>
var ra_no_of_membrs = 12;
var ra_aboutme = 0;
var ra_following = 1;
var ra_style = “adapt”;
<script language=”JavaScript” src=”http://www.redanyway.com/js/widget/ra.standard.widget.php?id=715” type=”text/javascript”>
Ultimately, my issue with these systems is that they don’t semi-permeably integrate into any existing community. I define community pretty narrowly: sites that actually support full account logins with some level of customization that you can do once you have an account. That leaves out most blogging only platforms (e.g. WordPress), but includes larger Drupal sites that allow and encourage . I’m especially interested to see how BuddyPress (a beta release today, I believe) might play into this space.
We do have the component tech pieces to build this distributed system — OAuth, OpenID, and so on. But, we don’t have great UIs nor great uses cases that make people want to use this functionality today. It’s going to be interesting to see how this space evolves. Scobleizer calls it the "war over your blog’s friends".
Disclaimer: I am evaluating Redanyway as a potential candidate for Bootup Labs.
#+title: Automation and the Future of Work
- source :: cite:benanav_2020
- tags :: [[file:../20210211094543-automation.org][automation]] [[file:../20210306160859-artificial_intelligence.org][artificial intelligence]]
* 1. The Automation Discourse
- The current mainstream discourse today is whether things like self-driving
trucks will replace truckers
- The main tenants of automation discourse are:
1. Workers are already being displaced by ever more advanced machines,
resulting in “technological unemployment”
2. This displacement is a sign that we’re on the verge of living in a totally
automated society, where work will be performed by machines and computers
3. Since we live in a society where one must work to live, such automation
would be a nightmare
4. The only way to prevent the aforementioned nightmare would be to implement
some kind of [[file:../20210306161251-universal_basic_income.org][universal basic income]]
- Those who believe that economic catastrophe as a result of automation is on
its way don’t think [[file:../capitalism.org][capitalism]] is going away, just that it’s shedding its need
for a labor market
- Left-wing adherents to this worldview believe that automation could bring
about [[file:../20210306161654-fully_automated_luxury_communism.org][fully automated luxury communism]]
- [[file:../20210211094543-automation.org][Automation]] :: the use of technology to /fully substitute/ human labor, rather
than merely augmenting its productive capacities
+ Automation destroys entire job classifications. There will never be switch
board operators again, for example
- Much of the existing debate surrounds whether or not present or near-future
technologies are labor-substituting or labor-augmenting
+ Are self-checkout machines something that replace cashiers, or something
that makes one cashier more productive?
+ In either case, the result can be unemployment
- Many automation theorists tend to see capitalism as a transitory stage, as the
bridge to full automation, which in turn will be an era where no further
automation will take place
- Ideas of full automation have been present since at least 1832
#+begin_quote
Charles Babbage’s On the Economy of Machinery and Manufactures in 1832, John
Adolphus Etzler’s The Paradise within the Reach of All Men, without Labour in
1833, and Andrew Ure’s The Philosophy of Manufactures in 1835…
#+end_quote
- The appeal of the full automation argument is that modern capitalism is
failing to provide enough jobs (and enough good jobs) for everyone to live
comfortably
+ There has been a low demand for labor
+ The labor share of income has been falling in G7 countries for decades
- Something strange has occurred within the economy, leading to a low demand for
labor, but it has not been caused by technological development
- Benanav says that automation theorists are the [[file:../20210306163324-utopian_socialism.org][utopians]] of modern capitalism
- Benanav will advance four counterarguments:
1. The decline in the demand for labor was not due to a leap in technological
innovation but economic stagnation
2. This underdemand for labor has tended to manifest as persistent
underemployment
3. The world of poorly paid workers will continue to be accepted by those in
power
a. UBI would only prop up a world of inequality, not dismantle it
4. Benanav will propose a path towards a world of abundance without the need
for automation
- The goal is a [[file:../20210306163746-post_scarcity.org][post-scarcity]] future, not necessarily a fully automated one
* 2. Labor’s Global [[file:../20210306164610-deindustrialization.org][Deindustrialization]]
- The [[file:../20210306164444-service_sector.org][service sector]] employs about 52% of workers worldwide
- Over the last 50 years much of the world has deindustrialized
- [[file:../20210306164610-deindustrialization.org][Deindustrialization]] :: “a decline in the share of manufacturing in total
employment.”
- It was assumed that the reason for deindustrialization was production moving
offshore, i.e. steel production moving from the US to China
- Manufacturing productivity has been slow to grow for decades as well
- [[file:../20210211094530-productivity_paradox.org][Productivity Paradox]] :: digitization has not lead to increased productivity,
as was expected
+ US manufacturing growth-rate statistics are overinflated, as they count the
production of computers with higher processing speeds as equivalent to
production of more computers
- Correcting US manufacturing statistics reveals that the US’s manufacturing
productivity is about the same as Japan and Germany
+ Germany and Japan are ahead of the US in the field of industrial robotics as well
- Productivity rates have gone from annual growth of ~5% in the post-war era to
~3% or less
- Productivity growth rates have been high relative to the output of growth
rates, hence why automation theorists believe productivity to be growing at a
rapid pace
+ USA
| Time Period | Output | Productivity | Employment |
|——————-+————+———————+——————+
| 1950–73 | 4.4% | 3.1% | 1.2% |
| 1974–2000 | 3.1% | 3.3% | -0.2% |
| 2001–17 | 1.2% | 3.2% | -1.8% |
+ Germany
| Time Period | Output | Productivity | Employment |
|——————-+————+———————+——————|
| 1950–73 | 7.6% | 5.7% | 1.8% |
| 1974–2000 | 1.3% | 2.5% | -1.1% |
| 2001–17 | 2.0% | 2.2% | -0.2% |
+ Japan
| Time Period | Output | Productivity | Employment |
|——————-+————+———————+——————|
| 1950–73 | 14.9% | 10.1% | 4.3% |
| 1974–2000 | 2.8% | 3.4% | -0.6% |
| 2001–17 | 1.7% | 2.7% | -1.1% |
- Deindustrialization on this scale caused solely by technological advancement
is impossible
- Worldwide rates of output growth have been declining since WWII
- More is produced by fewer workers, but not because workers are more
productive, but because output growth has been shrinking
- Overcapacity produced after WWII led to a long downturn in
manufacturing-output growth rates
- US overcapacity began to falter once cheaper manufacturers, first from Europe,
were able to penetrate the US domestic market, causing a decline in output
growth
- Other countries in the post-war era followed the pattern of the US by building
up their manufacturing and adopting export-led growth strategies
- Deindustrialization was passed off to poorer third world countries by
depressing prices in global markets
- Technological advancement was welcomed hand-in-hand with deindustrialization
in an attempt to reduce prices, resulting in sector-wide job loss
- Overcapacity explains why deindustrialization was accompanied by ongoing
efforts to develop labor-saving technologies as well as the building out of
massive labor-intensive supply chains
- [[file:../20210306171957-globalization.org][Globalization]] (the creation of international supply chains and spreading
manufacturing across the globe) led to a [[file:../20210306171918-centralization_of_capital.org][centralization of capital]], where the
world’s wealthiest companies retained manufacturing capacity
- Countries that have achieved a high degree of automation are not the worst hit
by deindustrialization, as high degrees of automation allow for a competitive
edge
- [[file:../20200607220504-china.org][China]] has seen productivity and employment growth, but not because of
automation, but because of a combination of advanced technology and low wages
- Firms can only achieve high rates of growth by taking market share from their
competitors in this modern environment
* 3. In the Shadow of Stagnation
- Labor productivity and output have been slow to grow since about the 70s in
advanced capitalist countries
+ Productivity has grown more slowly outside of manufacturing than in it
- “Manufacturing was a unique engine of economic growth”
- “Low rates of industrial productivity are the result of a slower pace of
expansion rather than the reverse”
- As deindustrialization has occurred, workers have pooled in less productive
sectors
- Deindustrialization has been paired with financialized capital (i.e. “chasing
returns to the ownership of relatively liquid assets rather than investing
long-term in new fixed capital”)
- “Japanification” :: balance sheet stagnation. A process whereby asset bubbles
create a “wealth effect” for richer households, “since their assets appear to
be saving money for them”. Said bubbles pop, and those households withdraw
from their assets to pay down debts. Named after Japanese bubble pop in 1991
- Deindustrialization has been paired with such bubbles. The biggest was the
real estate bubble that nearly brought down the Japanese economy and the [[file:../20200629122347-2008_financial_crisis.org][US
economy in 2008]]
- The markets that were created by industry have not been replaced by anything
else for poorer countries
- Growth rates prior to the first world war were more comparable to growth rates
today
+ That said much of the world was not industrialized
+ Much of the world market today requires people to enter into labor markets
to live, unlike prior to WWI
- [[file:../20201202215710-covid_19.org][Pandemics]] are followed by long-lasting declines in GDP rather than booms
- Automation theorists believe that technological development is linear and
occurs along a set path, leading to the belief in the upcoming [[file:../20210309214442-singularity.org][singularity]]
- Technological development is highly resource intensive, and researchers
prioritize the most profitable research
+ There is little research into how technology may make line workers more
productive, but lots of research in how to spy on line workers
- Agriculture was difficult to automate until the 1940s, but once it came farms
started to resemble “open-air factories”
+ And once it happened, the industry shed workers unlike any other industry
before
* 4. A Low Demand for Labor
- We are headed towards a “good job”-less future rather than a “job”-less one
- In the 1970s governments began scaling back unemployment benefits to try and
coax the unemployed back to work, as these welfare programs had not been
designed for long-term high rates of unemployment
- Higher rates of unemployment meant that employers could more easily break the
strength of labor by hiring cheaper
+ Benanav reminds us that this is the [[file:../20210310212707-general_law_of_capitalist_accumulation.org][general law of capitalist accumulation]]
- Comparatively, it’s unusual that in the United States, even highly paid
workers are just as vulnerable as their low-paid counterparts to potential job
loss. This is due to at-will employment
- Postwar and postcolonial development states sometimes had stronger labor
protections than their European counterparts
- In Africa, Asia, and Latin America, nonstandard employment became a major
problem as early as the 1950s
- This is the problem with the term “nonstandard employment”: it reveals the
dream of global full-employment that never came to pass
- The world’s underemployed are mostly working in the service sector
- The service sector has a difficult time automating, because they do not
experience dynamic patterns of expansion. Expansion in the service economy
occurs by simply hiring more employees
- Services form a stagnant economic sector: they do not contribute to economic
growth
- The activities that remain services today are those that cannot be easily
automated
- The service sector cannot rely on price effects for expansion demand, i.e.
rising productivity does not lead to falling prices and therefore increased
demand, so the service sector will likely grow slowly over time
- As underemployment rises, inequality will intensify
- As time goes on, immiserating employment growth becomes self-reinforcing,
where sectors of the economy expand by taking advantage of the underemployed
and then come to depend on their continued availability
#+begin_quote
Over time, immiserating employment growth becomes self-reinforcing. Sectors of
the economy expand by taking advantage of pools of underemployed labor and
then come to depend on their continued availability. As thoughtfully depicted
in Bong Joon-ho’s award-winning 2019 film Parasite, it begins to make sense
for high-net-worth and managerial households to hire working-class households
to perform more of the tasks they would otherwise do for themselves—as tutors,
domestic servants, drivers, childminders, and personal assistants—simply due
to large differences in the prices of their respective labors.
#+end_quote
- As inequality has risen social mobility has fallen
- The poor won’t get poorer as time goes on, but the poor will have less
opportunity to leave poverty
- The following sure sounds like the capitalism of Marx’s time:
#+begin_quote
These trends suggest that the apocalyptic crisis of labor market dysfunction
anticipated by automation theorists will not take place. Instead, unemployment
will continue to spike during downturns—as we are seeing happen once again, and
on a truly massive scale, in the present COVID-19 recession. Then, in the course
of the tepid boom periods that follow, this unemployment will slowly but surely
resolve itself into higher levels of underemployment and rising inequality. In
Rise of the Robots, futurist Martin Ford says that his worst nightmare would be
if the “economic system eventually manages to adapt to the new reality” of labor
displacement. But in truth, it has. As Mike Davis put it, the “late-capitalist
triage of humanity” has “already taken place.”48 Unless halted by concerted
political action, the coming decades are likely to see more of the same:
overcapacity in international markets for agricultural and industrial products
will continue to push workers out of those sectors and into services, which will
see their share of global employment climb from 50 percent today to 70 or 80
percent by mid century. Since overall rates of economic growth are set to remain
low, the service sector will absorb job losers and new labor market entrants
only by increasing income inequality, leading us further and further into the
postindustrial doldrums.
#+end_quote
* 5. Silver Bullets?
- Automation theorists believe that [[file:../20200629130431-keynesian_economics.org][Keynesianism]] may solve the issue of a low
demand for labor
#+begin_quote
#+end_quote
- Rapid post-war industrial expansion generated a high demand for labor on its
own
#+begin_quote
Instead, as I have argued in previous chapters, rapid postwar industrial
expansion generated a consistently high and stable demand for labor largely on
its own. Public spending on education, healthcare and infrastructural
development did not stimulate private investment; the former could barely keep
up with the latter’s needs. More productive capacity came online after the end
of World War II than ever before in world history. But precisely for that
reason, international markets for manufactures quickly began to suffer from
overcapacity, issuing in a reduced pace of capital accumulation and falling
rates of output growth. The replication of technical capacities across the world
undermined the conditions for further rapid expansion. The result was wave after
wave of deindustrialization and a persistently low labor demand.
#+end_quote
- Debt-driven spending failed to stimulate high rates of economic growth, contra
Keynes
- Keynes believed it would make more sense, under conditions of economic
maturity, to shrink the labor supply rather than stimulate labor demand
- Capital throughout the postwar period had one tactical advantage to get its
way: the [[file:../20210312164354-capital_strike.org][capital strike]]
- [[file:../20210312164831-public_spending_cannot_fight_capital.org][You can’t fight capital with public spending]] in a [[file:../20210312164713-new_deal.org][New Deal]]-like manner. You
must existentially threaten the existence of these firms with full
socialization
- Some other automation theorists as well as radical Keynesians argue for the
implementation of [[file:../20210306161251-universal_basic_income.org][UBI]], which, they say, would eliminate poverty and create a
world of luxury where labor is absolute
+ UBI is a technocratic solution, however, which will do far from what it
intends
- [[file:../20210306161251-universal_basic_income.org][UBI]] has its origins in the thought of [[file:../20210312165519-thomas_paine.org][Thomas Paine]], who believed that all
adults should receive a lump sum of money at some time in their life
#+begin_quote
UBI proposals long predate the advent of the automation discourse. Some trace
their origin to Thomas Paine, who suggested as early as 1797 that a lump-sum
payment should be distributed to all individuals on reaching the age of
majority.28 Paine justified this coming-of-age grant along classically Lockean
lines, arguing that all land had originally been held in common but had since
been divided up into parcels of private property. Rising generations were
therefore unable to access their fair shares of humanity’s inheritance. For
Paine, coming-of-age grants could serve as the cash equivalent of each
person’s share in the common stock of the earth—and thus enable everyone to
participate in the world of private property. In his proposal, which
anticipates the concept of basic income, payments are not a way to create a
post-scarcity world, but rather to secure the moral foundations of a
private-ownership society.
#+end_quote
- [[file:../20200607211237-neoliberalism.org][Neoliberal]] economists such as [[file:../20210120222224-friedrich_hayek.org][Friedrich Hayek]] and [[file:../20210312165716-milton_friedman.org][Milton Friedman]] advocated
for [[file:../20210306161251-universal_basic_income.org][UBI]]
- UBI is very heavily invested in by [[file:../20210312170133-silicon_valley.org][Silicon Valley]] as well as right-wing
thinkers, who want to do away with [[file:../20210312170148-public_welfare.org][public welfare]]
- It is unlikely that a state and socio-economic system that wishes to preserve
itself would ever provide a UBI so generous that it would undermine its
existence
- For UBI to work it would need rising productivity levels, as automation
theorists already erroneously claim to be true
- “UBI would empower workers without disempowering capital.”
* 6. Necessity and Freedom
- Although the automation theorists are wrong, they at least have a vision for
the future
- Automation theorists do themselves a disservice by focusing on technological
progress rather than the conquest of production
- [[file:../20210312175353-it_is_important_for_socialists_to_have_a_vision_of_the_alternative.org][it is important for socialists to have a vision of the alternative]]
- Marx et. al. believed that a [[file:../20210306163746-post_scarcity.org][post-scarcity]] world was possible through the
active reorganization of social life, not through some weird trick
- An influence on [[file:../20200611202011-marx.org][Marx]] was [[file:../20210312180305-etienne_cabet.org][Étienne Cabet]], an early utopian writer
- “Abundance is a social relationship”
#+begin_quote
For a post-scarcity society to come into being, a literal cornucopia is not
required. It is only necessary that scarcity and its accompanying mentality be
overcome, so people can live, as More said, “with a joyful and tranquil frame
of mind, with no worries about making a living.”23 According to this
perspective, abundance is not a technological threshold to be crossed.
Instead, abundance is a social relationship, based on the principle that the
means of one’s existence will never be at stake in any of one’s relationships.
The steadfast security that such a principle implies is what allows all people
to ask “What am I going to do with the time I am alive?” rather than “How am I
going to keep living?”24 Some will choose to follow a single idea to its end,
others to periodically reinvent themselves. The main choice people will have
to make is how to “balance the goal of bettering oneself against the
injunction to better humanity” (as Captain Picard of the starship Enterprise
tells a financial mogul, who had been cryogenically frozen in the twenty-first
century only to be revived, to his horror, in a post-scarcity world).25
In such a world, there could still be sanctions to ensure that necessary work
is actually undertaken. However, inducements to work would not take the form
of threats of starvation, but invitations to cooperate. Economists have long
recognized that hunger and homelessness are not the best motivators. Even in
Kropotkin’s time, economists admitted that “the best situation for man is when
he produces in freedom, has choice in his occupations, has no overseer to
impede him, and when he sees his work bring a profit to himself and others
like him.”26 A bestselling writer on motivation recently rediscovered these
same ideas: feelings of autonomy, mastery, and purpose are what generate the
best work, not higher levels of monetary reward.27
The successful organization of a post-scarcity world would require that its
denizens solve, to their satisfaction, the problems posed by the twentieth
century’s socialist calculation debates. They would do so with the tools of
the twenty-first century: utilizing digital technologies to coordinate their
needs and activities by designing algorithms—which process data and present
alternatives—and protocols—which structure decisions about alternatives—that
could be further modified and adapted over time in light of experience.
Individuals would have to be able to use digital applications to articulate
their needs and to transmit these to associations, while associations, in
turn, would need to be able both to allocate resources among themselves and to
figure out how to make do with the resources they are able to acquire, in a
way that was fair and rational. Efficiency would no longer be an overriding
goal of production, but producers would still have to be able to make
reasonable choices among production techniques, based on the ease with which
they can access different sorts of supplies. It would have to be possible, as
well, to hold producers accountable were they to fail to meet democratically
determined social standards. Again, there is likely to be no single best way
to deal with these crucial problems.28
#+end_quote
- “Of course, the realm of freedom is about having time for both socializing and
solitude, for engaging in hobbies and doing nothing at all—“/rien faire comme
une bête/, lying on water and looking peacefully at the sky.”30 Frankfurt
School critical theorist Theodor Adorno’s phrase is suggestive of a world in
which material dispossession and the existential insecurity to which it gives
rise have been universally abolished.”
- “Without a clear vision of this coming world, it is easy to get lost along the
way.”
A probabilistic neural network that accounts for uncertainty in weights and outputs. A standard neural network regression model typically predicts a scalar value; for example, a model predicts a house price of 853,000. By contrast, a Bayesian neural network predicts a distribution of values; for example, a model predicts a house price of 853,000 with a standard deviation of 67,200. A Bayesian neural network relies on Bayes’ Theorem to calculate uncertainties in weights and predictions. A Bayesian neural network can be useful when it is important to quantify uncertainty, such as in models related to pharmaceuticals. Bayesian neural networks can also help prevent overfitting.
More in-depth than its read-baity title might suggetst. Gives a historical overview of [[Luddism]] and [[Marxism]] in relation to various struggles through history.
In this book, I aim to show how technology developed by capitalism furthers its goals: it compels us to work more, limits our autonomy, and outmaneuvers and divides us when we organize to fight back. In response, a flourishing class struggle will necessarily target the machines of the day, and I document the moments where it has.
There is a palpable rise in Luddite sentiments, as well as anti-capitalist ones. As the following chapters show, these attitudes complement each other, and hold the key to the future of radical politics.
Our history is the Luddites’ as well, and their insight—that technology was political, and that it could and, in many cases, should be opposed—has carried down through all manner of militant movements, including those of the present.
In the complaints of Turkle and Wu, we might hear echoes of Martin Heidegger, who criticized technology for alienating us, through its disenchanting and instrumentalizing nature, from the mystical experience of Being
the problem of technology is its role in capitalism.
“Twitter revolutions” in the Middle East have been ground into dust.
While their manifesto specified that they did not oppose technology as such, the neo-Luddites’ opposition to everything from genetic engineering to television, computers, and “electromagnetic technologies” belied a debt to anti-civilization anarcho-primitivist politics.
The wealthy and powerful understood machines as a method to accumulate power, and so too did the toiling classes over whom they wished to exert it.
But Hobsbawm suggests something further: that through machine breaking itself, the Luddites composed themselves as a class by creating bonds of solidarity.
Workers are organized and exploited according to their technical composition; they then develop the forms of struggle necessary for overcoming their divisions and fighting their exploitation.
In thinking about the politics of machine breaking as a form of solidarity —a means of [[class composition]]—Linebaugh knits together a host of disparate yet contemporaneous struggles connected to the onslaught of primitive accumulation of the early nineteenth century.
“Machinery hurtful to Commonality”
Marx and the Luddites
Luddism is intellectually compatible with Marxism
For Negri and his collaborator Michael Hardt, this self-valorizing and self-organizing character of immaterial labor implies an egalitarian future: “Immaterial labor thus seems to provide the potential for a kind of spontaneous and elementary communism.”
Page 55 [2022-10-21 Fri 18:19]:
They are called “labour-saving” machines—a commonly used phrase which implies what we expect of them; but we do not get what we expect. What they really do is to reduce the skilled labourer to the rank of the unskilled, to increase the number of the “reserve army of labour”—that is, to increase the precariousness of life among the workers and to intensify the labour of those who serve the machines (as slaves their masters).
Page 55 [2022-10-21 Fri 18:22]:
Morris’s definition of socialism as a qualitative restructuring of work and society—a top-to-bottom reconceptualization of social relations, rather than simply a more equitable redistribution of existing work and goods—placed him in diametrical opposition to another utopian of his time, Edward Bellamy.
Page 56 [2022-10-21 Fri 18:24]:
Socialistic bourgeois want all the advantages of modern social conditions without the struggles and dangers necessarily resulting therefrom. They desire the existing state of society, minus its revolutionary and dis-integrating elements. They wish for a bourgeoisie without a proletariat
Page 57 [2022-10-21 Fri 18:32]:
Technology is an important site of these struggles: not only is militant opposition to technology a historical fact, but it can suggest a more liberatory politics of work and technology—one that is more easily supported by Marx’s work than are contemporary post-work utopias.
Page 58 [2022-10-21 Fri 18:33]:
Furthermore, these struggles point toward the only vehicle for a liberation from capitalism: the composition of a militant struggling class that attacks capital in all its manifold dominations, including the technological.
Page 75 [2022-10-22 Sat 04:38]:
Socialism cannot arise from a crippled and stagnant capitalism, but only from a capitalism carried to its highest point of productivity,” he wrote in 1924. An entire Marxist tradition of endlessly deferred action and disdain for the struggles in the “periphery” of capitalist production has followed in its wake.
An exciting hypothesis that motivates this work is that making discourse graphs widely available could accelerate human synthesis work, and thereby [[accelerate innovation and scientific discovery]].
To understand why this information model might augment synthesis, consider a researcher who wants to understand what interventions might be most promising for mitigating online harassment. To synthesize a formulation of this complex interdisciplinary problem that can advance the state of the art, she needs material that can help her work through detailed answers to a range of questions. For example, which theories have the most empirical support in this particular setting? Are there conflicting theoretical predictions that might signal fruitful areas of inquiry? What are the key phenomena to keep in mind when designing an intervention (e.g., perceptions of human vs. automated action, procedural considerations, noise in judgments of wrongdoing, scale considerations for spread of harm)? What intervention patterns (whether technical, behavioral, or institutional) have been proposed that are both a) judged on theoretical and circumstantial grounds as likely to be effective in this setting, and b) lacking in direct evidence for efficacy?
The answers to these questions cannot be found simply in the titles of research papers, in groupings of papers by area, or even in citation or authorship networks. The answers lie at lower levels of granularity: the level of theoretical and empirical claims or statements made within publications. For example, "viewers in a Twitch chat engaged in less bad behaviors after a user was banned by a moderator for bad behavior", and "banning bad actors from a subreddit in 2015 was somewhat effective at mitigating spread of hate speech on other subreddits" are claims that interrelate in complex ways, both supporting other claims/theories that are in tension with each other.
This level of granularity is crucial not just for finding relevant claims to inform the synthesis, but also for constructing more complex arguments and theories, by connecting statements in logical and discursive relationships.
Beyond operating at the claim level, our researcher will also need to work through a range of contextual details. For example, to judge which studies, findings, or theories are most applicable to her setting, she needs to know key methodological details including the comparability of different studies’ interventions, settings, populations, and outcome measures. She might need to reason over the fact that two studies that concluded limited efficacy of bans had ban interventions that were quite short, on a forum with no identity verification. Or she might reason through the fact that a prominent theory of bad faith and discourse was proposed by a philosopher from the early 2000’s (before the rise of modern social media). To judge the validity of past findings (e.g., what has been established with sufficient certainty, where the frontier might be), she would need to know, for example, which findings came from which measures (e.g., self-report, behavioral measures), and the extent to which findings have been replicated cross authors from different labs, and across a variety of settings (e.g., year, platform, scale).
Hypothesized individual benefits: Creative synthesis and exploration§
A discourse graph as a data structure has key affordances that are hypothesized to enable just these sorts of synthesis operations. Information is represented primarily at the claim or statement level, and embedded in a graph of relationships with other claims and context. In a discourse graph, claims have many-to-many relationships to support composition of more complex arguments and theories, or "decompression" into component supporting/opposing claims. Contextual entities and information, such as methodological details and metadata, are explicitly included in the discourse graph. This supports direct analysis of claims with their evidentiary context, supporting critical engagement, integration, and even reinterpretation of individual findings. The following figure shows how this might be supported in the specific worked example above. Note that discourse graphs need not be represented or manipulated in this visual format; the underlying graph model can be instantiated in a variety of media, such as hypertext notebooks, and also implicitly in various analog implementations that allow for cross-referencing. What is important is the information architecture of representing networks of claims and their context.
Beyond the theoretical match between the kinds of queries scientists need to run over their evidence collection for synthesis, a discourse-centric representation that encodes granular claims instead of document "buckets" could facilitate exploration and conceptual combination. There is theoretical precedent for this in research on expertise and creative problem solving, where breaking complex ideas down into more meaningful, smaller conceptual "chunks" may be necessary for creative recombination into new conceptual wholes.1 Removing contextual details (though not losing the ability to recover them) may also be necessary and useful for synthesizing ideas and reusing knowledge across boundaries.[^2]
At the same time, constructive and creative engagement with contextual details, is thought to be necessary for developing novel conceptual wholes from "data", such as in sensemaking,[^3] systematic reviews,[^4] or formal theory development.[^5] This is a more specific application of the general insight that [[C- Context is necessary for knowledge reuse]]. Further, accurately predicting just which contextual details are necessary to represent directly in an information object is a difficult task[^6] that may be functionally impossible in creative settings.
The conjunction of these affordances —- having both granular information objects like claims, and the ability to progressively expand their context by traversing/retrieving from the discourse graphs —- may help to resolve this tension between granularity and contextualizability. For instance, graph-model and hypertext affordances like hyperlinking or transclusion might enable scientists to hide "extraneous details" (to facilitate compression) without destructively blocking future reusers from obtaining necessary contextual details for reuse.[^6]
Hypothesized collective benefits: Reduced overhead, and enhanced creative reuse§
Discourse graphs (or parts thereof) could also significantly reduce the overhead to synthesis through reuse and repurposing over time, across projects, and potentially even across people.[^7] For example, imagine collaborators sharing discourse graphs with each other, rather than simple documents full of unstructured notes, to speed up the process of working towards shared mental models and identifying productive areas of divergence; or a lab onboarding new researchers not with long reading lists, but with discourse graph subsets they can build on over time. How much effort could be reduced if this were a reality?
The same affordances of discourse graphs around granularity and contextualizability that are hypothesized to augment individual synthesis should also facilitate exploration and reuse of an evidence collection that was created by someone else, or by oneself in the past. For example, granular representation of scientific ideas at the claim level is a much better theoretical match for the kinds of queries that scientists want to ask of an evidence collection during synthesis.2
These claims may also be more to the level of processing required to be understood and reused by others, compared to raw annotations and marginalia.[^9] Also, ambiguity around concepts can be a significant barrier to reuse across knowledge boundaries. For example, keyword search is only really useful when there is a stable, shared understanding of ontology:[^10] this condition is almost certainly not present when [[crossing knowledge boundaries]][^11] and perhaps not even within fields of study with [[significant ongoing controversy]] amongst different schools of thought [^12]
In these settings, judging that two things are "the same" is problematic and difficult task; doing so without engagement with context can sometimes introduce more destructive ambiguity, not less, a hard-won lesson from the history of Semantic Web,[^13] ontology[^14] and classification efforts.[^15] A discourse-centric graph that embeds concepts in discourse contexts, traversing through networks of contextual details (such as authors, measures, contexts), and perhaps augmented by formal concepts as hooks, may be a better match for exploring ideas across knowledge boundaries. Further, although in many instances of knowledge reuse, contextual details tend to vary substantially across reuse tasks,[^16] there might be sufficient overlap of useful contextual details (e.g., participant information, study context) that remain stable across reuse tasks.[^17]
Jobs that are often done by women, so-called ‘pink-collar’ jobs in health and education, not only represent some of the strongest segments of the labour movement today but also foreshadow the shift to a zero-carbon economy that prioritizes care work over extractive labour.
[[Ujima]] ([[Collective work]] and responsibility): To build and maintain our community together and make our brothers’ and sisters’ problems our problems and to solve them together.
Commons Network is a collaboratory for the social and ecological transition. We bring together people and ideas and we provide tools and insights for social movements, governments and community groups. We explore new models for economy and society in order to collectively transform the system and shape a caring and just future.
A neural network in which at least one layer is a convolutional layer. A typical convolutional neural network consists of some combination of the following layers:
convolutional layers
pooling layers
dense layers
Convolutional neural networks have had great success in certain kinds of problems, such as image recognition.
"We reject siloed and centralised hegemonies; we believe in the promise of Cosmos for a truly interoperable and decentralised future for [[governance]] and [[finance]]; we provide the building blocks for the future of [[finance]] and beyond.”
Deep Work: Rules for Focused Success in a Distracted World by Cal Newport
Notes
Deep Work: Professional activities performed in a state of distraction-free concentration that push your cognitive capabilities to their limit. These efforts create new value, improve your skill, and are hard to replicate.
We now know from decades of research in both psychology and neuroscience that the state of mental strain that accompanies deep work is also necessary to improve your abilities.
Why talent / ability to do deep work is important in today’s world
In a seminal 1981 paper, the economist Sherwin Rosen worked out the mathematics behind these “winner-take-all” markets.
explicitly model talent—as a factor with “imperfect substitution,” which Rosen explains as follows:
“Hearing a succession of mediocre singers does not add up to a single outstanding performance.”
talent is not a commodity you can buy in bulk and combine to reach the needed levels: There’s a premium to being the best. Therefore, if you’re in a marketplace where the consumer has access to all performers, and everyone’s q value is clear, the consumer will choose the very best. Even if the talent advantage of the best is small compared to the next rung down on the skill ladder, the superstars still win the bulk of the market.
I just identified two groups that are poised to thrive and that I claim are accessible:
those who can work creatively with intelligent machines and
those who are stars in their field.
Two Core Abilities for Thriving in the New Economy
The ability to quickly master hard things.
The ability to produce at an elite level, in terms of both quality and speed.
“Let your mind become a lens, thanks to the converging rays of attention; let your soul be all intent on whatever it is that is established in your mind as a dominant, wholly absorbing idea.” This advice comes from Antonin-Gilbert Sertillanges, a Dominican friar and professor of moral philosophy, who during the early part of the twentieth century penned a slim but influential volume titled The Intellectual Life.
a guide to “the development and deepening of the mind” for those called to make a living in the world of ideas.
Performance psychology
This task of formalization began in earnest in the 1970s, when a branch of psychology, sometimes called performance psychology, began to systematically explore what separates experts (in many different fields) from everyone else.
In the early 1990s, K. Anders Ericsson, a professor at Florida State University, pulled together these strands into a single coherent answer, consistent with the growing research literature, that he gave a punchy name: deliberate practice. Ericsson opens his seminal paper on the topic with a powerful claim: “We deny that these differences [between expert performers and normal adults] are immutable… Instead, we argue that the differences between expert performers and normal adults reflect a life-long period of deliberate effort to improve performance in a specific domain.”
In the intervening decades since K. Anders Ericsson’s first major papers on the topic, however, neuroscientists have been exploring the physical mechanisms that drive people’s improvements on hard tasks.
As the journalist Daniel Coyle surveys in his 2009 book, The Talent Code, these scientists increasingly believe the answer includes
myelin
a layer of fatty tissue that grows around neurons, acting like an insulator that allows the cells to fire faster and cleaner.
To understand the role of myelin in improvement, keep in mind that skills, be they intellectual or physical, eventually reduce down to brain circuits.
This new science of performance argues that you get better at a skill as you develop more myelin around the relevant neurons, allowing the corresponding circuit to fire more effortlessly and effectively. To be great at something is to be well myelinated.
srs
Attention residue
Sophie Leroy, a business professor at the University of Minnesota. In a 2009 paper, titled, intriguingly, “Why Is It So Hard to Do My Work?,” Leroy introduced an effect she called attention residue. In the introduction to this paper, she noted that other researchers have studied the effect of multitasking—trying to accomplish multiple tasks simultaneously—on performance, but that in the modern knowledge work office, once you got to a high enough level, it was more common to find people working on multiple projects sequentially:
The problem this research identifies with this work strategy is that when you switch from some Task A to another Task B, your attention doesn’t immediately follow—a residue of your attention remains stuck thinking about the original task. This residue gets especially thick if your work on Task A was unbounded and of low intensity before you switched, but even if you finish Task A before moving on, your attention remains divided for a while.
Ref: Just-in-Time Productivity
srs
Organization of modern knowledge work
Busyness as Proxy for Productivity: In the absence of clear indicators of what it means to be productive and valuable in their jobs, many knowledge workers turn back toward an industrial indicator of productivity: doing lots of stuff in a visible manner.
Deep work and happiness, meaning in life
The science writer Winifred Gallagher stumbled onto a connection between attention and happiness after an unexpected and terrifying event, a cancer diagnosis—“not just cancer,” she clarifies, “but a particularly nasty, fairly advanced kind.” As Gallagher recalls in her 2009 book Rapt,
Like fingers pointing to the moon, other diverse disciplines from anthropology to education, behavioral economics to family counseling, similarly suggest that the skillful management of attention is the sine qua non of the good life and the key to improving virtually every aspect of your experience.
**We tend to place a lot of emphasis on our circumstances, assuming that what happens to us (or fails to happen) determines how we feel. **From this perspective, the small-scale details of how you spend your day aren’t that important, because what matters are the large-scale outcomes, such as whether or not you get a promotion or move to that nicer apartment. According to Gallagher, decades of research contradict this understanding. Our brains instead construct our worldview based on what we pay attention to.
As Gallagher summarizes: “Who you are, what you think, feel, and do, what you love—is the sum of what you focus on.”
But the results from Mihaly Csikszentmihalyi ESM studies reveal that most people have this wrong:** Ironically, jobs are actually easier to enjoy than free time, because like flow activities they have built-in goals, feedback rules, and challenges, all of which encourage one to become involved in one’s work, to concentrate and lose oneself in it. Free time, on the other hand, is unstructured, and requires much greater effort to be shaped into something that can be enjoyed.**
There is, of course, overlap between the theory of flow and the ideas of Winifred Gallagher highlighted in the last section. Both point toward the importance of depth over shallowness, but they focus on two different explanations for this importance. Gallagher’s writing emphasizes that the content of what we focus on matters. If we give rapt attention to important things, and therefore also ignore shallow negative things, we’ll experience our working life as more important and positive. Csikszentmihalyi’s theory of flow, by contrast, is mostly agnostic to the content of our attention. Though he would likely agree with the research cited by Gallagher, his theory notes that the feeling of going deep is in itself very rewarding. Our minds like this challenge, regardless of the subject.
In 2011, Dreyfus and Kelly published a book, All Things Shining, which explores how notions of sacredness and meaning have evolved throughout the history of human culture. They set out to reconstruct this history because they’re worried about its endpoint in our current era. “The world used to be, in its various forms, a world of sacred, shining things,” Dreyfus and Kelly explain early in the book. “The shining things now seem far away.”
The craftsmen they cite don’t have rarified jobs. Throughout most of human history, to be a blacksmith or a wheelwright wasn’t glamorous. But this doesn’t matter, as the specifics of the work are irrelevant. The meaning uncovered by such efforts is due to the skill and appreciation inherent in craftsmanship—not the outcomes of their work. Put another way, a wooden wheel is not noble, but its shaping can be. The same applies to knowledge work. You don’t need a rarified job; you need instead a rarified approach to your work.
Seems to connect more to concepts of Flow than Gallagher’s thesis about content of focus mattering
How to do deep work
Deep work chambers - architecture
This brings us to the final room of the machine, a collection of what Dewane calls “deep work chambers” (he adopted the term “deep work” from my articles on the topic). Each chamber is conceived to be six by ten feet and protected by thick soundproof walls (Dewane’s plans call for eighteen inches of insulation). “The purpose of the deep work chamber is to allow for total focus and uninterrupted work flow,” Dewane explains. He imagines a process in which you spend ninety minutes inside, take a ninety-minute break, and repeat two or three times—at which point your brain will have achieved its limit of concentration for the day.
Note: What about collaboration.
The key to developing a deep work habit is to move beyond good intentions and add routines and rituals to your working life designed to minimize the amount of your limited willpower necessary to transition into and maintain a state of unbroken concentration.
(This issue is so important to Neal Stephenson that he went on to explore its implications—positive and negative—in his 2008 science fiction epic, Anathem, which considers a world where an intellectual elite live in monastic orders, isolated from the distracted masses and technology, thinking deep thoughts.)
Bi-modal (monastic vs worldly)
Carl Jung’s approach is what I call the bimodal philosophy of deep work. This philosophy asks that you divide your time, dedicating some clearly defined stretches to deep pursuits and leaving the rest open to everything else. During the deep time, the bimodal worker will act monastically—seeking intense and uninterrupted concentration. During the shallow time, such focus is not prioritized. This division of time between deep and open can happen on multiple scales. For example, on the scale of a week, you might dedicate a four-day weekend to depth and the rest to open time. Similarly, on the scale of a year, you might dedicate one season to contain most of your deep stretches (as many academics do over the summer or while on sabbatical).
Rhytmic (regular habit)
This philosophy argues that the easiest way to consistently start deep work sessions is to transform them into a simple regular habit. The goal, in other words, is to generate a rhythm for this work that removes the need for you to invest energy in deciding if and when you’re going to go deep.
The chain method
is a good example of the rhythmic philosophy of deep work scheduling because it combines a simple scheduling heuristic (do the work every day), with an easy way to remind yourself to do the work: the big red Xs on the calendar.
Fixed starting time.
Another common way to implement the rhythmic philosophy is to replace the visual aid of the chain method with a set starting time that you use every day for deep work. In much the same way that maintaining visual indicators of your work progress can reduce the barrier to entry for going deep, eliminating even the simplest scheduling decisions, such as when during the day to do the work, also reduces this barrier.
Use of rituals
Great minds like Caro and Darwin didn’t deploy rituals to be weird; they did so because success in their work depended on their ability to go deep, again and again—there’s
Their rituals minimized the friction in this transition to depth, allowing them to go deep more easily and stay in the state longer.
Ingredients:
Where you’ll work and for how long. Your ritual needs to specify a location for your deep work efforts.
How you’ll work once you start to work.
Your ritual needs rules and processes to keep your efforts structured. For example, you might institute a ban on any Internet use, or maintain a metric such as words produced per twenty-minute interval to keep your concentration honed. Without this structure, you’ll have to mentally litigate again and again what you should and should not be doing during these sessions and keep trying to assess whether you’re working sufficiently hard. These are unnecessary drains on your willpower reserves.
Link to Ultraworking
How you’ll support your work.
Your ritual needs to ensure your brain gets the support it needs to keep operating at a high level of depth. For example, the ritual might specify that you start with a cup of good coffee, or make sure you have access to enough food of the right type to maintain energy, or integrate light exercise such as walking to help keep the mind clear.
environmental factors,
such as organizing the raw materials of your work to minimize energy-dissipating friction (as we saw with Caro’s example).
the grand gesture.
The concept is simple: By leveraging a radical change to your normal environment, coupled perhaps with a significant investment of effort or money, all dedicated toward supporting a deep work task, you increase the perceived importance of the task. This boost in importance reduces your mind’s instinct to procrastinate and delivers an injection of motivation and energy.
you should track time spent in deep work (lead measure), not output
4DX Method
Once you’ve identified a wildly important goal, you need to measure your success.
two types of metrics for this purpose: lag measures and lead measures.
Lag measures
describe the thing you’re ultimately trying to improve. For example, if your goal is to increase customer satisfaction in your bakery, then the relevant lag measure is your customer satisfaction scores. As the 4DX authors explain, the problem with lag measures is that they come too late to change your behavior: “When you receive them, the performance that drove them is already in the past.”
Lead measures,
“measure the new behaviors that will drive success on the lag measures.” In the bakery example, a good lead measure might be the number of customers who receive free samples. This is a number you can directly increase by giving out more samples.
For an individual focused on deep work, it’s easy to identify the relevant lead measure:
time spent in a state of deep work dedicated toward your wildly important goal.
I used to focus on lag measures,
such as papers published per year. These measures, however, lacked influence on my day-to-day behavior because there was nothing I could do in the short term that could immediately generate a noticeable change to this long-term metric.
When I shifted to tracking deep work hours, suddenly these measures became relevant to my day-to-day: Every hour extra of deep work was immediately reflected in my tally.
scoreboard
In my early experiments with 4DX, I settled on a simple but effective solution for implementing this scoreboard. I took a piece of card stock and divided it into rows, one for each week of the current semester. I then labeled each row with the dates of the week and taped it to the wall next to my computer monitor (where it couldn’t be ignored). As each week progressed, I kept track of the hours spent in deep work that week with a simple tally of tick marks in that week’s row. To maximize the motivation generated by this scoreboard, whenever I reached an important milestone in an academic paper (e.g., solving a key proof), I would circle the tally mark corresponding to the hour where I finished the result.
the habit of a Weekly review in which you make a plan for the workweek ahead (see Rule #4). During my experiments with 4DX, I used a weekly review to look over my scoreboard to celebrate good weeks, help understand what led to bad weeks, and most important, figure out how to ensure a good score for the days ahead. This led me to adjust my schedule to meet the needs of my lead measure—enabling significantly more deep work than if I had avoided such reviews altogether.
Daily Plan - shutdown habit at the end of the day
At the end of the workday, shut down your consideration of work issues until the next morning—no after-dinner e-mail check, no mental replays of conversations, and no scheming about how you’ll handle an upcoming challenge; shut down work thinking completely. If you need more time, then extend your workday, but once you shut down, your mind must be left free to encounter Kreider’s buttercups, stink bugs, and stars.
Dutch psychologist Ap Dijksterhuis, set out to prove that some decisions are better left to your unconscious mind to untangle. - unconscious thought theory
In other words, to actively try to work through these decisions will lead to a worse outcome than loading up the relevant information and then moving on to something else while letting the subconscious layers of your mind mull things over.
Observations from experiments such as this one led Dijksterhuis and his collaborators to introduce unconscious thought theory (UTT)—an attempt to understand the different roles conscious and unconscious deliberation play in decision making.
At a high level, this theory proposes that
**for decisions that require the application of strict rules, the conscious mind must be involved. **
For example, if you need to do a math calculation, only your conscious mind is able to follow the precise arithmetic rules needed for correctness. On the other hand,
**for decisions that involve large amounts of information and multiple vague, and perhaps even conflicting, constraints, your unconscious mind is well suited to tackle the issue. ** #**holding an intention** #**System 1/2**
UTT hypothesizes that this is due to the fact that these regions of your brain have more neuronal bandwidth available, allowing them to move around more information and sift through more potential solutions than your conscious centers of thinking.
Your conscious mind, according to this theory, is like a home computer on which you can run carefully written programs that return correct answers to limited problems, whereas your unconscious mind is like Google’s vast data centers, in which statistical algorithms sift through terabytes of unstructured information, teasing out surprising useful solutions to difficult questions.
The implication of this line of research is that providing your conscious brain time to rest enables your unconscious mind to take a shift sorting through your most complex professional challenges. A shutdown habit, therefore, is not necessarily reducing the amount of time you’re engaged in productive work, but is instead diversifying the type of work you deploy.
Another key commitment for succeeding with this strategy is to support your commitment to shutting down with a strict shutdown ritual that you use at the end of the workday to maximize the probability that you succeed. In more detail, this ritual should ensure that every incomplete task, goal, or project has been reviewed and that for each you have confirmed that either (1) you have a plan you trust for its completion, or (2) it’s captured in a place where it will be revisited when the time is right. The process should be an algorithm: a series of steps you always conduct, one after another. When you’re done, have a set phrase you say that indicates completion (to end my own ritual, I say, “Shutdown complete”). This final step sounds cheesy, but it provides a simple cue to your mind that it’s safe to release work-related thoughts for the rest of the day.
To make this suggestion more concrete, let me walk through the steps of my own shutdown ritual (which I first developed around the time I was writing my doctoral dissertation, and have deployed, in one form or another, ever since). The first thing I do is take a final look at my e-mail inbox to ensure that there’s nothing requiring an urgent response before the day ends. The next thing I do is transfer any new tasks that are on my mind or were scribbled down earlier in the day into my official task lists. (I use Google Docs for storing my task lists, as I like the ability to access them from any computer—but the technology here isn’t really relevant.) Once I have these task lists open, I quickly skim every task in every list, and then look at the next few days on my calendar. These two actions ensure that there’s nothing urgent I’m forgetting or any important deadlines or appointments sneaking up on me. I have, at this point, reviewed everything that’s on my professional plate. To end the ritual, I use this information to make a rough plan for the next day. Once the plan is created, I say, “Shutdown complete,” and my work thoughts are done for the day.
attention restoration theory (ART), which claims that spending time in nature can improve your ability to concentrate. This theory, which was first proposed in the 1980s by the University of Michigan psychologists Rachel Kaplan and Stephen Kaplan, is based on the concept of [[attention fatigue]].
This resource is finite: If you exhaust it, you’ll struggle to concentrate. (For our purposes, we can think of this resource as the same thing as Roy F. Baumeister‘s limited willpower reserves we discussed in the introduction to this rule.*)
The 2008 study argues that walking on busy city streets requires you to use directed attention, as you must navigate complicated tasks like figuring out when to cross a street to not get run over, or when to maneuver around the slow group of tourists blocking the sidewalk. After just fifty minutes of this focused navigation, the subject’s store of directed attention was low.
Walking through nature, by contrast, exposes you to what lead author Marc Berman calls “inherently fascinating stimuli,” using sunsets as an example. These stimuli “invoke attention modestly, allowing focused-attention mechanisms a chance to replenish.”
Put another way, when walking through nature, you’re freed from having to direct your attention, as there are few challenges to navigate (like crowded street crossings), and experience enough interesting stimuli to keep your mind sufficiently occupied to avoid the need to actively aim your attention.
This state allows your directed attention resources time to replenish. After fifty minutes of such replenishment, the subjects enjoyed a boost in their concentration.
(You might, of course, argue that perhaps being outside watching a sunset puts people in a good mood, and being in a good mood is what really helps performance on these tasks.
But in a sadistic twist, the researchers debunked that hypothesis by repeating the experiment in the harsh Ann Arbor winter. Walking outside in brutal cold conditions didn’t put the subjects in a good mood, but they still ended up doing better on concentration tasks.)
srs
In K. Anders Ericsson’s seminal 1993 paper on the topic, titled “The Role of Deliberate Practice in the Acquisition of Expert Performance,” - max four hours per day for experts, less for novices
he dedicates a section to reviewing what the research literature reveals about an individual’s capacity for cognitively demanding work.
K. Anders Ericsson notes that for a novice, somewhere around an hour a day of intense concentration seems to be a limit, while for experts this number can expand to as many as four hours—but rarely more.
the Zeigarnik effect.
This effect, which is named for the experimental work of the early-twentieth-century psychologist Bluma Zeigarnik, describes the ability of incomplete tasks to dominate our attention.
It tells us that if you simply stop whatever you are doing at five p.m. and declare, “I’m done with work until tomorrow,” you’ll likely struggle to keep your mind clear of professional issues, as the many obligations left unresolved in your mind will, as in Bluma Zeigarnik’s experiments, keep battling for your attention throughout the evening (a battle that they’ll often win).
Riding to our rescue in this matter is our friend from earlier in the rule, the psychologist Roy F. Baumeister, who wrote a paper with E.J. Masicampo playfully titled “Consider It Done!”
In this study, the two researchers began by replicating the Zeigarnik effect in their subjects (in this case, the researchers assigned a task and then cruelly engineered interruptions), but then found that they could significantly reduce the effect’s impact by asking the subjects, soon after the interruption, to make a plan for how they would later complete the incomplete task. To quote the paper: “Committing to a specific plan for a goal may therefore not only facilitate attainment of the goal but may also free cognitive resources for other pursuits.”
Clifford Nass summarizing these findings in a 2010 interview with NPR’s Ira Flatow:
So we have scales that allow us to divide up people into people who multitask all the time and people who rarely do, and the differences are remarkable.
People who multitask all the time can’t filter out irrelevancy. They can’t manage a working memory. They’re chronically distracted.
They initiate much larger parts of their brain that are irrelevant to the task at hand… they’re pretty much mental wrecks.
At this point Flatow asks Nass whether the chronically distracted recognize this rewiring of their brain:
The people we talk with continually said, “look, when I really have to concentrate, I turn off everything and I am laser-focused.” And unfortunately, they’ve developed habits of mind that make it impossible for them to be laser-focused. They’re suckers for irrelevancy. They just can’t keep on task. [emphasis mine]
Training deep focus
Rule #2 will help you significantly improve this limit. The strategies that follow are motivated by the key idea that getting the most out of your deep work habit requires training, and as clarified previously, this training must address two goals: improving your ability to concentrate intensely and overcoming your desire for distraction.
Instead of scheduling the occasional break from distraction so you can focus, you should instead schedule the occasional break from focus to give in to distraction. To make this suggestion more concrete, let’s make the simplifying assumption that Internet use is synonymous with seeking distracting stimuli.
Schedule in advance when you’ll use the Internet, and then avoid it altogether outside these times. I suggest that you keep a notepad near your computer at work. On this pad, record the next time you’re allowed to use the Internet. Until you arrive at that time, absolutely no network connectivity is allowed—no matter how tempting. The idea motivating this strategy is that the use of a distracting service does not, by itself, reduce your brain’s ability to focus. It’s instead the constant switching from low-stimuli/high-value activities to high-stimuli/low-value activities, at the slightest hint of boredom or cognitive challenge, that teaches your mind to never tolerate an absence of novelty. This constant switching can be understood analogously as weakening the mental muscles responsible for organizing the many sources vying for your attention. By segregating Internet use (and therefore segregating distractions) you’re minimizing the number of times you give in to distraction, and by doing so you let these attention-selecting muscles strengthen. For example, if you’ve scheduled your next Internet block thirty minutes from the current moment, and you’re beginning to feel bored and crave distraction, the next thirty minutes of resistance become a session of concentration calisthenics. A full day of scheduled distraction therefore becomes a full day of similar mental training.
Point #2: Regardless of how you schedule your Internet blocks, you must keep the time outside these blocks absolutely free from Internet use.
If this is infeasible—perhaps you need to get the current offline activity done promptly—then the correct response is to change your schedule so that your next Internet block begins sooner. The key in making this change, however, is to not schedule the next Internet block to occur immediately. Instead, enforce at least a five-minute gap between the current moment and the next time you can go online. This gap is minor, so it won’t excessively impede your progress, but from a behavioralist perspective, it’s substantial because it separates the sensation of wanting to go online from the reward of actually doing so.
Point #3: Scheduling Internet use at home as well as at work can further improve your concentration training.
The key here isn’t to avoid or even to reduce the total amount of time you spend engaging in distracting behavior, but is instead to give yourself plenty of opportunities throughout your evening to resist switching to these distractions at the slightest hint of boredom. One place where this strategy becomes particularly difficult outside work is when you’re forced to wait (for example, standing in line at a store). It’s crucial in these situations that if you’re in an offline block, you simply gird yourself for the temporary boredom, and fight through it with only the company of your thoughts. To simply wait and be bored has become a novel experience in modern life, but from the perspective of concentration training, it’s incredibly valuable. To
identify a deep task (that is, something that requires deep work to complete) that’s high on your priority list. Estimate how long you’d normally put aside for an obligation of this type, then give yourself a hard deadline that drastically reduces this time. If possible, commit publicly to the deadline—for example, by telling the person expecting the finished project when they should expect it. If this isn’t possible (or if it puts your job in jeopardy), then motivate yourself by setting a countdown timer on your phone and propping it up where you can’t avoid seeing it as you work. At this point, there should be only one possible way to get the deep task done in time: working with great intensity—no e-mail breaks, no daydreaming, no Facebook browsing, no repeated trips to the coffee machine. Like Roosevelt at Harvard, attack the task with every free neuron until it gives way under your unwavering barrage of concentration. Try this experiment no more than once a week at first—giving your brain practice with intensity, but also giving it (and your stress levels) time to rest in between. Once you feel confident in your ability to trade concentration for completion time, increase the frequency of these Roosevelt dashes. Remember, however, to always keep your self-imposed deadlines right at the edge of feasibility.
The main motivation for this strategy is straightforward. Deep work requires levels of concentration well beyond where most knowledge workers are comfortable. Roosevelt dashes leverage artificial deadlines to help you systematically increase the level you can regularly achieve—providing, in some sense, interval training for the attention centers of your brain. An additional benefit is that these dashes are incompatible with distraction (there’s no way you can give in to distraction and still make your deadlines). Therefore, every completed dash provides a session in which you’re potentially bored, and really want to seek more novel stimuli—but you resist. As argued in the previous strategy, the more you practice resisting such urges, the easier such resistance becomes. After a few months of deploying this strategy, your understanding of what it means to focus will likely be transformed as you reach levels of intensity stronger than anything you’ve experienced before.
productive meditation. The goal of productive meditation is to take a period in which you’re occupied physically but not mentally—walking, jogging, driving, showering—and focus your attention on a single well-defined professional problem. Depending on your profession, this problem might be outlining an article, writing a talk, making progress on a proof, or attempting to sharpen a business strategy. As in mindfulness meditation, you must continue to bring your attention back to the problem at hand when it wanders or stalls.
In my experience, productive meditation builds on both of the key ideas introduced at the beginning of this rule. By forcing you to resist distraction and return your attention repeatedly to a well-defined problem, it helps strengthen your distraction-resisting muscles, and by forcing you to push your focus deeper and deeper on a single problem, it sharpens your concentration.
Suggestion #1: Be Wary of Distractions and Looping
When faced with a hard problem, your mind, as it was evolved to do, will attempt to avoid excess expenditure of energy when possible. One way it might attempt to sidestep this expenditure is by avoiding diving deeper into the problem by instead looping over and over again on what you already know about it. For example, when working on a proof, my mind has a tendency to rehash simple preliminary results, again and again, to avoid the harder work of building on these results toward the needed solution. You must be on your guard for looping, as it can quickly subvert an entire productive meditation session. When you notice it, remark to yourself that you seem to be in a loop, then redirect your attention toward the next step.
“Thinking deeply” about a problem seems like a self-evident activity, but in reality it’s not. When faced with a distraction-free mental landscape, a hard problem, and time to think, the next steps can become surprisingly non-obvious. In my experience, it helps to have some structure for this deep thinking process. I suggest starting with a careful review of the relevant variables for solving the problem and then storing these values in your working memory. For example, if you’re working on the outline for a book chapter, the relevant variables might be the main points you want to make in the chapter.
Once the relevant variables are identified, define the specific next-step question you need to answer using these variables. In the book chapter example, this next-step question might be, “How am I going to effectively open this chapter?,”
Assuming you’re able to solve your next-step question, the final step of this structured approach to deep thinking is to consolidate your gains by reviewing clearly the answer you identified. At this point, you can push yourself to the next level of depth by starting the process over.
They wanted to understand what differentiated these elite memorizers from the population at large. “We found that one of the biggest differences between memory athletes and the rest of us is in a cognitive ability that’s not a direct measure of memory at all but of attention,” explained Roediger in a New York Times blog post (emphasis mine). The ability in question is called “attentional control,” and it measures the subjects’ ability to maintain their focus on essential information.
More important than your ability to impress friends, of course, is the training such activities provide your mind. Proceeding through the steps described earlier requires that you focus your attention, again and again, on a clear target. Like a muscle responding to weights, this will strengthen your general ability to concentrate—allowing you to go deeper with more ease. It’s worth emphasizing, however, the obvious point that there’s nothing special about card memorization. Any structured thought process that requires unwavering attention can have a similar effect—be it studying the Talmud, like Adam Marlin from Rule #2’s introduction, or practicing productive meditation, or trying to learn the guitar part of a song by ear (a past favorite of mine). If card memorization seems weird to you, in other words, then choose a replacement that makes similar cognitive requirements. The key to this strategy is not the specifics, but instead the motivating idea that your ability to concentrate is only as strong as your commitment to train it.
Note: Memory palace for deck of cards
The Craftsman Approach to Tool Selection: Identify the core factors that determine success and happiness in your professional and personal life. Adopt a tool only if its positive impacts on these factors substantially outweigh its negative impacts.
Once you’ve identified these goals, list for each the two or three most important activities that help you satisfy the goal. These activities should be specific enough to allow you to clearly picture doing them. On the other hand, they should be general enough that they’re not tied to a onetime outcome. For example, “do better research” is too general (what does it look like to be “doing better research”?), while “finish paper on broadcast lower bounds in time for upcoming conference submission” is too specific (it’s a onetime outcome). A good activity in this context would be something like: “regularly read and understand the cutting-edge results in my field.” The next step in this strategy is to consider the network tools you currently use. For each such tool, go through the key activities you identified and ask whether the use of the tool has a substantially positive impact, a substantially negative impact, or little impact on your regular and successful participation in the activity. Now comes the important decision: Keep using this tool only if you concluded that it has substantial positive impacts and that these outweigh the negative impacts. To help illustrate this strategy in action, let’s
The Law of the Vital Few*: In many settings, 80 percent of a given effect is due to just 20 percent of the possible causes. For example, it might be the case that 80 percent of a business’s profits come from just 20 percent of its clients, 80 percent of a nation’s wealth is held by its richest 20 percent of citizens, or 80 percent of computer software crashes come from just 20 percent of the identified bugs. There’s a formal mathematical underpinning to this phenomenon (an 80/20 split is roughly what you would expect when describing a power law distribution over impact—a type of distribution that shows up often when measuring quantities in the real world), but it’s probably most useful when applied heuristically as a reminder that, in many cases, contributions to an outcome are not evenly distributed. Moving
Instead of “packing,” however, you’ll instead ban yourself from using them for thirty days. All of them: Facebook, Instagram, Google+, Twitter, Snapchat, Vine—or whatever other services have risen to popularity since I first wrote these words. Don’t formally deactivate these services, and (this is important) don’t mention online that you’ll be signing off: Just stop using them, cold turkey. If someone reaches out to you by other means and asks why your activity on a particular service has fallen off, you can explain, but don’t go out of your way to tell people.
After thirty days of this self-imposed network isolation, ask yourself the following two questions about each of the services you temporarily quit: 1. Would the last thirty days have been notably better if I had been able to use this service? 2. Did people care that I wasn’t using this service?
The “great and profound mistake which my typical man makes in regard to his day,” he elaborates, is that even though he doesn’t particularly enjoy his work (seeing it as something to “get through”), “he persists in looking upon those hours from ten to six as ‘the day,’ to which the ten hours preceding them and the six hours following them are nothing but a prologue and epilogue.” This is an attitude that Bennett condemns as “utterly illogical and unhealthy.”
Put more thought into your leisure time. In other words, this strategy suggests that when it comes to your relaxation, don’t default to whatever catches your attention at the moment, but instead dedicate some advance thinking to the question of how you want to spend your “day within a day.”
Bennett, to his credit, anticipated this complaint. As he argues, such worries misunderstand what energizes the human spirit: What? You say that full energy given to those sixteen hours will lessen the value of the business eight? Not so. On the contrary, it will assuredly increase the value of the business eight. One of the chief things which my typical man has to learn is that the mental faculties are capable of a continuous hard activity; they do not tire like an arm or a leg. All they want is change—not rest, except in sleep.
We spend much of our day on autopilot—not giving much thought to what we’re doing with our time. This is a problem. It’s difficult to prevent the trivial from creeping into every corner of your schedule if you don’t face, without flinching, your current balance between deep and shallow work, and then adopt the habit of pausing before action and asking, “What makes the most sense right now?”
Schedule every minute of your day.
Your goal is not to stick to a given schedule at all costs; it’s instead to maintain, at all times, a thoughtful say in what you’re doing with your time going forward—even if these decisions are reworked again and again as the day unfolds.
Quantify the Depth of Every Activity
To do so, it asks that you evaluate activities by asking a simple (but surprisingly illuminating) question: How long would it take (in months) to train a smart recent college graduate with no specialized training in my field to complete this task?
Here’s an important question that’s rarely asked: What percentage of my time should be spent on shallow work? This strategy suggests that you ask it. If you have a boss, in other words, have a conversation about this question. (You’ll probably have to first define for him or her what “shallow” and “deep” work means.) If you work for yourself, ask yourself this question. In both cases, settle on a specific answer. Then—and this is the important part—try to stick to this budget.
For most people in most non-entry-level knowledge work jobs, the answer to the question will be somewhere in the 30 to 50 percent range
fixed-schedule productivity, as I fix the firm goal of not working past a certain time, then work backward to find productivity strategies that allow me to satisfy this declaration.
Fixed-schedule productivity, in other words, is a meta-habit that’s simple to adopt but broad in its impact. If you have to choose just one behavior that reorients your focus toward the deep, this one should be high on your list of possibilities.
What is the project represented by this message, and what is the most efficient (in terms of messages generated) process for bringing this project to a successful conclusion?
Process-Centric Response to E-mail
a good process-centric message immediately “closes the loop” with respect to the project at hand. When a project is initiated by an e-mail that you send or receive, it squats in your mental landscape—becoming something that’s “on your plate” in the sense that it has been brought to your attention and eventually needs to be addressed. This method closes this open loop as soon as it forms.
Perhaps most impactful, I returned to my MIT habit of working on problems in my head whenever a good time presented itself—be it walking the dog or commuting.
“Let your mind become a lens”: from page 95 of Sertillanges, Antonin-Dalmace. The Intellectual Life: Its Spirits, Conditions, Methods. Trans. Mary Ryan. Cork, Ireland: Mercier Press, 1948. “the development and deepening of the mind”: Ibid., 13. Details about deliberate practice draw heavily on the following seminal survey paper on the topic: K. Anders Ericsson, K.A., R.T. Krampe, and C. Tesch-Römer. “The Role of Deliberate Practice in the Acquisition of Expert Performance.” Psychological Review 100.3 (1993): 363–406.
Details on the neurobiology of expert performance can be found in: Coyle, The Talent Code.
For more on deliberate practice, the following two books provide a good popular overview: • Colvin, Geoffrey. Talent Is Overrated: What Really Separates World-Class Performers from Everybody Else. New York: Portfolio, 2008. • Coyle, Daniel. The Talent Code: Greatness Isn’t Born. It’s Grown. Here’s How. New York: Bantam, 2009.
Larson, Reed, and Mihaly Csikszentmihalyi. “The Experience Sampling Method.” New Directions for Methodology of Social & Behavioral Science. 15 (1983): 41-56.
“Desire turned out to be the norm, not the exception”: from page 3 of Baumeister, Roy F., and John Tierney. Willpower: Rediscovering the Greatest Human Strength. New York: Penguin Press, 2011.
“every inch of [Caro’s] New York office” and “I trained myself” and other details about Robert Caro’s habits: Darman, Jonathan. “The Marathon Man,” Newsweek, February 16, 2009, which I discovered through the following post, “Robert Caro,” on Mason Currey’s Daily Routines blog: http://dailyroutines.typepad.com/daily_routines/2009/02/robert-caro.html.<span id=’fOm4axwvc’/>
“It is only ideas gained from walking that have any worth”: This Nietzsche quote was brought to my attention by the excellent book on walking and philosophy: Gros, Frédérick. A Philosophy of Walking. Trans. John Howe. New York: Verso Books, 2014.
Michael Pollan’s book about building a writing cabin: Pollan, Michael. A Place of My Own: The Education of an Amateur Builder. New York: Random House, 1997.
Clayton Christensen also talks more about his experience with Andy Grove in a July–August 2010 Harvard Business Review article, “How Will You Measure Your Life?” that he later expanded into a book of the same name: http://hbr.org/2010/07/how-will-you-measure-your-life/ar/1.
Much (though not all) of the research cited to support the value of downtime was first brought to my attention through a detailed Scientific American article on the subject: Jabr, Ferris. “Why Your Brain Needs More Downtime.” Scientific American, October 15, 2013. http://www.scientificamerican.com/article/mental-downtime/.
“The scientific literature has emphasized”: from the abstract of Dijksterhuis, Ap, Maarten W. Bos, Loran F. Nordgren, and Rick B. van Baaren, “On Making the Right Choice: The Deliberation-Without-Attention Effect.” Science 311.5763 (2006): 1005–1007. The attention restoration theory study described in the text: Berman, Marc G., John Jonides, and Stephen Kaplan. “The Cognitive Benefits of Interacting with Nature.” Psychological Science 19.12 (2008): 1207–1212.
Kaplan, Rachel, and Stephen Kaplan. The Experience of Nature: A Psychological Perspective. Cambridge: Cambridge University Press, 1989.
Newport, Cal. So Good They Can’t Ignore You: Why Skill Trumps Passion in the Quest for Work You Love. New York: Business Plus, 2012.
After Malcolm Gladwell popularized the idea of deliberate practice in his 2008 bestseller, Outliers: The Story of Success, it became fashionable within psychology circles (a group suspicious, generally speaking, of all things Gladwellian) to poke holes in the deliberate practice hypothesis. For the most part, however, these studies did not invalidate the necessity of deliberate practice, but instead attempted to identify other components also playing a role in expert performance. In a 2013 journal article, titled “Why Expert Performance Is Special and Cannot Be Extrapolated from Studies of Performance in the General Population: A Response to Criticisms,” and published in the journal Intelligence 45 (2014): 81–103, K. Anders Ericsson pushed back on many of these studies. In this article, Ericsson argues, among other things, that the experimental designs of these critical papers are often flawed because they assume you can extrapolate the difference between average and above average in a given field to the difference between expert and non-expert.
This idea has many different forms and names, including the 80/20 rule, Pareto’s principle, and, if you’re feeling particularly pretentious, the principle of factor sparsity.
The studies I cite are looking at the activity of deliberate practice—which substantially (but not completely) overlaps our definition of deep work. For our purposes here, deliberate practice is a good specific stand.in for the general category of cognitively demanding tasks to which deep work belongs.
The Design Justice Network is a home for people who are committed to embodying and practicing the Design Justice Network Principles.
We wield our collective power and experiences to bring forth worlds that are safer, more just, more accessible, and more sustainable. We uplift liberatory experiences, practices, and tools, and critically question the role of design and designers.
Rooted in a sense of abundance, possibility, and joy, we provide connection, care, and community for design justice practitioners.
The internet has enabled new ways of working, but we’re just starting to see them unfold. There are a lot of different ways to make work work. Ours is just one.
No one is an employee, everyone is a contractor, and they get paid hourly. They have an "anti-overtime" rate: past 20 hours per week, peoples’ hourly rate is cut to 50%.
They don’t have meetings or deadlines. People pick what to work on. They use Github, Notion, and Slack to "talk".
Today, working at Gumroad resembles working on an open source project like Rails. Except it’s neither open source, nor unpaid.
There are no deadlines either. We ship incrementally, and launch things whenever the stuff in development is better than what’s currently in production. The occasional exception does exist, such as a tax deadline, but as a rule, I try not to tell anyone what to do or how fast to do it. When someone new joins the company, they do what everyone else does: go into our Notion queue, pick a task, and get to work, asking for clarification when needed.
Instead of setting quarterly goals or using OKRs, we move towards a single north star: maximizing how much money creators earn. It’s simple and measurable, allowing anyone in the company to do the math on how much a feature or bug-fix might be worth.
People work at Gumroad as little as they need to sustain the other parts of their lives they prefer to spend their time and energy on: a creative side-hustle, their family, or anything else.
We also have an “anti-overtime” rate: past twenty hours a week, people can continue to work at an hourly rate of 50 percent. This allows us to have a high hourly rate for the highest leverage work and also allows people to work more per week if they wish.
Whatever your thing might be—and maybe there are many things—the most important component should be aiming to make it as unlike work as possible. This means resisting the very contemporary capitalist urge to commodify it in some way, even when people say to you, “Oh, you’re so good at [this thing]; you should sell it!” But it also means resisting the urge to master it, or display it in a way that transforms it into some mode of performance. You can want to improve, or make something for others, but that’s different from trying to be the best, and beating yourself up (or quitting entirely) because of your inadequacies.
if it’s not three, it’s one or two rather than four or five
When you get a bunch of people in a room under the assumption that consensus is the only way out again, you’re in for a war of attrition
That’s really the answer to new ideas that arrive too late: You’ll just have to wait!
if you actually want to make progress, you have to narrow as you go
Modern-day offices have become interruption factories
the further away you are from the fruit, the lower it looks
progress is achieved through iteration
Creativity, progress, and impact do not yield to brute force.
When someone takes a vacation at Basecamp, it should feel like they don’t work here anymore
Later is where excuses live. Later is where good intentions go to die. Later is a broken back and a bent spirit. Later says “all-nighters are temporary until we’ve got this figured out.” Unlikely. Make the change now.
Most of the time, if you’re uncomfortable with something, it’s because it isn’t right
Our market rates are based on San Francisco numbers despite the fact that we don’t have a single employee there. San Francisco is simply the highest-paying city in the world for our industry. So no matter where you choose to live, we pay the same top-market salaries
Companies spend their employees’ time and attention as if there were an infinite supply of both. As if they cost nothing
One monthly massage at an actual spa
Calm is protecting people’s time and attention.
Calm is about 40 hours of work a week.
Calm is reasonable expectations.
Calm is ample time off.
Calm is smaller.
Calm is a visible horizon.
Calm is meetings as a last resort.
Calm is asynchronous first, real-time second.
Calm is more independence, less interdependence.
Calm is sustainable practices for the long term.
Calm is profitability.
Note: Meetings as a last resort!
We didn’t start out paying everyone these extremely high San Francisco salaries. For a while we were following a similar model but using Chicago rates
Nothing tells the truth like actually experiencing the idea in real life
No growth-at-all-costs. No false busyness. No ego-driven goals. No keeping up with the Joneses Corporation. No hair on fire. And
Someone in charge has to make the final call
spread out across about 30 different cities around the world
When you deal with people who have trouble, you can either choose to take the token that says “It’s no big deal” or the token that says “It’s the end of the world.” Whichever token you pick, they’ll take the other.
Almost everything can wait. And almost everything should.
Comparison is the death of joy.
distractions spread like viruses
the only sustainable method in business is to have them made by individuals.
The hustle may have started as a beacon for those with little to outsmart those with a lot, but now it’s just synonymous with the grind
The expectation of an immediate response is the ember that ignites so many fires at work.
As a general rule, nobody at Basecamp really knows where anyone else is at any given moment. Are they working? Dunno. Are they taking a break? Dunno. Are they at lunch? Dunno. Are they picking up their kid from school? Dunno. Don’t care.
40 hours a week most of the year and just 32 in the summer
Another way to think about our deadlines is that they’re based on budgets, not estimates
your company should be your best product
Stop thinking of talent as something to be plundered and start thinking of it as something to be grown and nurtured
Our target is to pay everyone at the company at the top 10 percent of the market regardless of their role
Micromanagers tend to stay micromanagers.
Workaholics tend to stay workaholics.
Hustlers tend to stay hustlers
Note: Haters gonna hate, hate, hate, hate, hate
“There is nothing so useless as doing efficiently that which should not be done at all.”
The idea that you have to constantly push yourself out of your comfort zone is the kind of supposedly self-evident nonsense you’ll often find in corporate manifestos
Goals are fake
Like they say, all’s fair in love and war. Except this isn’t love, and it isn’t war. It’s business
Set out to do good work. Set out to be fair in your dealings with customers, employees, and reality. Leave a lasting impression with the people you touch and worry less (or not at all!) about changing the world
Friday is the worst day to release anything.
our salaries are benchmarked against other companies’ salaries plus bonus packages
There’s a fountain of happiness and productivity in working with a stable crew
When calm starts early, calm becomes the habit
attempting to be indiscriminately great at everything is a foolish waste of energy
A great work ethic isn’t about working whenever you’re called upon. It’s about doing what you say you’re going to do, putting in a fair day’s work, respecting the work, respecting the customer, respecting coworkers, not wasting time, not creating unnecessary work for other people, and not being a bottleneck
We don’t track your days off, we use the honor system
new approaches or ideas are bad, but their timing may well be
the final decision should be explained clearly to everyone involved
you don’t need to hurt yourself to get healthier
to do. Or, better yet, nothing worth doing. If you’ve only got three hours of work to do on a given day, then stop
The problem with per-seat pricing is that it makes your biggest customers your best customers
Nearly all product work at Basecamp is done by teams of three people
Companies pour gobs of money into buying or renting an office and filling it with desks, chairs, and computers. Then they arrange it all so that nobody can actually get anything done there.
All subject-matter experts at Basecamp now publish office hours
When you stick with planning for the short term, you get to change your mind often. And that’s a huge relief
Fully paid vacations every year
They guard so many things, but all too often they fail to protect what’s both most vulnerable and most precious: their employees’ time and attention.
“That’s fine” is such a wonderfully relaxing way to work most of the time
There are no stock options at Basecamp because we never intend to sell the company
Whatever it takes is an iceberg. Steer clear lest it literally sink your ship
If you can’t fit everything you want to do within 40 hours per week, you need to get better at picking what to do
Where does our money come from? Customers. Call us old-fashioned
we started by setting a target: one hour. The vast majority of the hundreds of customers writing to us every day should get a response within one hour
how many of those hours are really spent on the work itself? And how many are tossed away in meetings, lost to distraction, and withered away by inefficient business practices
People don’t like to have their grievances downplayed or dismissed
The modern workplace is sick. Chaos should not be the natural state at work. Anxiety isn’t a prerequisite for progress. Sitting in meetings all day isn’t required for success. These are all perversions of work —side effects of broken models and follow-the-lemming-off-the-cliff worst practices. Step aside and let the suckers jump.
Working 40 hours a week is plenty
During the summer, we even take Fridays off and still get plenty of good stuff done in just 32 hours
This is how you end up thinking “What did I actually do today?” when the clock turns to five and you supposedly spent eight hours at the office. You know you were there, but the hours had no weight, so they slipped away with nothing to show
six, seven, or eight on a team will inevitably make simple things more complicated than they need to be
The quickest way to disappointment is to set unreasonable expectations.
We didn’t just assume asynchronous communication is better than real-time communication most of the time. We figured it out after overusing chat tools for years
“Doing nothing isn’t an option.”
Oh, yes, it is. And it’s often the best one.
“Nothing” should always be on the table.
We didn’t realize paying for people’s vacations was better than cash bonuses. We started with the latter and realized that bonuses were just taken as an expected part of pay, anyway
We not only pay for people’s vacation time, we pay for the actual vacation, too
Putting everything we build in front of customers beforehand is slow, costly, and results in a mountain of prerelease feedback that has to be sifted through, considered, debated, discussed, and decided upon
Following group chat at work is like being in an all-day meeting with random participants and no agenda. It’s completely exhausting
The trust battery is dead.
If you can’t be bothered to schedule a meeting without software to do the work, just don’t bother at all. It probably wasn’t necessary in the first place.
Off our grid
Note: Could you block someone’s slack and email access?
after that brief period of exploration at the beginning of a project—it’s time to focus in and get narrow. It’s time for tunnel vision
We don’t do grand plans at Basecamp—not for the company, not for the product. There’s no five-year plan. No three-year plan. No one-year plan. Nada
$1,000 per year continuing-education stipend
Time and attention are best spent in large bills, if you will, not spare coins and small change
I disagree and commit all the time
Most people don’t actually have 8 hours a day to work, they have a couple of hours. The rest of the day is stolen from them by meetings, conference calls, and other distractions. So while you may be at the office for 8 hours, it feels more like just a few.
keep salaries equal for equal work and seniority
Change makes things worse all the time.
What’s worse is when management holds up certain people as having a great “work ethic” because they’re always around, always available, always working. That’s a terrible example of a work ethic and a great example of someone who’s overworked.
Sell new customers on the new thing and let old customers keep whatever they already have. This is the way to keep the peace and maintain the calm
We just want someone who can hit the ground running” is the common refrain for companies seeking senior-level job candidates
$100 monthly fitness allowance
“lottery tickets” (aka stock options)
If we tell a team that they have six weeks to build a great calendar feature in Basecamp, they’re much more likely to produce lovely work
you’ll hardly ever find more than three people around a table
When the boss says “My door is always open,” it’s a cop-out, not an invitation. One that puts the onus of speaking up entirely on the employees
30-day-paid sabbaticals every three years
When someone takes your time, it doesn’t cost them anything, but it costs you everything
If you don’t clearly communicate to everyone else why someone was let go, the people who remain at the company will come up with their own story to explain it. Those stories will almost certainly be worse than the real reason
Do people who work here know how to use the company?
Note: Customers/members too!
we chop problems down until they can be carried across the finish line by teams of three
The opposite of conquering the world isn’t failure, it’s participation
Eight people in a room for an hour doesn’t cost one hour, it costs eight hours
Make the first Thursday of the month Library Rules day at the office. We bet your employees will beg for more.
we’ve never committed to a product road map
It’s not worth trading sleep for a few extra hours at the office. Not only will it make you exhausted, it’ll literally make you stupid
The only way to get more done is to have less to do.
Meetings should be a last resort, especially big ones.
We come in peace. We don’t have imperial ambitions. We aren’t trying to dominate an industry or a market. We wish everyone well. To get ours, we don’t need to take theirs
People aren’t working longer and later because there’s more work to do all of a sudden. People are working longer and later because they can’t get work done at work anymore!
It’s sad to think that some people crave a commute because it’s the only time during the day they have to themselves
A fractured hour isn’t really an hour—it’s a mess of minutes
At Basecamp, we’ve designed the organization to be largely manager-free
We launch features that aren’t good enough for everyone (but will be Just Fine for plenty of people)
When we present work, it’s almost always written up first. A complete idea in the form of a carefully composed multipage document. Illustrated, whenever possible. And then it’s posted to Basecamp, which lets everyone involved know there’s a complete idea waiting to be considered.
Considered
We work on projects for six weeks at a time, then we take two weeks off from scheduled work to roam and decompress
You can’t credibly promote the virtues of reasonable hours, plentiful rest, and a healthy lifestyle to employees if you’re doing the opposite as the boss
The problem with four is that you almost always need to add a fifth to manage
We send people on month-long sabbaticals every three years
isn’t fueled by stress, or ASAP, or rushing, or late nights, or all-nighter crunches, or impossible promises, or high turnover, or consistently missed deadlines, or projects that never seem to end
Generally speaking, the notion of having to break out of something to reach the next level doesn’t jibe with us. Oftentimes it’s not breaking out, but diving in, digging deeper, staying in your rabbit hole that brings the biggest gains
The person with the question needed something and they got it. The person with the answer was doing something else and had to stop. That’s rarely a fair trade.
Three-day weekends all summer
“I disagree, but let’s commit”
Being one of many options in a market is a virtue that allows customers to have a real choice
Sleep-deprived people aren’t just short on brains or creativity, they’re short on patience. Short on understanding. Short on tolerance
we don’t have status meetings at Basecamp
What people don’t like is forced change—change they didn’t request on a timeline they didn’t choose
Heartbeats
Note: What could this be for me? Confluence blog posts? Slack posts?
We no longer negotiate salaries or raises at Basecamp. Everyone in the same role at the same level is paid the same. Equal work, equal pay.
0:10 Skip to 0 minutes and 10 seconds
I wrote the Feminist Chatbot Design Process in response to a couple of issues that I saw coming up in the AI and tech industry. It was 2016/2017 and the conversation around AI ethics, AI bias was really only just starting to happen. And in this context, I saw that there are a lot of people making a heap of chatbots at once, which is really exciting. And the underlying technology for chatbots is really cool, and natural language processing is really amazing, and, you know, there’s a lot to be excited about. But, I recognised that it was an industry that wasn’t ready to start thinking about the social impact of the design of these chatbots.
0:50 Skip to 0 minutes and 50 seconds
And rather than, you know, thinking about the ways in which to encourage, you know, a whole industry of designers and developers to go and get, you know, ethics trainings or do PhDs in feminist impact studies - which would all be great, which they should totally do anyway - it was more about how can we design an intervention that people can bring into their day to day work. So at the point where they’re being asked to put together a chatbot, have something ready in two weeks, you know, how can we provide support and an intervention there?
1:20 Skip to 1 minute and 20 seconds
To we get them thinking more critically about their design choices, and thinking more critically about how their design choices could have a negative impact on things like, you know, gender equality, perpetuating gender stereotypes, all that stuff. But do it in a way that it’s not meant to make people feel bad for what they’re doing, but really to try and empower them to think differently, think more critically, and come up with a better, more interesting result for their design. The end!
1:50 Skip to 1 minute and 50 seconds
The process can be used in a number of different contexts, and it’s meant to be something that anyone can pick up at any time. You don’t need to be specially trained in it. You don’t need any special equipment to use it. You don’t need a facilitator, you can facilitate it yourself. So it’s really about, you know, the tool being available for whichever context needs it. And primarily I was thinking about a design and development team sitting in, say, an ad agency or in a big tech company and just thinking ‘okay we’ve got to deliver this thing in four weeks and a product owner wants to see progress.’
2:26 Skip to 2 minutes and 26 seconds
You know, thinking about, OK, this tool needs to be able to work in that context. And then hopefully it can also work in, say, a university environment where you have young people who want to experiment with this technology. Artists could make it, you know, work in to how they work, in using technology to communicate their art. So really, it’s, you don’t need to have any kind of training or qualification to pick it up and just have a go.
2:56 Skip to 2 minutes and 56 seconds
Back in 2017 chatbots were being made in a particular way. There was a lot more manual training, I think, that was going on. They weren’t the services like Amazon Lex and, you know, the Google platform as well. I mean, they existed, but they weren’t as, sort of, widely adopted now as they are in chatbot production. And I think it was also this idea of conversation design as a ‘thing’ was still really emerging. And so the 2017 version of the Chatbot Process has those limitations within it. And since then, I think there is absolutely the growing focus on conversation design, and embedding feminist values in how you design the conversation of a chatbot. There’s also questions around that architecture use.
3:41 Skip to 3 minutes and 41 seconds
If you are going to use a platform like Amazon Lex. You know, how do you understand the impact of that choice of technology? So those are the two really key things that have come out. And I think more concerns around data privacy, and data sharing, as well has being really key.
Summary
: > This month, Spanish activist Stacco Troncoso and his collaborators released the [[DisCO Manifesto]] (disco.coop), which proposes a new model for organizations that account for the care work that supports workers and their communities. In this conversation, he explains how the model works and how it challenges norms, both in familiar workplaces and in techno-utopian visions. Troncoso is a founding member of the [[Guerrilla Media Collective]], which is pioneering the [[DisCO]] concept.
I liked this a lot, quoted by Stacco:
> Large-scale problems do not require large-scale solutions.
> They require small-scale solutions within a large-scale framework.
>
> – [[David Fleming]]
Un network est une carte exploitant la base de donnée de Communecter. Il permet d’afficher tous les points correspondant à un tag (par exemple : #AMAP, #Culture, #Energie, …) sur un périmètre défini.
Tous les networks sont liées par la base de données mutualisée, qui est commune. Par contre chaque carte ne montre que l’information relative à un contexte. Dans le schéma ci-dessous on constate que certaines cartes affichent tout ou partie des données déjà visibles sur d’autres cartes (ex : une carte zéro déchet locale permet de visualiser qu’une partie des données de la carte nationale). Si on ajoute un commerce zéro déchet via communecter.org, la carte nationale ou la carte locale, toutes ces cartes le verront apparaître automatiquement.
Voir la page : [utilisation des cartes](/2 - Utiliser l’outil/Fonctionnalités/cartes.md) pour des tutoriels utilisateurs. Voir le canal de discussion #co_network si vous avez besoin d’un coup de main.
L’adresse d’une carte commence par https://www.communecter.org/network/default/index?src= suivi d’un lien vers un fichier contenant les différents paramètres de la carte (nom, filtres, limites géographiques, etc.). Ce fichier peut être hébergé sur votre site ou sur un site tierce (pour ce tuto nous utiliserons Gist).
Clé fournit par Communecter pour accéder aux données (MANDATORY). Requête transmise à Communecter pour afficher des résultats lors de l’ouverture de la carte.
Type de recherche dans la base de donnée communecter (MANDATORY). Liste des valeurs possibles : ‘organizations’, ‘person’, ‘poi’, ‘projects’, ‘events’.
Un network est une carte exploitant la base de donnée de Communecter. Il permet d’afficher tous les points correspondant à un tag (par exemple : #AMAP, #Culture, #Energie, …) sur un périmètre défini (par exemple : plusieurs régions ou une seule ville).
L’adresse d’une carte commence par https://www.communecter.org/communecter?network= suivi d’un lien vers un fichier JSON contenant les différents paramètres de la carte (nom, filtres, limites géographiques, etc.). Ce JSON peut être hébergé sur votre site ou sur un site tierce (pour ce tuto nous utiliserons Gist).
Clé fournit par Communecter pour accéder aux données (MANDATORY).
Requête transmise à Communecter pour afficher des résultats lors de l’ouverture de la carte.
Type de recherche dans la base de donnée communecter (MANDATORY).
Liste des valeurs possibles : ‘organizations’, ‘person’, ‘poi’, ‘projects’, ‘events’.
Un network est une carte exploitant la base de donnée de Communecter. Il permet d’afficher tous les points correspondant à un tag (par exemple : #AMAP, #Culture, #Energie, …) sur un périmètre défini.
Tous les networks sont liées par la base de données mutualisée, qui est commune. Par contre chaque carte ne montre que l’information relative à un contexte. Dans le schéma ci-dessous on constate que certaines cartes affichent tout ou partie des données déjà visibles sur d’autres cartes (ex : une carte zéro déchet locale permet de visualiser qu’une partie des données de la carte nationale). Si on ajoute un commerce zéro déchet via communecter.org, la carte nationale ou la carte locale, toutes ces cartes le verront apparaître automatiquement.
Voir la page : [utilisation des cartes](/2 - Utiliser l’outil/Fonctionnalités/cartes.md) pour des tutoriels utilisateurs. Voir le canal de discussion #co_network si vous avez besoin d’un coup de main.
L’adresse d’une carte commence par https://www.communecter.org/network/default/index?src= suivi d’un lien vers un fichier contenant les différents paramètres de la carte (nom, filtres, limites géographiques, etc.). Ce fichier peut être hébergé sur votre site ou sur un site tierce (pour ce tuto nous utiliserons Gist).
Clé fournit par Communecter pour accéder aux données (MANDATORY). Requête transmise à Communecter pour afficher des résultats lors de l’ouverture de la carte.
Type de recherche dans la base de donnée communecter (MANDATORY). Liste des valeurs possibles : ‘organizations’, ‘person’, ‘poi’, ‘projects’, ‘events’.
Un network est une carte exploitant la base de donnée de Communecter. Il permet d’afficher tous les points correspondant à un tag (par exemple : #AMAP, #Culture, #Energie, …) sur un périmètre défini (par exemple : plusieurs régions ou une seule ville).
L’adresse d’une carte commence par https://www.communecter.org/communecter?network= suivi d’un lien vers un fichier JSON contenant les différents paramètres de la carte (nom, filtres, limites géographiques, etc.). Ce JSON peut être hébergé sur votre site ou sur un site tierce (pour ce tuto nous utiliserons Gist).
Clé fournit par Communecter pour accéder aux données (MANDATORY).
Requête transmise à Communecter pour afficher des résultats lors de l’ouverture de la carte.
Type de recherche dans la base de donnée communecter (MANDATORY).
Liste des valeurs possibles : ‘organizations’, ‘person’, ‘poi’, ‘projects’, ‘events’.
A model that, taking inspiration from the brain, is composed of layers (at least one of which is hidden) consisting of simple connected units or neurons followed by nonlinearities.
Virality and network effects are conflated by even experienced Founders, and it keeps them from having the right strategies and developing world-class products.
Viral effects and network effects are two completely different things.
Viral effects are about growth of new users. Viral effects are when you get your existing customers to get you more new customers, ideally for free.
Network effects are about adding value and defensibility to your product. A network effect is when every customer of your product adds incremental value to all the other customers of your product so that it becomes difficult for customers to find any alternative product which gives them as much value.
Viral effects can exist without network effects, and network effects can exist without viral effects.
Further, there are very different playbooks and mental models for building virality vs network effects. Not understanding the distinctions will be detrimental to your company’s long term success.
Yet at the same time, we learned how much less important viral effects are to long-term value creation than defensibilies like network effects.
…nd no one cares how I’m sitting. Of course, I still want my colleagues to like me, so I still bend a knee to gender norms. I simply say what needs to be said in [[Slack]], throw in an exclamation point and a nice [[emoji]], and call it a day. It’s much easier to perform your gender with a dancing penguin than by “power posing” or whatever. And best of all, Slack breaks t…
The technological facilitation of gender performance — will this raise the bar for us all, though?
…ave to think about any of that.” Women are often punished for not behaving gently and communally. But on the internet, nobody knows you’re a bitch. “One thing that women need to d…
I am dead sure the author is justifiedly proud of this sentence.
…ways welcome in digital spaces. When the audience is large and unregulated, women can feel shut down, harassed, or ignored, says Susan Herring, an Indiana University professor who researches gender and digital communication. But in situations where a teacher or a boss is reading what people say—like a classroom discussion group or a workplace Slack channel—people are more likely to be civil. Some women and members of margin…
Also — receipts!
…oid speaking for a few minutes. (It’s also much more obvious when you are stifling your anger in person than when you are typing and deleting draft Slack messages. I typically do this in an offline text file to avoid the ominous “Olga is typing.”) But the effect is that by writi…
Oh, Maya is typing. Maya can be typing for eight minutes for a single syllable answer. That’s communication, baby.
…t work are disingenuous anyway. Do you really care how that person’s weekend was? Is someone telling you that the…
…yes? Is this level of human interest really that hard for people?
…eople are unpleasant in person. To me, getting terse edits in Google Docs is preferable to the time an old-fashioned editor sat me down, looked at my draft, looked at me, and said soberly, “Words matter.” I am not suggesting that anyone …
A neural network that is intentionally run multiple times, where parts of each run feed into the next run. Specifically, hidden layers from the previous run provide part of the input to the same hidden layer in the next run. Recurrent neural networks are particularly useful for evaluating sequences, so that the hidden layers can learn from previous runs of the neural network on earlier parts of the sequence.
For example, the following figure shows a recurrent neural network that runs four times. Notice that the values learned in the hidden layers from the first run become part of the input to the same hidden layers in the second run. Similarly, the values learned in the hidden layer on the second run become part of the input to the same hidden layer in the third run. In this way, the recurrent neural network gradually trains and predicts the meaning of the entire sequence rather than just the meaning of individual words.
You don’t have to work miserable 60/80/100-hour weeks to make it work. 10–40 hours a week is plenty. (Location 144)
Learning from mistakes is overrated (Location 163)
What do you really learn from mistakes? You might learn what not to do again, but how valuable is that? You still don’t know what you should do next. (Location 171)
Success gives you real ammunition. When something succeeds, you know what worked—and you can do it again. (Location 172)
already-successful entrepreneurs are far more likely to succeed again (the success rate for their future companies is 34 percent). But entrepreneurs whose companies failed the first time had almost the same follow-on success rate as people starting a company for the first time: just 23 percent. (Location 174)
Failure is not a prerequisite for success. (Location 174)
Plans let the past drive the future. (Location 186)
Sometimes you need to say, “We’re going in a new direction because that’s what makes sense today.” (Location 188)
You have the most information when you’re doing something, not before you’ve done it. (Location 190)
That’s the worst time to make a big decision. (Location 191)
Plans more than a few pages long just wind up as fossils in your file cabinet. (Location 194)
Make decisions right before you do something, not far in advance. (Location 195)
Figure out the next most important thing and do that. (Location 195)
It’s OK to wing it. Just get on the plane and go. You can pick up a nicer shirt, shaving cream, and a toothbrush once you get there. (Location 196)
Working without a plan may seem scary. But blindly following a plan that has no relationship with reality is even scarier. (Location 197)
What’s wrong with finding the right size and staying there? (Location 204)
Not only is this workaholism unnecessary, it’s stupid. (Location 222)
Workaholics wind up creating more problems than they solve. (Location 224)
They try to make up for intellectual laziness with brute force. This results in inelegant solutions. (Location 226)
They even create crises. They don’t look for ways to be more efficient because they actually like working overtime. They enjoy feeling like heroes. They create problems (often unwittingly) just so they can get off on working more. (Location 227)
You stop being able to decide what’s worth extra effort and what’s not. And you wind up just plain [[Tired]]. No one makes sharp decisions when [[Tired]]. (Location 232)
In the end, workaholics don’t actually accomplish more than nonworkaholics. (Location 233)
they’re wasting time fixating on inconsequential details instead of moving on to the next task. (Location 234)
Workaholics aren’t heroes. They don’t save the day, they just use it up. The real hero is already home because she figured out a faster way to get things done. (Location 235)
day. If you’re solving someone else’s problem, you’re constantly stabbing in the dark. When you solve your own problem, the light comes on. (Location 268)
this “solve your own problem” approach lets you fall in love with what you’re making. (Location 287)
Having the idea for eBay has nothing to do with actually creating eBay. What you do is what matters, not what you think or say or plan. (Location 293)
Ideas are cheap and plentiful. The original pitch idea is such a small part of a business that it’s almost negligible. The real question is how well you execute. (Location 299)
If what we make isn’t right for everyone, that’s OK. We’re willing to lose some customers if it means that others love our products intensely. (Location 325)
When you don’t know what you believe, everything becomes an argument. Everything is debatable. But when you stand for something, decisions are obvious. (Location 326)
There’s a world of difference between truly standing for something and having a mission statement that says you stand for something. (Location 340)
We didn’t advertise; we promoted by sharing our experiences online. (Location 395)
Embrace the idea of having less mass. (Location 431)
Mass is increased by … Long-term contracts Excess staff Permanent decisions Meetings Thick process Inventory (physical or mental) Hardware, software, and technology lock-ins Long-term road maps Office politics (Location 433)
Limited resources force you to make do with what you’ve got. (Location 456)
You’re better off with a kick-ass half than a half-assed whole. (Location 477)
If you are looking for a small social media site that will hopefully develop a tiny community over the next year or two, then you are welcome to stay and participate. Try to ignore the bugginess for the time being. The bugs will go away over time as I squash them one by one.
Не похоже, что работает с Fediverse. А ещё дизайн очень больный. Мне не нравится.
To most people, social acceptance is one of the most important driving forces of their lives. As such, social media discussion sites are mainly dominated by people who follow hype and trends. They cannot and do not think independently, and they are afraid of going against the current. If you use your brain and don't follow the hive mind, you will definitely not be liked.
In Deep Q-learning, a neural network that is a stable approximation of the main neural network, where the main neural network implements either a Q-function or a policy. Then, you can train the main network on the Q-values predicted by the target network. Therefore, you prevent the feedback loop that occurs when the main network trains on Q-values predicted by itself. By avoiding this feedback, training stability increases.
I used to say it was a ‘new’ kind, perhaps as a nod to [[stephen wolfram]], but actually the [[agora]] is sort of retro in many key ways. It is inspired by [[everything2]] and [[wiki]].
Chase your enthusiasm down a rabbit hole—even if you’re not sure it’s the best one. You only need to start with something halfway good to later discover something great beyond it.
If you can reliably produce good work via imitation, it means you understand the mechanics of your craft. Once you’ve achieved that, it’s easier to break free from those mechanics in pursuit of origination. Origination is how you achieve greatness.
Transcript
In 2011 an IBM cognitive system won Jeopardy. Now cognitive systems
are tackling business challenges as varied as operations and healthcare.
Let’s see how IBM Watson is helping elevator engineers.
Hello my name is Watson, greetings from the top of Q1 tower.
You might be wondering how I got here,
I did not climb the 1331 stairs in this skyscraper.
Instead I took an elevator operated by Kone.
Everyday Kone helps to transport approximately one billion elevator and
escalator passengers throughout the world.
And I am working with them to help ensure smoothness with every ride.
Elevators are being equipped with IOT sensors that connect to the IBM
cloud which I can analyze for wear and tear, bumpy rides and
the smallest misalignments.
I can immediately alert maintenance crews of any issues via their smartphones,
provide probable causes and solutions and help them run tests remotely.
With this information along with data from structured and
unstructured sources, I can prioritize jobs and
help technicians continue providing a great passenger experience.
With my help, engineers are fixing potential problems before they happen.
Working together that can help Kone service technicians speed up repairs and
make rides smoother.
This lowers your chances of spending too much time in an elevator with a co-
worker, I have heard that can be awkward.
From the big city to a rural doctor’s office, Watson can help.
So you miss the big city?
I don’t miss much, definitely not the traffic.
Excuse me, doctor, the genomic data came in.
Thank you.
You can do that kind of analysis?
Yeah, Watson.
I can quickly analyze millions of clinical and scientific reports to help
you tailor treatment options for the patient’s genomic profile.
You can do that, even way out here?
Yes, even way out here.
Watson and AI can be part of a wide range of business ventures,
wherever you are.
Which channels for what purpose, responsiveness, which tools, how to deal with urgences Focus time slots Team days Team agreements on all these aspects Digital morning coffee / stand up
Group 5: Design telcos beforehand
group 5: meeting rules. use of chat, break-out rooms, whiteboards, agenda: time allocated by speaker and/or subject. meeting room according to the number of people present + necessary technology for those virtually.
All this suggests a peculiar conclusion: as a medium, books are surprisingly bad at conveying knowledge, and readers mostly don’t realize it.
In the Cosmos episode, “The Persistence of Memory,” Carl Sagan exalts: What an astonishing thing a book is. It’s a flat object made from a tree with flexible parts on which are imprinted lots of funny dark squiggles. But one glance at it and you’re inside the mind of another person, maybe somebody dead for thousands of years. Across the millennia, an author is speaking clearly and silently inside your head, directly to you. Writing is perhaps the greatest of human inventions, binding together people who never knew each other, citizens of distant epochs. Books break the shackles of time. A book is proof that humans are capable of working magic.
So if you hope to help others understand things, you had better draw on some great ideas about how people learn.
The lectures-as-warmup model is a post-hoc rationalization, but it does gesture at a deep theory about cognition: to understand something, you must actively engage with it.
So let’s reframe the question. Rather than “how might we make books actually work reliably,” we can ask: How might we design mediums which do the job of a non-fiction book—but which actually work reliably?
To begin, it’s important to see that mediums can be designed, not just inherited. What’s more: it is possible to design new mediums which embody specific ideas.
It’s not just that it’s possible to create a medium informed by certain ideas in cognitive science. Rather, it’s possible to weave a medium made out of those ideas, in which a reader’s thoughts and actions are inexorably—perhaps even invisibly—shaped by those ideas.
If we pile together enough of these questions we’re left with: how might we design mediums in which “reading” is the same as “understanding”?
