2016 LessWrong Diaspora Survey Analysis: Part Two (LessWrong Use, Successorship, Diaspora)
2016 LessWrong Diaspora Survey Analysis
Overview
- Results and Dataset
- Meta
- Demographics
- LessWrong Usage and Experience
- LessWrong Criticism and Successorship
- Diaspora Community Analysis (You are here)
- Mental Health Section
- Basilisk Section/Analysis
- Blogs and Media analysis
- Politics
- Calibration Question And Probability Question Analysis
- Charity And Effective Altruism Analysis
Introduction
Before it was the LessWrong survey, the 2016 survey was a small project I was working on as market research for a website I'm creating called FortForecast. As I was discussing the idea with others, particularly Eliot he made the suggestion that since he's doing LW 2.0 and I'm doing a site that targets the LessWrong demographic, why don't I go ahead and do the LessWrong Survey? Because of that, this years survey had a lot of questions oriented around what you would want to see in a successor to LessWrong and what you think is wrong with the site.
LessWrong Usage and Experience
How Did You Find LessWrong?
Been here since it was started in the Overcoming Bias days: 171 8.3%
Referred by a link: 275 13.4%
HPMOR: 542 26.4%
Overcoming Bias: 80 3.9%
Referred by a friend: 265 12.9%
Referred by a search engine: 131 6.4%
Referred by other fiction: 14 0.7%
Slate Star Codex: 241 11.7%
Reddit: 55 2.7%
Common Sense Atheism: 19 0.9%
Hacker News: 47 2.3%
Gwern: 22 1.1%
Other: 191 9.308%
How do you use Less Wrong?
I lurk, but never registered an account: 1120 54.4%
I've registered an account, but never posted: 270 13.1%
I've posted a comment, but never a top-level post: 417 20.3%
I've posted in Discussion, but not Main: 179 8.7%
I've posted in Main: 72 3.5%
[54.4% lurkers.]
How often do you comment on LessWrong?
I have commented more than once a week for the past year.: 24 1.2%
I have commented more than once a month for the past year but less than once a week.: 63 3.1%
I have commented but less than once a month for the past year.: 225 11.1%
I have not commented this year.: 1718 84.6%
[You could probably snarkily title this one "LW usage in one statistic". It's a pretty damning portrait of the sites vitality. A whopping 84.6% of people have not commented this year a single time.]
How Long Since You Last Posted On LessWrong?
I wrote one today.: 12 0.637%
Within the last three days.: 13 0.69%
Within the last week.: 22 1.168%
Within the last month.: 58 3.079%
Within the last three months.: 75 3.981%
Within the last six months.: 68 3.609%
Within the last year.: 84 4.459%
Within the last five years.: 295 15.658%
Longer than five years.: 15 0.796%
I've never posted on LW.: 1242 65.924%
[Supermajority of people have never commented on LW, 5.574% have within the last month.]
About how much of the Sequences have you read?
Never knew they existed until this moment: 215 10.3%
Knew they existed, but never looked at them: 101 4.8%
Some, but less than 25% : 442 21.2%
About 25%: 260 12.5%
About 50%: 283 13.6%
About 75%: 298 14.3%
All or almost all: 487 23.3%
[10.3% of people taking the survey have never heard of the sequences. 36.3% have not read a quarter of them.]
Do you attend Less Wrong meetups?
Yes, regularly: 157 7.5%
Yes, once or a few times: 406 19.5%
No: 1518 72.9%
[However the in-person community seems to be non-dead.]
Is physical interaction with the Less Wrong community otherwise a part of your everyday life, for example do you live with other Less Wrongers, or you are close friends and frequently go out with them?
Yes, all the time: 158 7.6%
Yes, sometimes: 258 12.5%
No: 1652 79.9%
About the same number say they hang out with LWers 'all the time' as say they go to meetups. I wonder if people just double counted themselves here. Or they may go to meetups and have other interactions with LWers outside of that. Or it could be a coincidence and these are different demographics. Let's find out.
P(Community part of daily life | Meetups) = 40%
Significant overlap, but definitely not exclusive overlap. I'll go ahead and chalk this one up up to coincidence.
Have you ever been in a romantic relationship with someone you met through the Less Wrong community?
Yes: 129 6.2%
I didn't meet them through the community but they're part of the community now: 102 4.9%
No: 1851 88.9%
LessWrong Usage Differences Between 2016 and 2014 Surveys
How do you use Less Wrong?
I lurk, but never registered an account: +19.300% 1125 54.400%
I've registered an account, but never posted: -1.600% 271 13.100%
I've posted a comment, but never a top-level post: -7.600% 419 20.300%
I've posted in Discussion, but not Main: -5.100% 179 8.700%
I've posted in Main: -3.300% 73 3.500%
About how much of the sequences have you read?
Never knew they existed until this moment: +3.300% 217 10.400%
Knew they existed, but never looked at them: +2.100% 103 4.900%
Some, but less than 25%: +3.100% 442 21.100%
About 25%: +0.400% 260 12.400%
About 50%: -0.400% 284 13.500%
About 75%: -1.800% 299 14.300%
All or almost all: -5.000% 491 23.400%
Do you attend Less Wrong meetups?
Yes, regularly: -2.500% 160 7.700%
Yes, once or a few times: -2.100% 407 19.500%
No: +7.100% 1524 72.900%
Is physical interaction with the Less Wrong community otherwise a part of your everyday life, for example do you live with other Less Wrongers, or you are close friends and frequently go out with them?
Yes, all the time: +0.200% 161 7.700%
Yes, sometimes: -0.300% 258 12.400%
No: +2.400% 1659 79.800%
Have you ever been in a romantic relationship with someone you met through the Less Wrong community?
Yes: +0.800% 132 6.300%
I didn't meet them through the community but they're part of the community now: -0.400% 102 4.900%
No: +1.600% 1858 88.800%
Write Ins
In a bit of a silly oversight I forgot to ask survey participants what was good about the community, so the following is going to be a pretty one sided picture. Below are the complete write ins respondents submitted
Issues With LessWrong At It's Peak
Philosophical Issues With LessWrong At It's Peak[Part One]
Philosophical Issues With LessWrong At It's Peak[Part Two]
Community Issues With LessWrong At It's Peak[Part One]
Community Issues With LessWrong At It's Peak[Part Two]
Issues With LessWrong Now
Philosophical Issues With LessWrong Now[Part One]
Philosophical Issues With LessWrong Now[Part Two]
Community Issues With LessWrong Now[Part One]
Community Issues With LessWrong Now[Part Two]
Peak Philosophy Issue Tallies
| Label | Code | Tally |
|---|---|---|
| Arrogance | A | 16 |
| Bad Aesthetics | BA | 3 |
| Bad Norms | BN | 3 |
| Bad Politics | BP | 5 |
| Bad Tech Platform | BTP | 1 |
| Cultish | C | 5 |
| Cargo Cult | CC | 3 |
| Doesn't Accept Criticism | DAC | 3 |
| Don't Know Where to Start | DKWS | 5 |
| Damaged Me Mentally | DMM | 1 |
| Esoteric | E | 3 |
| Eliezer Yudkowsky | EY | 6 |
| Improperly Indexed | II | 7 |
| Impossible Mission | IM | 4 |
| Insufficient Social Support | ISS | 1 |
| Jargon | ||
| Literal Cult | LC | 1 |
| Lack of Rigor | LR | 14 |
| Misfocused | M | 13 |
| Mixed Bag | MB | 3 |
| Nothing | N | 13 |
| Not Enough Jargon | NEJ | 1 |
| Not Enough Roko's Basilisk | NERB | 1 |
| Not Enough Theory | NET | 1 |
| No Intuition | NI | 6 |
| Not Progressive Enough | NPE | 7 |
| Narrow Scholarship | NS | 20 |
| Other | O | 3 |
| Personality Cult | PC | 10 |
| None of the Above | ||
| Quantum Mechanics Sequence | QMS | 2 |
| Reinvention | R | 10 |
| Rejects Expertise | RE | 5 |
| Spoiled | S | 7 |
| Small Competent Authorship | SCA | 6 |
| Suggestion For Improvement | SFI | 1 |
| Socially Incompetent | SI | 9 |
| Stupid Philosophy | SP | 4 |
| Too Contrarian | TC | 2 |
| Typical Mind | TM | 1 |
| Too Much Roko's Basilisk | TMRB | 1 |
| Too Much Theory | TMT | 14 |
| Too Progressive | TP | 2 |
| Too Serious | TS | 2 |
| Unwelcoming | U | 8 |
Well, those are certainly some results. Top answers are:
Narrow Scholarship: 20
Arrogance: 16
Too Much Theory: 14
Lack of Rigor: 14
Misfocused: 13
Nothing: 13
Reinvention (reinvents the wheel too much): 10
Personality Cult: 10
So condensing a bit: Pay more attention to mainstream scholarship and ideas, try to do better about intellectual rigor, be more practical and focus on results, be more humble. (Labeled Dataset)
Peak Community Issue Tallies
| Label | Code | Tally |
|---|---|---|
| Arrogance | A | 7 |
| Assumes Reader Is Male | ARIM | 1 |
| Bad Aesthetics | BA | 1 |
| Bad At PR | BAP | 5 |
| Bad Norms | BN | 5 |
| Bad Politics | BP | 2 |
| Cultish | C | 9 |
| Cliqueish Tendencies | CT | 1 |
| Diaspora | D | 1 |
| Defensive Attitude | DA | 1 |
| Doesn't Accept Criticism | DAC | 3 |
| Dunning Kruger | DK | 1 |
| Elitism | E | 3 |
| Eliezer Yudkowsky | EY | 2 |
| Groupthink | G | 11 |
| Insufficiently Indexed | II | 9 |
| Impossible Mission | IM | 1 |
| Imposter Syndrome | IS | 1 |
| Jargon | J | 2 |
| Lack of Rigor | LR | 1 |
| Mixed Bag | MB | 1 |
| Nothing | N | 5 |
| ??? | NA | 1 |
| Not Big Enough | NBE | 3 |
| Not Enough of A Cult | NEAC | 1 |
| Not Enough Content | NEC | 7 |
| Not Enough Community Infrastructure | NECI | 10 |
| Not Enough Meetups | NEM | 5 |
| No Goals | NG | 2 |
| Not Nerdy Enough | NNE | 3 |
| None Of the Above | NOA | 1 |
| Not Progressive Enough | NPE | 3 |
| Not Rational | NR | 3 |
| NRx (Neoreaction) | NRx | 1 |
| Narrow Scholarship | NS | 4 |
| Not Stringent Enough | NSE | 3 |
| Parochialism | P | 1 |
| Pickup Artistry | PA | 2 |
| Personality Cult | PC | 7 |
| Reinvention | R | 1 |
| Recurring Arguments | RA | 3 |
| Rejects Expertise | RE | 2 |
| Sequences | S | 2 |
| Small Competent Authorship | SCA | 5 |
| Suggestion For Improvement | SFI | 1 |
| Spoiled Issue | SI | 9 |
| Socially INCOMpetent | SINCOM | 2 |
| Too Boring | TB | 1 |
| Too Contrarian | TC | 10 |
| Too COMbative | TCOM | 4 |
| Too Cis/Straight/Male | TCSM | 5 |
| Too Intolerant of Cranks | TIC | 1 |
| Too Intolerant of Politics | TIP | 2 |
| Too Long Winded | TLW | 2 |
| Too Many Idiots | TMI | 3 |
| Too Much Math | TMM | 1 |
| Too Much Theory | TMT | 12 |
| Too Nerdy | TN | 6 |
| Too Rigorous | TR | 1 |
| Too Serious | TS | 1 |
| Too Tolerant of Cranks | TTC | 1 |
| Too Tolerant of Politics | TTP | 3 |
| Too Tolerant of POSers | TTPOS | 2 |
| Too Tolerant of PROGressivism | TTPROG | 2 |
| Too Weird | TW | 2 |
| Unwelcoming | U | 12 |
| UTILitarianism | UTIL | 1 |
Top Answers:
Unwelcoming: 12
Too Much Theory: 12
Groupthink: 11
Not Enough Community Infrastructure: 10
Too Contrarian: 10
Insufficiently Indexed: 9
Cultish: 9
Again condensing a bit: Work on being less intimidating/aggressive/etc to newcomers, spend less time on navel gazing and more time on actually doing things and collecting data, work on getting the structures in place that will onboard people into the community, stop being so nitpicky and argumentative, spend more time on getting content indexed in a form where people can actually find it, be more accepting of outside viewpoints and remember that you're probably more likely to be wrong than you think. (Labeled Dataset)
One last note before we finish up, these tallies are a very rough executive summary. The tagging process basically involves trying to fit points into clusters and is prone to inaccuracy through laziness, adding another category being undesirable, square-peg into round-hole fitting, and my personal political biases. So take these with a grain of salt, if you really want to know what people wrote in my advice would be to read through the write in sets I have above in HTML format. If you want to evaluate for yourself how well I tagged things you can see the labeled datasets above.
I won't bother tallying the "issues now" sections, all you really need to know is that it's basically the same as the first sections except with lots more "It's dead." comments and from eyeballing it a higher proportion of people arguing that LessWrong has been taken over by the left/social justice and complaints about effective altruism. (I infer that the complaints about being taken over by the left are mostly referring to effective altruism.)
Traits Respondents Would Like To See In A Successor Community
Philosophically
Attention Paid To Outside Sources
More: 1042 70.933%
Same: 414 28.182%
Less: 13 0.885%
Self Improvement Focus
More: 754 50.706%
Same: 598 40.215%
Less: 135 9.079%
AI Focus
More: 184 12.611%
Same: 821 56.271%
Less: 454 31.117%
Political
More: 330 22.837%
Same: 770 53.287%
Less: 345 23.875%
Academic/Formal
More: 455 31.885%
Same: 803 56.272%
Less: 169 11.843%
In summary, people want a site that will engage with outside ideas, acknowledge where it borrows from, focus on practical self improvement, less on AI and AI risk, and tighten its academic rigor. They could go either way on politics but the epistemic direction is clear.
Community
Intense Environment
More: 254 19.644%
Same: 830 64.192%
Less: 209 16.164%
Focused On 'Real World' Action
More: 739 53.824%
Same: 563 41.005%
Less: 71 5.171%
Experts
More: 749 55.605%
Same: 575 42.687%
Less: 23 1.707%
Data Driven/Testing Of Ideas
More: 1107 78.344%
Same: 291 20.594%
Less: 15 1.062%
Social
More: 583 43.507%
Same: 682 50.896%
Less: 75 5.597%
This largely backs up what I said about the previous results. People want a more practical, more active, more social and more empirical LessWrong with outside expertise and ideas brought into the fold. They could go either way on it being more intense but the epistemic trend is still clear.
Write Ins
Diaspora Communities
So where did the party go? We got twice as many respondents this year as last when we opened up the survey to the diaspora, which means that the LW community is alive and kicking it's just not on LessWrong.
LessWrong
Yes: 353 11.498%
No: 1597 52.02%
LessWrong Meetups
Yes: 215 7.003%
No: 1735 56.515%
LessWrong Facebook Group
Yes: 171 5.57%
No: 1779 57.948%
LessWrong Slack
Yes: 55 1.792%
No: 1895 61.726%
SlateStarCodex
Yes: 832 27.101%
No: 1118 36.417%
[SlateStarCodex by far has the highest proportion of active LessWrong users, over twice that of LessWrong itself, and more than LessWrong and Tumblr combined.]
Rationalist Tumblr
Yes: 350 11.401%
No: 1600 52.117%
[I'm actually surprised that Tumblr doesn't just beat LessWrong itself outright, They're only a tenth of a percentage point behind though, and if current trends continue I suspect that by 2017 Tumblr will have a large lead over the main LW site.]
Rationalist Facebook
Yes: 150 4.886%
No: 1800 58.632%
[Eliezer Yudkowsky currently resides here.]
Rationalist Twitter
Yes: 59 1.922%
No: 1891 61.596%
Effective Altruism Hub
Yes: 98 3.192%
No: 1852 60.326%
FortForecast
Yes: 4 0.13%
No: 1946 63.388%
[I included this as a 'troll' option to catch people who just check every box. Relatively few people seem to have done that, but having the option here lets me know one way or the other.]
Good Judgement(TM) Open
Yes: 29 0.945%
No: 1921 62.573%
PredictionBook
Yes: 59 1.922%
No: 1891 61.596%
Omnilibrium
Yes: 8 0.261%
No: 1942 63.257%
Hacker News
Yes: 252 8.208%
No: 1698 55.309%
#lesswrong on freenode
Yes: 76 2.476%
No: 1874 61.042%
#slatestarcodex on freenode
Yes: 36 1.173%
No: 1914 62.345%
#hplusroadmap on freenode
Yes: 4 0.13%
No: 1946 63.388%
#chapelperilous on freenode
Yes: 10 0.326%
No: 1940 63.192%
[Since people keep asking me, this is a postrational channel.]
/r/rational
Yes: 274 8.925%
No: 1676 54.593%
/r/HPMOR
Yes: 230 7.492%
No: 1720 56.026%
[Given that the story is long over, this is pretty impressive. I'd have expected it to be dead by now.]
/r/SlateStarCodex
Yes: 244 7.948%
No: 1706 55.57%
One or more private 'rationalist' groups
Yes: 192 6.254%
No: 1758 57.264%
[I almost wish I hadn't included this option, it'd have been fascinating to learn more about these through write ins.]
Of all the parties who seem like plausible candidates at the moment, Scott Alexander seems most capable to undiaspora the community. In practice he's very busy, so he would need a dedicated team of relatively autonomous people to help him. Scott could court guest posts and start to scale up under the SSC brand, and I think he would fairly easily end up with the lions share of the free floating LWers that way.
Before I call a hearse for LessWrong, there is a glimmer of hope left:
Would you consider rejoining LessWrong?
I never left: 668 40.6%
Yes: 557 33.8%
Yes, but only under certain conditions: 205 12.5%
No: 216 13.1%
A significant fraction of people say they'd be interested in an improved version of the site. And of course there were write ins for conditions to rejoin, what did people say they'd need to rejoin the site?
Rejoin Condition Write Ins [Part One]
Rejoin Condition Write Ins [Part Two]
Rejoin Condition Write Ins [Part Three]
Rejoin Condition Write Ins [Part Four]
Rejoin Condition Write Ins [Part Five]
Feel free to read these yourselves (they're not long), but I'll go ahead and summarize: It's all about the content. Content, content, content. No amount of usability improvements, A/B testing or clever trickery will let you get around content. People are overwhelmingly clear about this; they need a reason to come to the site and right now they don't feel like they have one. That means priority number one for somebody trying to revitalize LessWrong is how you deal with this.
Let's recap.
Future Improvement Wishlist Based On Survey Results
Philosophical
- Pay more attention to mainstream scholarship and ideas.
- Improved intellectual rigor.
- Acknowledge sources borrowed from.
- Be more practical and focus on results.
- Be more humble.
Community
- Less intimidating/aggressive/etc to newcomers,
- Structures that will onboard people into the community.
- Stop being so nitpicky and argumentative.
- Spend more time on getting content indexed in a form where people can actually find it.
- More accepting of outside viewpoints.
While that list seems reasonable, it's quite hard to put into practice. Rigor, as the name implies requires high-effort from participants. Frankly, it's not fun. And getting people to do un-fun things without paying them is difficult. If LessWrong is serious about it's goal of 'advancing the art of human rationality' then it needs to figure out a way to do real investigation into the subject. Not just have people 'discuss', as though the potential for Rationality is within all of us just waiting to be brought out by the right conversation.
I personally haven't been a LW regular in a long time. Assuming the points about pedanticism, snipping, "well actually"-ism and the like are true then they need to stop for the site to move forward. Personally, I'm a huge fan of Scott Alexander's comment policy: All comments must be at least two of true, kind, or necessary.
-
True and kind - Probably won't drown out the discussion signal, will help significantly decrease the hostility of the atmosphere.
-
True and necessary - Sometimes what you have to say isn't nice, but it needs to be said. This is the common core of free speech arguments for saying mean things and they're not wrong. However, something being true isn't necessarily enough to make it something you should say. In fact, in some situations saying mean things to people entirely unrelated to their arguments is known as the ad hominem fallacy.
-
Kind and necessary - The infamous 'hugbox' is essentially a place where people go to hear things which are kind but not necessarily true. I don't think anybody wants a hugbox, but occasionally it can be important to say things that might not be true but are needed for the sake of tact, reconciliation, or to prevent greater harm.
If people took that seriously and really gave it some thought before they used their keyboard, I think the on-site LessWrong community would be a significant part of the way to not driving people off as soon as they arrive.
More importantly, in places like the LessWrong Slack I see this sort of happy go lucky attitude about site improvement. "Oh that sounds nice, we should do that." without the accompanying mountain of work to actually make 'that' happen. I'm not sure people really understand the dynamics of what it means to 'revive' a website in severe decay. When you decide to 'revive' a dying site, what you're really doing once you're past a certain point is refounding the site. So the question you should be asking yourself isn't "Can I fix the site up a bit so it isn't quite so stale?". It's "Could I have founded this site?" and if the answer is no you should seriously question whether to make the time investment.
Whether or not LessWrong lives to see another day basically depends on the level of ground game its last users and administrators can muster up. And if it's not enough, it won't.
Virtus junxit mors non separabit!
Learn (and Maybe Get a Credential in) Data Science
Coursera is now offering a sequence of online courses on data science. They include:
1. The Data Scientist's Toolbox
Upon completion of this course you will be able to identify and classify data science problems. You will also have created your Github account, created your first repository, and pushed your first markdown file to your account.
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.
Upon completion of this course you will be able to obtain data from a variety of sources. You will know the principles of tidy data and data sharing. Finally, you will understand and be able to apply the basic tools for data cleaning and manipulation.
After successfully completing this course you will be able to make visual representations of data using the base, lattice, and ggplot2 plotting systems in R, apply basic principles of data graphics to create rich analytic graphics from different types of datasets, construct exploratory summaries of data in support of a specific question, and create visualizations of multidimensional data using exploratory multivariate statistical techniques.
In this course you will learn to write a document using R markdown, integrate live R code into a literate statistical program, compile R markdown documents using knitr and related tools, and organize a data analysis so that it is reproducible and accessible to others.
In this class students will learn the fundamentals of statistical inference. Students will receive a broad overview of the goals, assumptions and modes of performing statistical inference. Students will be able to perform inferential tasks in highly targeted settings and will be able to use the skills developed as a roadmap for more complex inferential challenges.
In this course students will learn how to fit regression models, how to interpret coefficients, how to investigate residuals and variability. Students will further learn special cases of regression models including use of dummy variables and multivariable adjustment. Extensions to generalized linear models, especially considering Poisson and logistic regression will be reviewed.
Upon completion of this course you will understand the components of a machine learning algorithm. You will also know how to apply multiple basic machine learning tools. You will also learn to apply these tools to build and evaluate predictors on real data.
Students will learn how communicate using statistics and statistical products. Emphasis will be paid to communicating uncertainty in statistical results. Students will learn how to create simple Shiny web applications and R packages for their data products.
The State of the Art of Scientific Research on Polyamoury
The idea of polyamoury is one that interests me. However, while such books as The Ethical Slut have done a good job of providing me with tools to understand and possibly handle the challenges and rewards involved, I found them unsatisfying in that they were largely based on anecdotal evidence, with a very strong selection bias. Before making the jump of attempting to live that way, one would need to know precisely the state of the art of scientific, rigourous, credible research on the topic; it is a tedious job to seek out and compile everything, but I believe it is a job worth doing.
I'll be initiating an ongoing process of data compilation, and will publish my findings on this thread as I discover and summarize them. Any help is greatly appreciated, as this promises to be long and tedious. I might especially need help extracting meaningful information from the masses of data; I am not a good statistician yet, far from it.
To Be Expanded...
Internet Research (with tangent on intelligence analysis and collapse)
Want to save time? Skip down to "I'm looking to compile a thread on Internet Research"!
Opinionated Preamble:
There is a lot of high level thinking on Less Wrong, which is great. It's done wonders to structure and optimize my own decisions. I think the political and futurology-related issues that Less Wrong cover can sometimes get out of sync with the reality and injustices of events in the immediate world. There are comprehensive treatments of how medical science is failing, or how academia cannot give unbiased results, and this is the milieu of programmers and philosophers in the middle-to-upper-class of the planet. I at least believe that this circle of awareness can be expanded, even if it's treading into mind-killing territory. If anything I want to give people a near-mode sense of the stakes aside from x-risk: all in all the x-risk scenarios I've seen Less Wrong fear the most, kill humanity somewhat instantly. A slower descent into violence and poverty is to me much more horrifying, because I might have to live in it and I don't know how. In a matter of fact, I have no idea of how to predict it.
This is one reason why I'm drawn to the Intelligence Operations performed by the military and crime units, among other things. Intelligence product delivery is about raw and immediate *fact*, and there is a lot of it. The problems featured in IntelOps are one of the few things rationality is good for - highly uncertain scenarios with one-off executions and messy or noisy feedback. Facts get lost in translation as messages are passed through, and of course the feeding and receiving fake facts are all a part of the job - but nevertheless, knowing *everything* *everywhere* is in the job description, and some form of rationality became a necessity.
It gets ugly. The demand for these kinds of skills often lie in industries that are highly competitive, violent, and illegal. I believe that once a close look is taken on how force and power is applied in practice then there isn't any pretending anymore that human evils are an accident.
Open Source Intelligence, or "OSINT", is the mining of data and facts from public information databases, news articles, codebases, journals. Although the amount of classified data dwarfs the unclassified, the size and scope of the unclassified is responsible for a majority of intelligence reports - and thus is involved in the great majority of executive decisions made by government entities. It's worth giving some thought as to how much that we know, that they do too. As illustrated in this expose, the processing of OSINT is a great big chunk of what modern intelligence is about aside from many other things. I think understanding how rationality as developed on Less Wrong can contribute to better IntelOps, and how IntelOps can feed the rationality community, would be awesome, but that's a post for another time.
--
The Show
Through my investigations into IntelOps I've noticed the emphasis on search. Good search.
I'm looking to compile a thread on Internet Research. I'm wondering if there is any wisdom on Less Wrong that can be taken advantage of here on how to become more effective searchers. Here are some questions that could be answered specifically, but they are just guidelines - feel free to voice associated thoughts, we're exploring here.
- Before actually going out and searching, what would be the most effective way of drafting and optimizing a collection plan? Are there any formal optimization models that inform our distribution of time and attention? Exploration vs exploitation comes to mind, but it would be worth formulating something specific. I heard that the multi-armed bandit problem is solved?
- Do you have any links or resources regarding more effective search?
- Do you have any experiences regarding internet research that you can share? Any patterns that you've noticed that have made you more effective at searching?
- What are examples of closed-source information that are low-hanging fruit in terms of access (e.g. academic journals)? What are possible strategies for acquiring closed source data (e.g. enrolling in small courses at universities, e-mailing researchers, cohesion via the law/Freedom of Information Act, social engineering etc)?
- I would like to hear from SEOs and software developers on what their interpretation of semantic web technologies and how they are going to affect end-users. I am somewhat unfamiliar with the semantic web, but from my understanding information that could not be indexed is now indexed; and new ontologies will emerge as this information is mined. What should an end-user expect and what opportunities will there be that didn't exist in the current generation of search?
That should be enough to get started. Below are some links that I have found useful with respect to Internet Research.
--
Meta-Search Engines or Assisted Search:
- Carrot - http://search.carrot2.org/stable/search (concept clustering search engine)
Summarizers:
- TextTeaser - http://www.textteaser.com/ - SOURCE: https://github.com/MojoJolo/textteaser
- Copernic (Commercial Summarizing Feed Program) - http://www.copernic.com/en/products/summarizer/
Bots/Collectors/Automatic Filters:
- Google Alerts - http://www.google.ca/alerts
- Change Detection - http://www.changedetection.com/
Compilations and Directories:
- Directories and Search Engine Repository - http://rr.reuser.biz/index.html (probably the last one you'll ever need.)
- How to Perform Industry Research - http://businesslibrary.uflib.ufl.edu/industryresearch
Guides:
- Google Guide - http://www.googleguide.com/ (with practice and tutorials)
- From UC Berkeley - http://www.lib.berkeley.edu/TeachingLib/Guides/Internet/FindInfo.html
- "How to Solve Impossible Problems" - http://www.johntedesco.net/blog/2012/06/21/how-to-solve-impossible-problems-daniel-russells-awesome-google-search-techniques/
- The NSA Guide to "Untangling the Web"; Internet Research - http://www.nsa.gov/public_info/_files/Untangling_the_Web.pdf [C. 2007]
- Fravia's Learnings on searching (value in essays) - http://search.lores.eu/indexo.htm [C. 1990s - 2009]
- "Power Searching With Google" Course - http://www.powersearchingwithgoogle.com/
Practice:
- SearchReSearch - http://searchresearch1.blogspot.ca/
- A Google A Day - http://agoogleaday.com/
I don't really care how you use this information, but I hope I've jogged some thinking of why it could be important.
[POLL RESULTS] LessWrong Members and their Local Communities
The results for these have been stable for a while now; I'm posting them a bit late. 95 people took the survey after I modified it to add two questions. For the public version, I removed the pre-change data (10 data points).
One text response included identifying information, which I removed in the public version of the data. If you participated and there is any information you provided that you would like removed from the public version, PLEASE tell me as soon as possible and I will remove it.
P.S. To the person who predicted an 80-90% significant difference between different parts of California: I predict with at least 90% confidence that there will be no significant difference, because of the wide spread of locations and smallish sample size of this survey.
(The original post about the survey.)
EDIT: After some comments that it was unethical for me to post the data (in particular the text), I removed public access from the link provided earlier. Given my precommitment to post the data, I assumed it was clear enough to respondents that it would be public. I'm not convinced that this has hurt anyone, but given that others seem to disagree, it seemed prudent to remove it. Please feel free to continue this discussion; I'm interested in your thoughts.
[LINK] "We have a new form of knowing."
Interesting corollary to Tyler Cowen's TED talk:
Models this complex -- whether of cellular biology, the weather, the economy, even highway traffic -- often fail us, because the world is more complex than our models can capture. But sometimes they can predict accurately how the system will behave. At their most complex these are sciences of emergence and complexity, studying properties of systems that cannot be seen by looking only at the parts, and cannot be well predicted except by looking at what happens.
[...]
With the new database-based science, there is often no moment when the complex becomes simple enough for us to understand it. The model does not reduce to an equation that lets us then throw away the model. You have to run the simulation to see what emerges. For example, a computer model of the movement of people within a confined space who are fleeing from a threat--they are in a panic--shows that putting a column about one meter in front of an exit door, slightly to either side, actually increases the flow of people out the door. Why? There may be a theory or it may simply be an emergent property. We can climb the ladder of complexity from party games to humans with the single intent of getting outside of a burning building, to phenomena with many more people with much more diverse and changing motivations, such as markets. We can model these and perhaps know how they work without understanding them. They are so complex that only our artificial brains can manage the amount of data and the number of interactions involved.
[...]
Model-based knowing has many well-documented difficulties, especially when we are attempting to predict real-world events subject to the vagaries of history; a Cretaceous-era model of that eras ecology would not have included the arrival of a giant asteroid in its data, and no one expects a black swan. Nevertheless, models can have the predictive power demanded of scientific hypotheses. We have a new form of knowing.
Go Try Things
So this isn't quite done, and its late here so I don't quite trust my judgements about writing at this hour. I've never done a top-level post before, so I wanted to get some feedback first.
Failure isn’t that Bad
You’ve probably read about how to properly turn information into beliefs, and how to squeeze every last bit from your data. What seems not to have received as much attention is the importance of just going and getting data.
For precise and well-defined fields and problems, clear thinking and reasoning will get you really far. Mathematics departments don’t use that much equipment, and they’ve been going fine for hundreds of years.
For more mundane day-to-day concerns, getting data is probably more important than being rational. Where Rationality helps you get an accurate model of the world based on the data, Data gets you well, data. And practice. Your human brain can’t rederive social rules in a vacuum, no matter how smart you are, so you have to go out and get information about it. But rationality with data is far better than either alone.
Sometimes you have to get your data by actually trying. Some things are just hard to explain in words and video. Your brain has all of this built in hardware for detecting and interpreting emotions and body language, but people are comparatively terrible at talking about it. This makes learning about different social or mood-variant things online difficult. Motions are also hard to teach online. I can kind of visualize how to do a front handspring, but I really can’t transmit what it feels like to someone else without just asking them to try it. Note: I’m not saying that asking others is useless, but I am saying that its mostly only effective as a complement to actually trying.
Practice is important. As any akrasiatic or novice would know, knowledge in a field or domain doesn’t translate directly to success in it. Like muscle memory, you need practice in order to get your brain to incorporate what you know to the point that you can use it automatically. Consciously thinking about what you’re doing while you’re doing it tends to cause lag and awkwardness, and in some fields (like conversation or physical activities) is a pretty large detriment.
I had/have the problem of hesitating on acting until I’m sure that whatever I’m considering attempting is going to be successful. I’m afraid of it not working, and am willing to do anything short of doing it in order to ensure success.
This kind of hesitation though, is pretty useless. In many cases failure to act is about the same as your action failing. It avoids doing things that you regret, but it also avoids doing things in general. And if your hesitation doesn’t result in a well thought-out plan to guarantee success in the future, then not only do you fail it that one time you hesitate, you’re not going to make progress on succeeding in the future.
Sometimes failure is actually a problem (like you’ll break something if you try extreme parkour tricks and fail), but I feel like in most instances I grossly overestimate how bad failing is. To combat this I do a few things:
- Consider a failure to act as an implicit failure. Not trying is as bad as trying and failing, except for whatever costs a failed attempt incur.
- Not regret failing. As long as I learn from my mistakes then making them results in a net gain. In the long term having failed at something and learning what to do is better than not attempting it.
- Attempt to minimize the cost of a failed attempt. I hesitate a lot with social things. If I fail with a stranger and never see them again, it’s not that big of a deal. They might be annoyed, but as long as I didn’t do something super horrible to them then they’re probably going to forget about it.
So long story short, try things out. Improvement is hard unless you do, and failure seriously isn’t that bad.
Link: The Uncertain Future - "The Future According to You"
Visualizing "The Future According to You"
The Uncertain Future is a future technology and world-modeling project by the Singularity Institute for Artificial Intelligence. Its goal is to allow those interested in future technology to form their own rigorous, mathematically consistent model of how the development of advanced technologies will affect the evolution of civilization over the next hundred years. To facilitate this, we have gathered data on what experts think is going to happen, in such fields as semiconductor development, biotechnology, global security, Artificial Intelligence and neuroscience. We invite you, the user, to read about the opinions of these experts, and then come to your own conclusion about the likely destiny of mankind.
Link: theuncertainfuture.com
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