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The Effective Altruist Forum will be launched at effective-altruism.com on September 10, British time.
Now seems like a good time time to discuss why we might need an effective altruist forum, and how it might compare to LessWrong.
About the Effective Altruist Forum
The motivation for the Effective Altruist Forum is to improve the quality of effective altruist discussion and coordination. A big part of this is to give many of the useful features of LessWrong to effective altruists, including:
- Archived, searchable content (this will begin with archived content from effective-altruism.com)
- Nested comments
- A karma system
- A dynamically upated list of external effective altruist blogs
- Introductory materials (this will begin with these articles)
The effective altruist forum has been designed by Mihai Badic. Over the last month, it has been developed by Trike Apps, who have built the new site using the LessWrong codebase. I'm glad to report that it is now basically ready, looks nice, and is easy to use.
I expect that at the new forum, as on the effective altruist Facebook and Reddit pages, people will want to discuss the which intellectual procedures to use to pick effective actions. I also expect some proposals of effective altruist projects, and offers of resources. So users of the new forum will share LessWrong's interest in instrumental and epistemic rationality. On the other hand, I expect that few of its users will want to discuss the technical aspects of artificial intelligence, anthropics or decision theory, and to the extent that they do so, they will want to do it at LessWrong. As a result, I expect the new forum to cause:
- A bunch of materials on effective altruism and instrumental rationality to be collated for new effective altruists
- Discussion of old LessWrong materials to resurface
- A slight increase to the number of users of LessWrong, possibly offset by some users spending more of their time posting at the new forum.
At least initially, the new forum won't have a wiki or a Main/Discussion split and won't have any institutional affiliations.
It's really important to make sure that the Effective Altruist Forum is established with a beneficial culture. If people want to help that process by writing some seed materials, to be posted around the time of the site's launch, then they can contact me at ry [dot] duff [at] gmail.com. Alternatively, they can wait a short while until they automatically receive posting priveleges.
It's also important that the Effective Altruism Forum helps the shared goals of rationalists and effective altruists, and has net positive effects on LessWrong in particular. Any suggestions for improving the odds of success for the effective altruism forum are most welcome.
About 18 months ago I made a post here on my workflow. I've received a handful of requests for follow-up, so I thought I would make another post detailing changes since then. I expect this post to be less useful than the last one.
For the most part, the overall outline has remained pretty stable and feels very similar to 18 months ago. Things not mentioned below have mostly stayed the same. I believe that the total effect of continued changes have been continued but much smaller improvements, though it is hard to tell (as opposed to the last changes, which were more clearly improvements).
Based on comparing time logging records I seem to now do substantially more work on average, but there are many other changes during this period that could explain the change (including changes in time logging). Changes other than work output are much harder to measure; I feel like they are positive but I wouldn't be surprised if this were an illusion.
I now regularly divide my day into two halves, and treat the two halves as separate units. I plan each separately and reflect on each separately. I divide them by an hour long period of reflecting on the morning, relaxing for 5-10 minutes, napping for 25-30 minutes, processing my emails, and planning the evening. I find that this generally makes me more productive and happier about the day. Splitting my days is often difficult due to engagements in the middle of the day, and I don't have a good solution to that.
I have longstanding objections to explicitly rationing internet use (since it seems either indicative of a broader problem that should be resolved directly, or else to serve a useful function that would be unwise to remove). That said, I now use the extension WasteNoTime to limit my consumption of blogs, webcomics, facebook, news sites, browser games, etc., to 10 minutes each half-day. This has cut the amount of time I spend browsing the internet from an average of 30-40 minutes to an average of 10-15 minutes. It doesn't seem to have been replaced by lower-quality leisure, but by a combination of work and higher-quality leisure.
Similarly, I turned off the newsfeed in facebook, which I found to improve the quality of my internet time in general (the primary issue was that I would sometimes be distracted by the newsfeed while sending messages over facebook, which wasn't my favorite way to use up wastenotime minutes).
I also tried StayFocusd, but ended up adopting WasteNoTime because of the ability to set limits per half-day (via "At work" and "not at work" timers) rather than per-day. I find that the main upside is cutting off the tail of derping (e.g. getting sucked into a blog comment thread, or looking into a particularly engrossing issue), and for this purpose per half-day timers are much more effective.
I set gmail to archive all emails on arrival and assign them the special label "In." This lets me to search for emails and compose emails, using the normal gmail interface, without being notified of new arrivals. I process the items with label "in" (typically turning emails into todo items to be processed by the same system that deals with other todo items) at the beginning of each half day. Each night I scan my email quickly for items that require urgent attention.
Todo lists / reminders:
I continue to use todo lists for each half day and for a range of special conditions. I now check these lists at the beginning of each half day rather than before going to bed.
I also maintain a third list of "reminders." These are things that I want to be reminded of periodically, organized by day; each morning I look at the day's reminders and think about them briefly. Each of them is copied and filed under a future day. If I feel like I remember a thing well I file it in far in the future, if I feel like I don't remember it well I file it in the near future.
Over the last month most of these reminders have migrated to be in the form "If X, then Y," e.g. "If I agree to do something for someone, then pause, say `actually I should think about it for a few minutes to make sure I have time,' and set a 5 minute timer that night to think about it more clearly." These are designed to fix problems that I notice when reflecting on the day. This is a recommendation from CFAR folks, which seems to be working well, though is the newest part of the system and least tested.
I now attempt to isolate things that probably need doing, but don't seem maximally important; I aim to do them only on every 5th day, and only during one half-day. If I can't finish them in this time, I will typically delay them 5 days. When they spill over to other days, I try to at least keep them to one half-day or the other. I don't know if this helps, but it feels better to have isolated unproductive-feeling blocks of time rather than scattering it throughout the week.
I don't do this very rigidly. I expect the overall level of discipline I have about it is comparable to or lower than a normal office worker who has a clearer division between their personal time and work time.
I now use Toggl for detailed time tracking. Katja Grace and I experimented with about half a dozen other systems (Harvest, Yast, Klok, Freckle, Lumina, I expect others I'm forgetting) before settling on Toggl. It has a depressing number of flaws, but ends up winning for me by making it very fast to start and switch timers which is probably the most important criterion for me. It also offers reviews that work out well with what I want to look at.
I find the main value adds from detailed time tracking are:
1. Knowing how long I've spent on projects, especially long-term projects. My intuitive estimates are often off by more than a factor of 2, even for things taking 80 hours; this can lead me to significantly underestimate the costs of taking on some kinds of projects, and it can also lead me to think an activity is unproductive instead of productive by overestimating how long I've actually spent on it.
2. Accurate breakdowns of time in a day, which guide efforts at improving my day-to-day routine. They probably also make me feel more motivated about working, and improve focus during work.
Reflection / improvement:
Reflection is now a smaller fraction of my time, down from 10% to 3-5%, based on diminishing returns to finding stuff to improve. Another 3-5% is now redirected into longer-term projects to improve particular aspects of my life (I maintain a list of possible improvements, roughly sorted by goodness). Examples: buying new furniture, improvements to my diet (Holden's powersmoothie is great), improvements to my sleep (low doses of melatonin seem good). At the moment the list of possible improvements is long enough that adding to the list is less valuable than doing things on the list.
I have equivocated a lot about how much of my time should go into this sort of thing. My best guess is the number should be higher.
I don't use pomodoros at all any more. I still have periods of uninterrupted work, often of comparable length, for individual tasks. This change wasn't extremely carefully considered, it mostly just happened. I find explicit time logging (such that I must consciously change the timer before changing tasks) seems to work as a substitute in many cases. I also maintain the habit of writing down candidate distractions and then attending to them later (if at all).
For larger tasks I find that I often prefer longer blocks of unrestricted working time. I continue to use Alinof timer to manage these blocks of uninterrupted work.
Catch disappeared, and I haven't found a replacement that I find comparably useful. (It's also not that high on the list of priorities.) I now just send emails to myself, but I do it much less often.
I no longer use beeminder. This again wasn't super-considered, though it was based on a very rough impression of overhead being larger than the short-term gains. I think beeminder was helpful for setting up a number of habits which have persisted (especially with respect to daily routine and regular focused work), and my long-term averages continue to satisfy my old beeminder goals.
I now organize notes about each project I am working on in a more standardized way, with "Queue of todos," "Current workspace," and "Data" as the three subsections. I'm not thrilled by this system, but it seems to be an improvement over the previous informal arrangement. In particular, having a workspace into which I can easily write thoughts without thinking about where they fit, and only later sorting them into the data section once it's clearer how they fit in, decreases the activation energy of using the system. I now use Toggl rather than maintaining time logs by hand.
As described in my last post I tried various randomized trials (esp. of effects of exercise, stimulant use, and sleep on mood, cognitive performance, and productive time). I have found extracting meaningful data from these trials to be extremely difficult, due to straightforward issues with signal vs. noise. There are a number of tests which I still do expect to yield meaningful data, but I've increased my estimates for the expensiveness of useful tests substantially, and they've tended to fall down the priority list. For some things I've just decided to do them without the data, since my best guess is positive in expectation and the data is too expensive to acquire.
Yet another exceptionally interesting blog post by Scott Aaronson, describing his talk at the Quantum Foundations of a Classical Universe workshop, videos of which should be posted soon. Despite the disclaimer "My talk is for entertainment purposes only; it should not be taken seriously by anyone", it raises several serious and semi-serious points about the nature of conscious experience and related paradoxes, which are generally overlooked by the philosophers, including Eliezer, because they have no relevant CS/QC expertise. For example:
- Is an FHE-encrypted sim with a lost key conscious?
- If you "untorture" a reversible simulation, did it happen? What does the untorture feel like?
- Is Vaidman brain conscious? (You have to read the blog post to learn what it is, not going to spoil it.)
Scott also suggests a model of consciousness which sort-of resolves the issues of cloning, identity and such, by introducing what he calls a "digital abstraction layer" (again, read the blog post to understand what he means by that). Our brains might be lacking such a layer and so be "fundamentally unclonable".
Another interesting observation is that you never actually kill the cat in the Schroedinger's cat experiment, for a reasonable definition of "kill".
There are several more mind-blowing insights in this "entertainment purposes" post/talk, related to the existence of p-zombies, consciousness of Boltzmann brains, the observed large-scale structure of the Universe and the "reality" of Tegmark IV.
I certainly got the humbling experience that Scott is the level above mine, and I would like to know if other people did, too.
Finally, the standard bright dilettante caveat applies: if you think up a quick objection to what an expert in the area argues, and you yourself are not such an expert, the odds are extremely heavy that this objection is either silly or has been considered and addressed by the expert already.
When I talk to people about earning to give, it's common to hear worries about "backsliding". Yes, you say you're going to go make a lot of money and donate it, but once you're surrounded by rich coworkers spending heavily on cars, clothes, and nights out, will you follow through? Working at a greedy company in a selfishness-promoting culture you could easily become corrupted and lose initial values and motivation.
First off, this is a totally reasonable concern. People do change, and we are pulled towards thinking like the people around us. I see two main ways of working against this:
- Be public with your giving. Make visible commitments and then list your donations. This means that you can't slowly slip away from giving; either you publish updates saying you're not going to do what you said you would, or you just stop updating and your pages become stale. By making a public promise you've given friends permission to notice that you've stopped and ask "what changed?"
- Don't just surround yourself with coworkers. Keep in touch with friends and family. Spend some time with other people in the effective altruism movement. You could throw yourself entirely into your work, maximizing income while sending occasional substantial checks to GiveWell's top picks, but without some ongoing engagement with the community and the research this doesn't seem likely to last.
One implication of the "won't you drift away" objection, however, is often that if instead of going into earning to give you become an activist then you'll remain true to your values. I'm not so sure about this: many people who are really into activism and radical change in their 20s have become much less ambitious and idealistic by their 30s. You can call it "burning out" or "selling out" but decreasing idealism with age is very common. This doesn't mean people earning to give don't have to worry about losing their motivation—in fact it points the opposite way—but this isn't a danger unique to the "go work at something lucrative" approach. Trying honestly to do the most good possible is far from the default in our society, and wherever you are there's going to be pressure to do the easy thing, the normal thing, and stop putting so much effort into altruism.
The Feynman lectures on physics are now available to read online for free. This is a classic resource for not just learning physics also but also the process of science and the mindset of a scientific rationalist.
The New York Times has a calculator to explain how getting on a jury works. They have a slider at the top indicating how likely each of the two lawyers think you are to side with them, and as you answer questions it moves around. For example, if you select that your occupation is "blue collar" then it says "more likely to side with plaintiff" while "white collar" gives "more likely to side with defendant". As you give it more information the pointer labeled "you" slides back and forth, representing the lawyers' ongoing revision of their estimates of you. Let's see what this looks like.
- Selecting "Over 30"
- Selecting "Under 30"
For several other questions, however, the options aren't matched. If your household income is under $50k then it will give you "more likely to side with plaintiff" while if it's over $50k then it will say "no effect on either lawyer". This is not how conservation of expected evidence works: if learning something pushes you in one direction, then learning its opposite has to push you in the other.
Let's try this with some numbers. Say people's leanings are:
|income||probability of siding with plaintiff||probability of siding with defendant|
So the lawyers best guess for you is that you're at 60%, and then they ask the question. If you say ">$50k" then they update their estimate for you down to 50%, if you say "<$50k" they update it up to 70%. "No effect on either lawyer" can't be an option here unless the question gives no information.
 Almost; the median income in the US in 2012 was $51k. (pdf)
Much of the glamor and attention paid toward Friendly AI is focused on the misty-future event of a super-intelligent general AI, and how we can prevent it from repurposing our atoms to better run Quake 2. Until very recently, that was the full breadth of the field in my mind. I recently realized that dumber, narrow AI is a real thing today, helpfully choosing advertisements for me and running my 401K. As such, making automated programs safe to let loose on the real world is not just a problem to solve as a favor for the people of tomorrow, but something with immediate real-world advantages that has indeed already been going on for quite some time. Veterans in the field surely already understand this, so this post is directed at people like me, with a passing and disinterested understanding of the point of Friendly AI research, and outlines an argument that the field may be useful right now, even if you believe that an evil AI overlord is not on the list of things to worry about in the next 40 years.
Let's look at the stock market. High-Frequency Trading is the practice of using computer programs to make fast trades constantly throughout the day, and accounts for more than half of all equity trades in the US. So, the economy today is already in the hands of a bunch of very narrow AIs buying and selling to each other. And as you may or may not already know, this has already caused problems. In the “2010 Flash Crash”, the Dow Jones suddenly and mysteriously hit a massive plummet only to mostly recover within a few minutes. The reasons for this were of course complicated, but it boiled down to a couple red flags triggering in numerous programs, setting off a cascade of wacky trades.
The long-term damage was not catastrophic to society at large (though I'm sure a couple fortunes were made and lost that day), but it illustrates the need for safety measures as we hand over more and more responsibility and power to processes that require little human input. It might be a blue moon before anyone makes true general AI, but adaptive city traffic-light systems are entirely plausible in upcoming years.
To me, Friendly AI isn't solely about making a human-like intelligence that doesn't hurt us – we need techniques for testing automated programs, predicting how they will act when let loose on the world, and how they'll act when faced with unpredictable situations. Indeed, when framed like that, it looks less like a field for “the singularitarian cultists at LW”, and more like a narrow-but-important specialty in which quite a bit of money might be made.
After all, I want my self-driving car.
(To the actual researchers in FAI – I'm sorry if I'm stretching the field's definition to include more than it does or should. If so, please correct me.)
(Cross-posted from my blog.)
Since some belief-forming processes are more reliable than others, learning by what processes different beliefs were formed is for several reasons very useful. Firstly, if we learn that someone's belief that p (where p is a proposition such as "the cat is on the mat") was formed a reliable process, such as visual observation under ideal circumstances, we have reason to believe that p is probably true. Conversely, if we learn that the belief that p was formed by an unreliable process, such as motivated reasoning, we have no particular reason to believe that p is true (though it might be - by luck, as it were). Thus we can use knowledge about the process that gave rise to the belief that p to evaluate the chance that p is true.
Secondly, we can use knowledge about belief-forming processes in our search for knowledge. If we learn that some alleged expert's beliefs are more often than not caused by unreliable processes, we are better off looking for other sources of knowledge. Or, if we learn that the beliefs we acquire under certain circumstances - say under emotional stress - tend to be caused by unreliable processes such as wishful thinking, we should cease to acquire beliefs under those circumstances.
Thirdly, we can use knowledge about others' belief-forming processes to try to improve them. For instance, if it turns out that a famous scientist has used outdated methods to arrive at their experimental results, we can announce this publically. Such "shaming" can be a very effective means to scare people to use more reliable methods, and will typically not only have an effect on the shamed person, but also on others who learn about the case. (Obviously, shaming also has its disadvantages, but my impression is that it has played a very important historical role in the spreading of reliable scientific methods.)
A useful way of inferring by what process a set of beliefs was formed is by looking at its structure. This is a very general method, but in this post I will focus on how we can infer that a certain set of beliefs most probably was formed by (politically) motivated cognition. Another use is covered here and more will follow in future posts.
Let me give two examples. Firstly, suppose that we give American voters the following four questions:
- Do expert scientists mostly agree that genetically modified foods are safe?
- Do expert scientists mostly agree that radioactive wastes from nuclear power can be safely disposed of in deep underground storage facilities?
- Do expert scientists mostly agree that global temperatures are rising due to human activities?
- Do expert scientists mostly agree that the "intelligent design" theory is false?
The answer to all of these questions is "yes".* Now suppose that a disproportionate number of republicans answer "yes" to the first two questions, and "no" to the third and the fourth questions, and that a disproportionate number of democrats answer "no" to the first two questions, and "yes" to the third and the fourth questions. In the light of what we know about motivated cognition, these are very suspicious patterns or structures of beliefs, since that it is precisely the patterns we would expect them to arrive at given the hypothesis that they'll acquire whatever belief on empirical questions that suit their political preferences. Since no other plausibe hypothesis seem to be able to explain these patterns as well, this confirms this hypothesis. (Obviously, if we were to give the voters more questions and their answers would retain their one-sided structure, that would confirm the hypothesis even stronger.)
Secondly, consider a policy question - say minimum wages - on which a number of empirical claims have bearing. For instance, these empirical claims might be that minimum wages significantly decrease employers' demand for new workers, that they cause inflation, that they significantly increase the supply of workers (since they provide stronger incentives to work) and that they significantly reduce workers' tendency to use public services (since they now earn more). Suppose that there are five such claims which tell in favour of minimum wages and five that tell against them, and that you think that each of them has a roughly 50 % chance of being true. Also, suppose that they are probabilistically independent of each other, so that learning that one of them is true does not affect the probabilities of the other claims.
Now suppose that in a debate, all proponents of minimum wages defend all of the claims that tell in favour of minimum wages, and reject all of the claims that tell against them, and vice versa for the opponents of minimum wages. Now this is a very surprising pattern. It might of course be that one side is right across the board, but given your prior probability distribution (that the claims are independent and have a 50 % probability of being true) a more reasonable interpretation of the striking degree of coherence within both sides is, according to your lights, that they are both biased; that they are both using motivated cognition. (See also this post for more on this line of reasoning.)
The difference between the first and the second case is that in the former, your hypothesis that the test-takers are biased is based on the fact that they are provably wrong on certain questions, whereas in the second case, you cannot point to any issue where any of the sides is provably wrong. However, the patterns of their claims are so improbable given the hypothesis that they have reviewed the evidence impartially, and so likely given the hypothesis of bias, that they nevertheless strongly confirms the latter. What they are saying is simply "too good to be true".
These kinds of arguments, in which you infer a belief-forming process from a structure of beliefs (i.e you reverse engineer the beliefs), have of course always been used. (A salient example is Marxist interpretations of "bourgeois" belief structures, which, Marx argued, supported their material interests to a suspiciously high degree.) Recent years have, however, seen a number of developments that should make them less speculative and more reliable and useful.
Firstly, psychological research such as Tversky and Kahneman's has given us a much better picture of the mechanisms by which we acquire beliefs. Experiments have shown that we fall prey to an astonishing list of biases and identified which circumstances that are most likely to trigger them.
Secondly, a much greater portion of our behaviour is now being recorded, especially on the Internet (where we spend an increasing share of our time). This obviously makes it much easier to spot suspicious patterns of beliefs.
Thirdly, our algorithms for analyzing behaviour are quickly improving. FiveLabs recently launched a tool that analyzes your big five personality traits on the basis of your Facebook posts. Granted, this tool does not seem completely accurate, and inferring bias promises to be a harder task (since the correlations are more complicated than that between usage of exclamation marks and extraversion, or that betwen using words such as "nightmare" and "sick of" and neuroticism). Nevertheless, better algorithms and more computer power will take us in the right direction.
In my view, there is thus a large untapped potential to infer bias from the structure of people's beliefs, which in turn would be inferred from their online behaviour. In coming posts, I intend to flesh out my ideas on this in some more details. Any comments are welcome and might be incorporated in future posts.
* The second and the third questions are taken from a paper by Dan Kahan et al, which refers to the US National Academy of Sciences (NAS) assessment of expert scientists' views on these questions. Their study shows that many conservatives don't believe that experts agree on climate change, whereas a fair number of liberals think experts don't agree that nuclear storage is safe, confirming the hypothesis that people let their political preferences influence their empirical beliefs. The assessment of expert consensus on the first and fourth question are taken from Wikipedia.
Asking people what they think about the expert consensus on these issues, rather than about the issues themselves, is good idea, since it's much easier to come to an agreement on what the true answer is on the former sort of question. (Of course, you can deny that professors from prestigious universities count as expert scientists, but that would be a quite extreme position that few people hold.)
If it's worth saying, but not worth its own post (even in Discussion), then it goes here.
Notes for future OT posters:
1. Please add the 'open_thread' tag.
2. Check if there is an active Open Thread before posting a new one.
3. Open Threads should be posted in Discussion, and not Main.
4. Open Threads should start on Monday, and end on Sunday.
So, here's the study¹:
It's veterans' day in Canada. As any good Canadian knows, you're supposed to wear a poppy to show you support the veterans (it has something to do with Flanders Field). As people enter a concourse on the university, a person there does one of three things: gives them a poppy to wear on their clothes; gives them an envelope to carry and tells them (truthfully) that there's a poppy inside; or gives them nothing. Then, after they've crossed the concourse, another person asks them if they want to put donations in a box to support Canadian war veterans.
Who do you think gives the most?
If you guessed that it's the people who got the poppy inside the envelope, you're right. 78% of them gave, for an overall average donation of $0.86. That compares to 58% of the people wearing the poppy, for an average donation of $0.34; and 56% of those with no poppy, for an average of $0.15.
Why did the envelope holders give the most? Unlike the no-poppy group, they had been reminded of the expectation of supporting veterans; but unlike the poppy-wearers, they hadn't been given an easy, cost-free means of demonstrating their support.
I think this research has obvious applications, both to fundraising and to self-hacking. It also validates the bible quote (Matthew 6:3) which is the title of this article.
¹ The Nature of Slacktivism: How the Social Observability of an Initial Act of Token Support Affects Subsequent Prosocial Action; K Kristofferson, K White, J Peloza - Journal of Consumer Research, 2014
Some of the comments on the link by James_Miller exactly six months ago provided very specific estimates of how the events might turn out:
- The odds of Russian intervening militarily = 40%.
- The odds of the Russians losing the conventional battle (perhaps because of NATO intervention) conditional on them entering = 30%.
- The odds of the Russians resorting to nuclear weapons conditional on them losing the conventional battle = 20%.
"Russians intervening militarily" could be anything from posturing to weapon shipments to a surgical strike to a Czechoslovakia-style tank-roll or Afghanistan invasion. My guess that the odds of the latter is below 5%.
A bet between James_Miller and solipsist:
I will bet you $20 U.S. (mine) vs $100 (yours) that Russian tanks will be involved in combat in the Ukraine within 60 days. So in 60 days I will pay you $20 if I lose the bet, but you pay me $100 if I win.
While it is hard to do any meaningful calibration based on a single event, there must be lessons to learn from it. Given that Russian armored columns are said to capture key Ukrainian towns today, the first part of James_Miller's prediction has come true, even if it took 3 times longer than he estimated.
Note that even the most pessimistic person in that conversation (James) was probably too optimistic. My estimate of 5% appears way too low in retrospect, and I would probably bump it to 50% for a similar event in the future.
Now, given that the first prediction came true, how would one reevaluate the odds of the two further escalations he listed? I still feel that there is no way there will be a "conventional battle" between Russia and NATO, but having just been proven wrong makes me doubt my assumptions. If anything, maybe I should give more weight to what James_Miller (or at least Dan Carlin) has to say on the issue. And if I had any skin in the game, I would probably be even more cautious.
This summary was posted to LW Main on August 15th. The following week's summary is here.
Irregularly scheduled Less Wrong meetups are taking place in:
- [Atlanta] MIRIxAtlanta - Decision Theory 2: 17 August 2014 06:00PM
- Bratislava: 18 August 2014 06:00PM
- Helsinki Book Blanket Meetup: 16 August 2014 03:00PM
- Houston, TX: 13 September 2014 02:00PM
- Perth, Australia: Sunday lunch: 17 August 2014 12:00PM
- Perth, Australia: Games night: 02 September 2014 06:00PM
The remaining meetups take place in cities with regular scheduling, but involve a change in time or location, special meeting content, or simply a helpful reminder about the meetup:
- Austin, TX: 16 August 2025 01:30PM
- [Cambridge MA] The Psychology of Video Games: 17 August 2014 03:30PM
- Canberra: Cooking for LessWrongers: 22 August 2014 06:00PM
- [Moscow] Regular Moscow Meetup: 17 August 2014 02:00PM
- Sydney Meetup - August: 27 August 2014 06:30PM
- [Utrecht] Cognitive Biases: 23 August 2014 02:00PM
- Washington, D.C.: Fun & Games Meetup: 17 August 2014 03:00PM
Locations with regularly scheduled meetups: Austin, Berkeley, Berlin, Boston, Brussels, Buffalo, Cambridge UK, Canberra, Columbus, London, Madison WI, Melbourne, Moscow, Mountain View, New York, Philadelphia, Research Triangle NC, Salt Lake City, Seattle, Sydney, Toronto, Vienna, Washington DC, Waterloo, and West Los Angeles. There's also a 24/7 online study hall for coworking LWers.
At the Australia online hangout; one of the topics we discussed (before I fell asleep on camera for a bunch of people) Was writing a rationality TV show as an outreach task. Of course there being more ways for this to go wrong than right I figured its worth mentioning the ideas and getting some comments.
The strategy is to have a set of regular characters who's rationality behaviour seems nuts. Effectively sometimes because it is; when taken out of context. Then to have one "blank" person who tries to join - "rationality house". and work things out. My aim was to have each episode straw man a rationality behaviour and then steelman it. Where by the end of the episode it saves the day; makes someone happy; achieves a goal - or some other <generic win-state>.
Here is a list of notes of characters from the hangout or potential topics to talk about.
- No showers. Bacterial showers
- Stopwatches everywhere
- temperature controls everywhere, light controls.
- radical honesty person.
- Soylent only eating person
- born-again atheist
- bayesian person
- Polyphasic sleep cycles.
I have found (there is some (evidence)[http://mentalfloss.com/article/52586/why-do-our-best-ideas-come-us-shower] to suggest this) that showers are a great place to think. While I am taking a shower I find that I can think about things in a whole new perspective and it's very refreshing. Well today, while I was taking a shower, an interesting thing popped into my head. Memory is everything. Your memory contains you, it contains your thoughts, it contains your own unique perception of reality. Imagine going to bed tonight and waking up with absolutely no memory of your past. Would you still consider that person yourself? There is no question that our memories/experiences influence our behavior in every possible way. If you were born in a different environment with different stimuli you would've responded to your environment differently and became a different person. How different? I don't want to get involved in the nature/nurture debate but I think there is no question that humans are influenced by their environment. How are humans influenced by our environment? Through learning from our past experiences, which are contained in our memory. I'm getting off topic and I have no idea what my point is... So I propose a thought experiment!
Omega the supercomputer gives you 3 Options. Option 1 is for you to pay Omega $1,000,000,000 and Omega will grant you unlimited utility potential for 1 week in which Omega will basically provide to your every wish. You will have absolutely no memory of the experience after the week is up. Option 2 is for Omega to pay you $1,000,000,000 but you must be willing to suffer unlimited negative utility potential for a week (you will not be harmed physically or mentally you will simply experience excruciating pain). You will also have absolutely memory of this experience after the week (your subconscious will also not be affected). Finally, Option 3 is simply to refuse Option 1 and 2 and maintain the status quo.
At first glance, it may seem that Option 2 is simply not choosable. It seems insane to subject yourself to torture when you have the option of nirvana. But it requires more thought than that. If you compare Option 1 to Option 2 after the week is up there is no difference between the options except that Option 2 nets you 2 billion dollars compared to Option 1. In both Options you have absolutely no memory of either weeks. The question that I'm trying to put forward in this thought experiment is this. If you have no memory of an experience does that experience still matter? Is it worth experiencing something for the experience alone or is it the memory of an experience that matters? Those are some questions that I have been thinking about lately. Any feedback or criticism is appreciated.
One last thing, if you are interested in the concept and importance of memory two excellent movies on the subject are [Memento](http://www.imdb.com/title/tt0209144/) and [Eternal Sunshine of the Spotless Mind](http://www.imdb.com/title/tt0338013/0). I know they both of these movies aren't scientific but I thought them to be very intriguing and thought provoking.