Follow-Up to Good Judgment Project, Season Three.

During the last forecasting season I took part in the Good Judgment Project (GJP; see also the blog) and this is a short summary of my participation (actually triggered by hamnox comment).

The GJP estimates world events like

• Ukraine conflict
• Arctic ice cap melting
• Ebola outbreak duration
• Chinese sea conflict
• ISIS attacks
• Terrorist attacks
• Oil price
• Certain exchange rates
• Election results
• and many other political events

To participate in that study one has to register (can't remember where exactly I stumbled over the link, possibly the one at the top). And one has to do an preparatory online course and one has to pass an online test. At least I had to complete it. Whether the result affected my assignment to any group I can't say. The course explains the scoring and gives recommendations for making good forecasts (choose forecasts one has an edge in, estimate early, update often, do post-mortems). The test seems to test for calibration and accuracy by asking for known (mostly political) events and whether one is sure about them.

The current forecasting season started in November 2014 and has just ended. I invested significantly less then half an hour a week on 8 questions of about 100 (and thus less than I projected in an early questionaire). I did 2 to 15 updates for these questions and I earned a score in the middle range (mostly due to getting hit by an unexpected terrorist attack). As I just learned I was assigned to the study condition were I could neither see the total group estimate nor the estimates of the other group members - only their comments. I was somewhat disappointed by this as I had hoped to learn something from how the scores developed. Too bad I wasn't in a prediction marked group. But I hope to get the study results later.

I will not take part in further rounds as I shy the effort for the types of forecasts which are mostly political. They are political because the sponsor (guess who) is interested mostly in political events - less in economical, environmental, scientific or other types. But I enjoyed forecasting artic ice cap melting and ebola - and netted a better than average score on that. 

The scoring - at least in this group - is interesting and uses an averaged Brier Score - averaged over a) all forecast questiontion and b) within a question over all the days for which a forecast is provided. I intended to game that by betting on questions that a) I could forecast well and b) that had an expected reliable outcome. Sadly there were few of type a.

From this experience I learned that

• such prediction organizations ask mostly for political events,
• political events are hard to predict and
• predicting political events requires a lot of background information.
• I'm below average in predicting political event (at least compared to my group which I'd guess has more interest in politics than I) but
• I'm above average on non-political topics.

Bayesian inference with probabilistic population codes by Wei Ji Ma et al 2006

Recent psychophysical experiments indicate that humans perform near-optimal Bayesian inference in a wide variety of tasks, ranging from cue integration to decision making to motor control. This implies that neurons both represent probability distributions and combine those distributions according to a close approximation to Bayes’ rule. At first sight, it would seem that the high variability in the responses of cortical neurons would make it difficult to implement such optimal statistical inference in cortical circuits. We argue that, in fact, this variability implies that populations of neurons automatically represent probability distributions over the stimulus, a type of code we call probabilistic population codes. Moreover, we demonstrate that the Poissonlike variability observed in cortex reduces a broad class of Bayesian inference to simple linear combinations of populations of neural activity. These results hold for arbitrary probability distributions over the stimulus, for tuning curves of arbitrary shape and for realistic neuronal variability.

Note that "humans perform near-optimal Bayesian inference" refers to the integration of information - not conscious symbolic reasoning. Nonetheless I think this is of interest here. 

Over at Scott Adams' Blog you can find a very fine example of using the 'Rationality Engine' to solve the social problem of assisted dying.

Technology can be used and perceived in different ways. Future technology may change our lives beyond imagination. How can friendly AI technology enrich human experience in a positive way? Technology can feel like it controls us or - if it goes well - it can feel like a natural enhancement of mind and body.

I'm interested in ways future technology could or couldn't do this. I will explore some avenues and state my opinion on these. Make up your mind. I'd like to hear your opinion.

“Happiness in intelligent people is the rarest thing I know.” ― Ernest Hemingway, The Garden of Eden see here

Did you know The surprising downsides of being clever? Is Happiness And Intelligence: Rare Combination? There are longitudinal studies which seem to imply this: Being Labeled as Gifted, Self-appraisal, and Psychological Well-being: A Life Span Developmental Perspective

I found these via slashdot.

As LessWrong is harbor to unusually high-IQ people (see section B in here). I wonder how happiness compares to the mean. What are your thoughts.

Related-to Focus Areas of Effective Altruism

These are some small tidbits from our LW-like Meetup in Hamburg. The focus was on sustainability not on altruism as that was more in the spirit of our group. EA was mentioned but no comparison was made. Well-informed effective altruists will probably find little new in this writeup.

So we discussed effective sustainability. To this end we were primed to think rationally by my 11-year old who moderated a session on mind-mapping 'reason' (with contributions from the children). Then we set out to objectively compare concrete everyday things by their sustainability. And how to do this. 

Is it better to drink fruit juice or wine? Or wine or water? Or wine vs. nothing (i.e.to forego sth.)? Or wine vs. paper towels? (the latter intentionally different)

The idea was to arrive at simple rules of thumb to evaluate the sustainability of something. But we discovered that even simple comparisons are not that simple and intuition can run afoul (surpise!). One example was that apparently tote bags are not clearly better than plastic bags in terms of sustainability. But even the simple comparison of tap water vs. wine which seems like a trivial subset case is non-trivial when you consider where the water comes from and how it is extracted from the ground (we still think that water is better but we not as sure as before).

We discussed some ways to measure sustainability (in brackets to which we reduced it):

• fresh water use -> energy
• packaging material used -> energy, permanent ressources
• transport -> energy
• energy -> CO_2, permanent ressources
• CO_2 production 
• permanent consumption of ressources

Life-Cycle-Assessment (German: Ökobilanz) was mentioned in this context but it was unclear what that meant precisely. Only afterwards was it discovered that it's a blanket term for exactly this question (with lots of estabilished measurements for which it is unclear how to simplify them for everyday use).

We didn't try to break this down - a practical everyday approch doesn't allow for that and the time spent on analysing and comparing options is also equivalent to ressources possibly not spent efficiently.

One unanswered question was how much time to invest in comparing alternatives. Too little comparison means to take the nextbest option which is what most people apparently do and which also apparently doesn't lead to overall sustainable behavior. But too much analysis of simple decisions is also no option.

The idea was still to arrive at actionable criteria. One first approximation be settled on was

1) Forego consumption. 

A nobrainer really, but maybe even that has to be stated. Instead of comparing options that are hard to compare try to avoid consumption where you can. Water instead of wine or fruit juice or lemonde. This saves lots of cognitive ressources.

Shortly after we agreed on the second approximation:

2) Spend more time on optimizing ressources you consume large amounts of.

The example at hand was wine (which we consume only a few times a year) versus toilet paper... No need to feel remorse over a one-time present packaging.

Note that we mostly excluded personal well-being, happiness and hedons from our consideration. We were aware that our goals affect our choices and hedons have to factored into any real strategy, but we left this additional complication out of our analysis - at least for this time.

We did discuss signalling effects. Mostly in the context of how effective ressources can be saved by convincing others to act sustainably. One important aspect for the parents was to pass on the idea and to act as a role model (with the caveat that children need a simplified model to grasp the concept). It was also mentioned humorously that one approach to minimize personal ressource consumption is suicide and transitively to convice others of same. The ultimate solution having no humans on the planet (a solution my 8-year old son - a friend of nature - arrived at too). This apparently being the problem when utilons/hedons are expluded.

A short time we considered whether outreach comes for free (can be done in addition to abstinence) and should be the no-brainer number 3. But it was then realized that at least right now and for us most abstinence comes at a price. It was quoted that buying sustainable products is about 20% more expensive than normal products. Forgoing e.g. a car comes at reduced job options. Some jobs involve supporting less sustainable large-scale action. Having less money means less options to act sustaibale. Time being convertible to money and so on.

At this point the key insight mentioned was that it could be much more efficient from a sustainability point of view to e.g. buy CO_2 certificates than to buy organic products. Except that the CO_2 certificate market is oversupplied currently. But there seem to be organisations which promise to achieve effective CO_2 reduction in developing countries (e.g. solar cooking) at a much higher rate than be achieved here. Thus the thrid rule was

3) Spend money on sustainable organisations instead of on everyday products that only give you a good feeling.

Discussion article for the meetup : LessWrong-like Meetup Hamburg

Discussion article for the meetup : LessWrong-like Meetup Hamburg

On Combat - The Psychology and hysiology of Deadly Conflict in War and in Peace by Lt. Col. Dave Grossman and Loren W. Christensen (third edition from 2007) is a well-written, evidence-based book about the reality of human behaviour in life-threatening situations. It is comprehensive (400 pages), provides detailed descriptions, (some) statistics as well as first-person recounts, historical context and other relevant information. But my main focus in this post is in the advice it gives and what lessons the LessWrong community may take from it.

TL;DR

In deadly force encounters you will experience and remember the most unusual physiological and psychological things. Innoculate yourself against extreme stress with repeated authentic training; play win-only paintball, train 911-dialing and -reporting. Train combat breathing. Talk to people after traumatic events.

Your job, should you choose to accept it, is to comment on this thread explaining the most awesome thing you've done this month. You may be as blatantly proud of yourself as you feel. You may unabashedly consider yourself the coolest freaking person ever because of that awesome thing you're dying to tell everyone about. This is the place to do just that.