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author: niplav, created: 2023-08-28, modified: 2023-08-28, language: english, status: finished, importance: 7, confidence: certain

There are too many possible quantified self experiments to run. Do hobbyist prediction platforms1 make priorisation easier? I test this by setting up multiple markets and running two experiments on nootropics for meditation.

Using Prediction Platforms to Select Quantified Self Experiments

dynomight 2022 has a good proposal:

Fortunately, there’s a good (and well-known) alternative, which is to randomize decisions sometimes, at random. You tell people: “I will roll a 20-sided die. If it comes up 1-19, everyone gets their money back and I do what I want. If it comes up 20, the bets activate and I decide what to do using a coinflip.”

What’s nice about this is that you can do whatever you want when 1-19 come up, including making your decisions using the market prices. But you must make decisions randomly sometimes, because if bets never activate, no one will waste their time betting in your market.

This is elegant. Oh, and by the way are you THE NSF or DARPA or THE NIH or A BILLIONAIRE WHO WANTS TO SPEND LOTS OF MONEY AND BRAG ABOUT HOW YOU ADVANCED THE STATE OF HUMAN KNOWLEDGE MORE THAN ALL THOSE OTHER LAME BILLIONAIRES WHO WOULDN’T KNOW A HIGH ROI IF IT HIT THEM IN THE FACE? Well how about this:

  1. Gather proposals for a hundred RCTs that would each be really expensive but also really awesome. (E.g. you could investigate SALT → MORTALITY or ALCOHOL → MORTALITY or UBI → HUMAN FLOURISHING.)
  2. Fund highly liquid markets to predict the outcome of each of these RCTs, conditional on them being funded.
    • If you have hangups about prison, you might want to chat with the CFTC before doing this.
  3. Randomly pick 5% of the proposed projects, fund them as written, and pay off the investors who correctly predicted what would happen.
  4. Take the other 95% of the proposed projects, give the investors their money back, and use the SWEET PREDICTIVE KNOWLEDGE to pick another 10% of the RCTs to fund for STAGGERING SCIENTIFIC PROGRESS and MAXIMAL STATUS ENHANCEMENT.

dynomight, “Prediction market does not imply causation”, 2022

Well, I'm neither a billionaire nor the NSF or DARPA, but I have run two shitty self-blinded RCTs on myself already, and I'm certainly not afraid of the CFTC. And indeed I don't have a shortage of ideas on things I could run RCTs on, but the time is scarce (I try to collect m=50 samples in each RCT, which (with days off) is usually more than 2 months of data collection).

So I'll do what @saulmunn pointed out to me is a possibility: I'm going to do futarchy myself by setting up a set of markets of Manifold Markets with respect to the outcomes of some pre-specified self-blinded RCTs, waiting until bets on them accumulate, and then running two of those RCTs (the "best" one, by my standards, and a random one) and using the results as resolutions, while resolving the others as ambiguous.

Timeline

If the markets receive enough liquidity, I'll start the first experiment early in 2024, and the second one sometime in 2024 (depending on the exact experiment), hopefully finishing both before 2025.

Markets

Some experiments can be self-blinded, especially ones that involve substances, others can not because they require me to engage in an activity or receive some sensory input), so I distinguish the two, and will slightly prioritise the experiments that can be blinded.

In all experiments, I will be using the statistical method detailed here, code for it here.

Self-Blinded Experiments

  1. L-Theanine + Caffeine vs. SugarMeditative absorption: 50 samples in the morning after waking up, 25 intervention with 500mg l-theanine & 200mg caffeine and 25 placebo (sugar pills). Expected duration of trial: ~2½ months (one sample every day, but with possible pauses).
  2. Nicotine vs. Normal chewing gumMeditative absorption: 40 samples, with blocking after waking up, 20 intervention with 2mg nicotine, 20 placebo (similar-looking square chewing gum). Expected duration of trial: ~4½ months (two samples/week, to avoid getting addicted to nicotine).
  3. Modafinil vs. SugarMeditative absorption: 40 samples, again with blocking directly after waking up, 20 intervention with 100mg modafinil and 20 placebo (sugar pills). Expected duration of trial: Also ~4½ months with two samples per week, as to prevent becoming dependent on modafinil.
  4. Vitamin D vs. SugarMeditative absorption: 50 samples, taken after waking up, 25 intervention (25μg Vitamin D₃) and 25 placebo (sugar pills). Expected duration of trial: ~2½ months (taken ~every day, with possible pauses).
  5. Vitamin B12 vs. SugarMeditative absorption
  6. LSD Microdosing vs. WaterMeditative absorption: 50 samples in the morning, 25 intervention (10μg LSD), and 25 placebo (distilled water). Expected duration of trial is ~4 months (4 samples per week, with some time left as a buffer).
  7. CBDMeditative absorption
  8. THCMeditative absorption
  9. AspartameMeditative absorption
  10. PhenylalanineMeditative absorption
  11. BupropionHappiness

Non-Blinded Experiments

  1. Intermittent fastingHappiness
  2. MeditationSleep duration
  3. Binaural beatsMeditative absorption
  4. Brown noise vs. MusicProductivity
  5. Silence vs. MusicProductivity
  6. Pomodoro methodProductivity
  7. Time since last masturbationProductivity
  8. Time since last masturbationHappiness

Plea

I would love to subsidise my markets on Manifold a whole bunch, but don't have enough mana for that (I've subsidised them best I could).

So here is my plea: Please predict on the markets!

It would be cool to know whether hobbyist prediction markets can be used for choosing experiments, and the worst result would be a "well, we can't really tell because liquidity on the markets was too small".

Further Ideas

Combinatorial prediction markets, latent-variable prediction markets.

Results


  1. I refuse to call any platform on which people functionally give probabilities, but without staking real money, "prediction markets". Neither Metaculus not Manifold Markets are prediction markets, but PredictIt and Kalshi are.