Predicting who will live the longest

How the longevity community and prediction markets answer long-term questions without waiting decades

What can you do when you want answers to a question that won’t resolve for decades? The longevity research community has this problem, and one market demonstrates a clever solution.

Let’s say you want information about how to best extend your own lifespan. Diet and exercise (probably yes)? Fish oil? Resveratrol? Blood transfusions? There are a lot of ideas in the space, and a lot of pseudo-celebrity endorsers behind each. But actual human studies will take decades, and you presumably want to start taking action now. Which experts know what they’re talking about? Who can you believe? And whose advice should you follow?

Enter: Prediction Markets

On the surface, longevity is an ideal topic for prediction markets. The wisdom of the crowd, combined with possible insider knowledge from various research teams and influencers, should be able to help reveal which interventions have real promise, and which do not.

So you might post a question: which longevity expert will live the longest? This seems like a natural way to frame the question as a market; it should reveal the information you want about whose advice is worth researching for your own use. But this question has a problem: it leads to a very long-running market, likely several decades even in the case that the anti-aging experts all live average lifespans.

You might be a little bit clever, and instead ask which longevity expert will die the youngest? You can expect the information in the market to be about the same, but it can potentially be resolved much sooner. This is an improvement, but it’s still a long market. The subjects are healthy people in middle age who are trying to live long, it is likely to be decades until even one of them dies. Even after that happens, if it’s one of the older members, you have to wait for the youngest member to reach their age at death to resolve the market (an 8-year gap in the linked market).

Traders have an incentive to bet in shorter-term markets, all else being equal, so long markets end up with fewer corrective trades. The loan system helps to offset the imbalance, and there are markets set up to inform users of the relative value of short and long-term markets by measuring the discount rate on Mana. But the reduced precision and responsiveness of long-running markets should be a consideration when creating a new market.

Reframing for the short term

So how can we be even more clever and create a market that will run on the order of one year, which has been indicated as a sweet spot for Manifold markets? The longevity community has set up a proxy that’s being used in this market:

Instead of asking who will live the longest, die soonest, or any other question that may not resolve this century, much of the same information can be unearthed with this proxy question. Who will be at the top of the Rejuvenation Olympics leaderboard at the end of the year?

What is the Rejuvenation Olympics?

The question that we originally wanted to answer, how to extend our own lifespan, is not unique to Manifold. The longevity community also wants an answer, and one effort has set up this leaderboard of biomarkers that appear to be indicators of longevity. The participants submit standardized sample results that can be compared as a proxy for aging.

This system is not perfect. One flaw is that the measured signals may not correlate well with actual aging, the research behind them is relatively new. Another flaw is that one of the names in the market is a person who has editorial control over the leaderboard, as a founder of the project. The longevity community is relatively small, but that doesn’t stop them, on Manifold or outside of it, from trying to measure and predict progress.

What to do?

Longevity research is a topic that’s interesting to me. There’s a small, but growing, community behind it, and the movement and the related markets get more interesting every day. These markets can provide useful information despite the significant limitations on input data.

You probably have an interest in similar small communities. Ask yourself what new markets would benefit the community, and try to create them. If your interests are more long-term, look at this example, and try to create a proxy signal that can answer long-term questions with short-term data.