(Author here.) I agree with this critique in theory, but not in practice. The stakes don't need to be high to encourage strong participation. Corporate prediction markets have already scaled quite far, and those who have studied them don't find evidence of manipulation.
Can't let perfect be the enemy of the good!
If you want a fuller critique of prediction markets in the corporate setting, see the Dec 2021 article linked near the end [1].
> A senior executive saw Prophit give a very low probability that the company would complete the hire of a new senior executive on time (filling the position had been a quarterly objective for the past six quarters). “The betting on this goal was extremely harsh. I am shocked and outraged by the lack of brown-nosing at this company,” the executive said to laughter in a company-wide meeting. But the market was the nudge the execs needed. They subsequently “made some hard decisions” to complete the hire on time.
Indeed. The whole point of the prediction markets espoused is to alter the decisions being made. That means the prediction itself can have an impact on the outcome intentionally or otherwise.
Yes, this example does illustrate this point. As I acknowledge later in the article:
> This turns out to be a general lesson from running a corporate prediction market. Forecasting internal progress, and acting on that information, requires solving complex operational problems and understanding the moral mazes that managers face. Forecasting competitors’ progress has almost none of these problems.
Forecasts on competitors (or, say, regulators) avoids this problem... unless employees are manipulating the outside world too!
Yes it has fewer problems, but not 0. The social network between competitors can be quite tight because the communities involved are so small. So the predictions can be used as social taunts or challenges. Similarly, I can conspire with my friends working for said competitors to game the system to win the prize if the prize is valuable enough.
Basically, betting markets have all the problems and risks of traditional public markets (insider trading) without any of the regulation or ability to enforce the law.
> Indeed. The whole point of the prediction markets espoused is to alter the decisions being made. That means the prediction itself can have an impact on the outcome intentionally or otherwise.
Which is great when the impact of the prediction market is "people making hard decisions" and not so great when they're studiously slowing down the process because they've got a bet on something not happening on time...
I think one criticism that the linked post misses but the OP article touches on is that most forecasts (whether they be prediction markets or super-forecasting style) is that they often predict the wrong things.
> We asked questions of the type “Will Google integrate LLMs into Gmail by Spring 2023?” and “How many parameters will the next LaMDA model have?” Yet what executives would have wanted to know was “Will Microsoft integrate LLMs into Outlook by Spring 2023?” and “How many parameters will the next GPT model have?”
It's really hard to build a prediction market for these things and I'm not sure "forecasting" is the right way of thinking about them.
The stakes don't need to be high to encourage strong participation.
OK but strong participation isn't necessarily a positive for the accuracy of a market. The problem is the prediction market with lots of participants can be just outlet for partisans to put forward their opinions. There's a tax on wrong opinions but someone is spending a bucks, the markets won't be a powerful force for changing those opinions.
What you want for a prediction market is for the major participants to actively researching the problems - expend money and effort to have a well founded reason for their positions. Markets for random real-world events have the problem that many events don't occur often to weed out arbitrary biases and there may not be any easy or cost effect way to attain a well-founded opinion on the subject.
Can't let perfect be the enemy of the good!
If you want a fuller critique of prediction markets in the corporate setting, see the Dec 2021 article linked near the end [1].
[1] https://forum.effectivealtruism.org/posts/dQhjwHA7LhfE8YpYF/...