This post was initially written in French, Si personne ne paie pour la preuve, tout le monde paiera pour le sinistre
Let’s start with a truism. In ordinary life, just as in economic life, we have to make decisions without ever knowing everything. Every decision involves some uncertainty, and therefore some risk. Some risks are small, manageable, and we barely notice them anymore. Others can have financial consequences large enough that we would rather transfer them to a third party, by paying a premium so that an insurer will bear them for us. That is, at bottom, one of the most concrete functions of insurance. But an equally interesting question arises when that transfer becomes impossible, or at least impossible at a reasonable price. That is what we call uninsurability. We already encounter it with certain natural risks, when losses become too correlated, too massive, too difficult to mutualize, as I discussed in Insurers and AI, a systemic risk and in Insuring AI. New risks? New models?. And apologies for using this umbrella term, “AI,” which I do not like very much, but I need to simplify a little or I would never finish this post…
The day before yesterday, Thomas Claburn wrote in AI still doesn’t work very well in business, businesses are faking it, and a reckoning is coming:
Another looming problem is that large insurers have become wary of underwriting policies that cover companies against AI risk.
(Thanks to @flomaraninchi and @ugo for pointing it out to me.) I have the feeling that it is important to understand exactly what this means. If major insurers are becoming reluctant to cover AI-related uses, this is probably not just one more market anecdote, nor simply another legal precaution. It is a signal. An important signal for anyone who builds predictive models, or who is interested in uncertainty and ambiguity, because insurers do not need to be prophets to become cautious. Perhaps that is what risk culture is. It is enough for them to conclude that they do not understand the risk well enough, that they cannot observe it properly, that they cannot reconstruct the chain of responsibility behind it, or that they doubt they can carry it at a sustainable price. In other words, if insurers are stepping back, that should force us to ask whether AI is really under control. What we are dealing with here are very classical questions in the economics of information, imperfect measurement, misaligned incentives, and insufficient proof, much more than a simple dispute about the current level of the technology.
Continue reading If No One Pays for Proof, Everyone Will Pay for the Loss