Measuring AI-Driven Risk with Stock Prices
Susana Campos-Martins (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 31-2024
We propose an empirical approach to identify and measure AI-driven shocks based on the co-movements of relevant financial asset prices. For that purpose, we first calculate the common volatility of the share prices of major US AI-relevant companies. Then we isolate the events that shake this industry only from those that shake all sectors of economic activity at the same time. For the sample analysed, AI shocks are identified when there are announcements about (mergers and) acquisitions in the AI industry, launching of new products, releases of new versions, and AI-related regulations and policies.
Other working papers
Exceeding expectations: stochastic dominance as a general decision theory – Christian Tarsney (Global Priorities Institute, Oxford University)
The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal’s Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls…
Evolutionary debunking and value alignment – Michael T. Dale (Hampden-Sydney College) and Bradford Saad (Global Priorities Institute, University of Oxford)
This paper examines the bearing of evolutionary debunking arguments—which use the evolutionary origins of values to challenge their epistemic credentials—on the alignment problem, i.e. the problem of ensuring that highly capable AI systems are properly aligned with values. Since evolutionary debunking arguments are among the best empirically-motivated arguments that recommend changes in values, it is unsurprising that they are relevant to the alignment problem. However, how evolutionary debunking arguments…
In Defence of Moderation – Jacob Barrett (Vanderbilt University)
A decision theory is fanatical if it says that, for any sure thing of getting some finite amount of value, it would always be better to almost certainly get nothing while having some tiny probability (no matter how small) of getting sufficiently more finite value. Fanaticism is extremely counterintuitive; common sense requires a more moderate view. However, a recent slew of arguments purport to vindicate it, claiming that moderate alternatives to fanaticism are sometimes similarly counterintuitive, face a powerful continuum argument…