Artificial Intelligence Development Races in Heterogeneous Settings

TL;DR

This paper explores how different interaction structures among AI developers influence race dynamics and regulatory needs, highlighting the role of network heterogeneity and inequality in shaping collective outcomes and governance strategies.

Contribution

It introduces a game-theoretical model to analyze AI development races in heterogeneous interaction networks, revealing how diversity reduces conflicts and informs targeted regulation.

Findings

Heterogeneous networks lessen conflicts compared to homogeneous settings.

Patent and economic inequality can be leveraged for effective regulation.

Targeted interventions on key participants can promote ethical AI development.

Abstract

Regulation of advanced technologies such as Artificial Intelligence (AI) has become increasingly important, given the associated risks and apparent ethical issues. With the great benefits promised from being able to first supply such technologies, safety precautions and societal consequences might be ignored or shortchanged in exchange for speeding up the development, therefore engendering a racing narrative among the developers. Starting from a game-theoretical model describing an idealised technology race in a fully connected world of players, here we investigate how different interaction structures among race participants can alter collective choices and requirements for regulatory actions. Our findings indicate that, when participants portray a strong diversity in terms of connections and peer-influence (e.g., when scale-free networks shape interactions among parties), the conflicts that exist in homogeneous settings are significantly reduced, thereby lessening the need for regulatory actions. Furthermore, our results suggest that technology governance and regulation may profit from the world's patent heterogeneity and inequality among firms and nations, so as to enable the design and implementation of meticulous interventions on a minority of participants, which is capable of influencing an entire population towards an ethical and sustainable use of advanced technologies.