# Norms for Beneficial A.I.: A Computational Analysis of the Societal Value Alignment Problem

## TL;DR

This paper uses an agent-based game-theoretical model to analyze societal conflicts and benefits arising from A.I. adoption, highlighting the importance of regulation and ethical norms to balance individual gains and societal welfare.

## Contribution

It introduces a novel simulation framework to study the societal value alignment problem and demonstrates how regulation and ethical norms influence A.I. adoption outcomes.

## Key findings

- Selfish A.I. systems dominate without regulation.
- Human-conscious policies can promote equitable benefits.
- External regulation is necessary for ethical norm adoption.

## Abstract

The rise of artificial intelligence (A.I.) based systems is already offering substantial benefits to the society as a whole. However, these systems may also enclose potential conflicts and unintended consequences. Notably, people will tend to adopt an A.I. system if it confers them an advantage, at which point non-adopters might push for a strong regulation if that advantage for adopters is at a cost for them. Here we propose an agent-based game-theoretical model for these conflicts, where agents may decide to resort to A.I. to use and acquire additional information on the payoffs of a stochastic game, striving to bring insights from simulation to what has been, hitherto, a mostly philosophical discussion. We frame our results under the current discussion on ethical A.I. and the conflict between individual and societal gains: the societal value alignment problem. We test the arising equilibria in the adoption of A.I. technology under different norms followed by artificial agents, their ensuing benefits, and the emergent levels of wealth inequality. We show that without any regulation, purely selfish A.I. systems will have the strongest advantage, even when a utilitarian A.I. provides significant benefits for the individual and the society. Nevertheless, we show that it is possible to develop A.I. systems following human conscious policies that, when introduced in society, lead to an equilibrium where the gains for the adopters are not at a cost for non-adopters, thus increasing the overall wealth of the population and lowering inequality. However, as shown, a self-organised adoption of such policies would require external regulation.