  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.
