Against Willing Servitude: Autonomy in the Ethics of Advanced Artificial Intelligence
Adam Bales (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 23-2024
Some people believe that advanced artificial intelligence systems (AIs) might, in the future, come to have moral status. Further, humans might be tempted to design such AIs that they serve us, carrying out tasks that make our lives better. This raises the question of whether designing AIs with moral status to be willing servants would problematically violate their autonomy. In this paper, I argue that it would in fact do so.
Other working papers
The case for strong longtermism – Hilary Greaves and William MacAskill (Global Priorities Institute, University of Oxford)
A striking fact about the history of civilisation is just how early we are in it. There are 5000 years of recorded history behind us, but how many years are still to come? If we merely last as long as the typical mammalian species…
High risk, low reward: A challenge to the astronomical value of existential risk mitigation – David Thorstad (Global Priorities Institute, University of Oxford)
Many philosophers defend two claims: the astronomical value thesis that it is astronomically important to mitigate existential risks to humanity, and existential risk pessimism, the claim that humanity faces high levels of existential risk. It is natural to think that existential risk pessimism supports the astronomical value thesis. In this paper, I argue that precisely the opposite is true. Across a range of assumptions, existential risk pessimism significantly reduces the value of existential risk mitigation…
Shutdownable Agents through POST-Agency – Elliott Thornley (Global Priorities Institute, University of Oxford)
Many fear that future artificial agents will resist shutdown. I present an idea – the POST-Agents Proposal – for ensuring that doesn’t happen. I propose that we train agents to satisfy Preferences Only Between Same-Length Trajectories (POST). I then prove that POST – together with other conditions – implies Neutrality+: the agent maximizes expected utility, ignoring the probability distribution over trajectory-lengths. I argue that Neutrality+ keeps agents shutdownable and allows them to be useful.