In defence of fanaticism
Hayden Wilkinson (Australian National University)
GPI Working Paper No. 4-2020, published in Ethics
Which is better: a guarantee of a modest amount of moral value, or a tiny probability of arbitrarily large value? To prefer the latter seems fanatical. But, as I argue, avoiding such fanaticism brings severe problems. To do so, we must (1) decline intuitively attractive trade-offs; (2) rank structurally identical pairs of lotteries inconsistently, or else admit absurd sensitivity to tiny probability differences;(3) have rankings depend on remote, unaffected events (including events in ancient Egypt); and often (4) neglect to rank lotteries as we already know we would if we learned more. Compared to these implications, fanaticism is highly plausible
Other working papers
AI takeover and human disempowerment – Adam Bales (Global Priorities Institute, University of Oxford)
Some take seriously the possibility of AI takeover, where AI systems seize power in a way that leads to human disempowerment. Assessing the likelihood of takeover requires answering empirical questions about the future of AI technologies and the context in which AI will operate. In many cases, philosophers are poorly placed to answer these questions. However, some prior questions are more amenable to philosophical techniques. What does it mean to speak of AI empowerment and human disempowerment? …
When should an effective altruist donate? – William MacAskill (Global Priorities Institute, Oxford University)
Effective altruism is the use of evidence and careful reasoning to work out how to maximize positive impact on others with a given unit of resources, and the taking of action on that basis. It’s a philosophy and a social movement that is gaining considerable steam in the philanthropic world. For example,…
Will AI Avoid Exploitation? – Adam Bales (Global Priorities Institute, University of Oxford)
A simple argument suggests that we can fruitfully model advanced AI systems using expected utility theory. According to this argument, an agent will need to act as if maximising expected utility if they’re to avoid exploitation. Insofar as we should expect advanced AI to avoid exploitation, it follows that we should expected advanced AI to act as if maximising expected utility. I spell out this argument more carefully and demonstrate that it fails, but show that the manner of its failure is instructive…