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The neuroscientist who wants us to be nicer to psychopaths

New Scientist

Abigail Marsh has found that many psychopaths don't want to be cruel and uncaring, and argues that they deserve support to help them get there Think of a psychopath and you probably picture someone dangerous, someone whose ruthless self-interest leads to great harm for others and considerable success for themselves. Perhaps unsurprisingly, while only around 1 per cent of people in the general population have psychopathy, roughly 1 in 5 men in prison show signs of it, and research has also found a link between corporate leadership and psychopathic traits . But just as it is painful to know a psychopath, it isn't necessarily fun to be one either. Abigail Marsh, a professor of psychology and neuroscience at Georgetown University in Washington DC, studies those with psychopathic traits who largely lead ordinary lives among us. She has uncovered something surprising: many don't want to be psychopathic at all. Researchers are still honing the precise definition, but psychopathy is characterised by callousness, a lack of empathy, glib social charm and impulsivity.


Efficiency of the First-Price Auction in the Autobidding World

Neural Information Processing Systems

We study the price of anarchy of first-price auctions in the autobidding world, where bidders can be either utility maximizers (i.e., traditional bidders) or value maximizers (i.e., autobidders).



Group Fairness in Peer Review

Neural Information Processing Systems

Large conferences such as NeurIPS and AAAI serve as crossroads of various AI fields, since they attract submissions from a vast number of communities. However, in some cases, this has resulted in a poor reviewing experience for some communities, whose submissions get assigned to less qualified reviewers outside of their communities. An often-advocated solution is to break up any such large conference into smaller conferences, but this can lead to isolation of communities and harm interdisciplinary research.






Explainable and Efficient Randomized Voting Rules

Neural Information Processing Systems

With a rapid growth in the deployment of AI tools for making critical decisions (or aiding humans in doing so), there is a growing demand to be able to explain to the stakeholders how these tools arrive at a decision.