Gil Hersch: Queuing is Scarcely Better than a Lottery
When there are no morally relevant differences between individuals, a 'first come, first served' allocation mechanism for goods is often a more efficient, more equitable, and a fairer allocation mechanism than lotteries, argue Tyler John and Joseph Millum. While John and Millum set aside the discussion of the type of good to be allocated, from a moral perspective the most pressing cases are those in which the allocated good is scarce, meaning not everyone can get one, no matter how long they wait. When the good is actually scarce, the allocation mechanism must determine not only the order in which a good is allocated but, more importantly, who will get the good and who will not. Dr. Hersch argues that for cases that involve scarce goods, lotteries are both a fairer allocative mechanism that 'first come, first served' and a no less efficient one.
Dr. Gil Hersch is an Assistant Professor at the Virginia Tech Department of Philosophy and the Program in Philosophy, Politics, and Economics. He specializes in ethical issues at the intersection of economics, business, and policy, especially as they relate to happiness and well-being. His research examines the relationship between philosophical theories of well-being and the variety of well-being measures available in the social sciences, and the implications this relationship can have for public policy.
While agreement on what measures represent well-being as philosophers think of it might be unattainable, Dr. Hersch argues that some agreement can be reached when treating well-being measurement as a practical problem for guiding public policy.
The Virginia Tech Center for Humanities presents a series of talks by faculty research associates who will discuss their work. This talk is free and open to the public and we invite anyone to attend. There will be a brief Q and A with viewers following the presentation. If you are an individual with a disability and desire an accommodation, please contact the Center for Humanities at 540.231.1981 or email email@example.com at least 10 business days prior to the event.