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This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
HAI Weekly Seminar
One unsolved problem in democratic theory is how we can reconcile the twin goals of quality deliberation and mass participation. Both are arguably conditions for the full legitimacy of a democratic system. Quality deliberation, as a process through which laws and policies are generated, in theory promises good governance (output-legitimacy) as well as, at the very least, good reasons for the laws and policies put forward. Mass participation, by contrast, is a condition for the democratic input-legitimacy of the system, namely its capacity to take into account people’s needs and preferences. Unfortunately, thus far, it has proven impossible to reconcile those two goals as the quality of deliberation diminishes past a relatively low threshold of participants (a few hundreds, perhaps a few thousand people) and mass participation, on the other hand, is not conducive to the thoughtful, informed exchanges smaller numbers afford. In this presentation, Hélène Landemore explores the ways in which Artificial Intelligence may help bridge that gap, at least up to a point.
Hélène LandemoreProfessor of Political Science, Yale University
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