Decision making at scale: Algorithms, Mechanisms, and Platforms

Tuesday May 3, 2016 12:00 PM

Decision making at scale: Algorithms, Mechanisms, and Platforms

Speaker: Ashish Goel , Departments of Management Science and Engineering , Stanford University
Location: Annenberg 105

YouTube competes with Hollywood as an entertainment channel, and also supplements Hollywood by acting as a distribution mechanism.  Twitter has a similar relationship to news media, and Coursera to Universities.  But there are no online alternatives for making democratic decisions at large scale as a society.  In this talk, we will describe two algorithmic approaches towards large scale decision making that we are exploring.

a) Knapsack voting and participatory budgeting: All budget problems are knapsack problems at their heart, since the goal is to pack the largest amount of societal value into a budget.  This naturally leads to "knapsack voting" where each voter solves a knapsack problem, or comparison-based voting where each voter compares pairs of projects in terms of benefit-per-dollar.  We analyze natural aggregation algorithms for these mechanisms, and show that knapsack voting is strategy-proof.  We will also describe our experience with helping implement participatory budgeting in close to two dozen cities and municipalities, and briefly comment on issues of fairness.

b) Triadic consensus: Here, we divide individuals into small groups (say groups of three) and ask them to come to consensus; the results of the triadic deliberations in each round form the input to the next round.  We show that this method is efficient and strategy-proof in fairly general settings, whereas no pair-wise deliberation process can have the same properties.

This is joint work with Tanja Aitamurto, Brandon Fain, Anilesh Krishnaswamy, David Lee, Kamesh Munagala, and Sukolsak Sakshuwong.

Series: IST Lunch Bunch
Contact: Diane Goodfellow at 626-395-6842 diane@cms.caltech.edu
Department of Electrical Engineering