DeepAI AI Chat
Log In Sign Up

On Modeling Human Perceptions of Allocation Policies with Uncertain Outcomes

03/10/2021
by   Hoda Heidari, et al.
0

Many policies allocate harms or benefits that are uncertain in nature: they produce distributions over the population in which individuals have different probabilities of incurring harm or benefit. Comparing different policies thus involves a comparison of their corresponding probability distributions, and we observe that in many instances the policies selected in practice are hard to explain by preferences based only on the expected value of the total harm or benefit they produce. In cases where the expected value analysis is not a sufficient explanatory framework, what would be a reasonable model for societal preferences over these distributions? Here we investigate explanations based on the framework of probability weighting from the behavioral sciences, which over several decades has identified systematic biases in how people perceive probabilities. We show that probability weighting can be used to make predictions about preferences over probabilistic distributions of harm and benefit that function quite differently from expected-value analysis, and in a number of cases provide potential explanations for policy preferences that appear hard to motivate by other means. In particular, we identify optimal policies for minimizing perceived total harm and maximizing perceived total benefit that take the distorting effects of probability weighting into account, and we discuss a number of real-world policies that resemble such allocational strategies. Our analysis does not provide specific recommendations for policy choices, but is instead fundamentally interpretive in nature, seeking to describe observed phenomena in policy choices.

READ FULL TEXT

page 1

page 2

page 3

page 4

02/27/2013

Some Properties of Joint Probability Distributions

Several Artificial Intelligence schemes for reasoning under uncertainty ...
12/21/2020

Off-Policy Optimization of Portfolio Allocation Policies under Constraints

The dynamic portfolio optimization problem in finance frequently require...
08/07/2018

Evolution of Preferences in Multiple Populations

We study the evolution of preferences and the behavioral outcomes in an ...
03/05/2021

The Effect of Behavioral Probability Weighting in a Simultaneous Multi-Target Attacker-Defender Game

We consider a security game in a setting consisting of two players (an a...
12/18/2015

Learning the Preferences of Ignorant, Inconsistent Agents

An important use of machine learning is to learn what people value. What...
07/04/2020

Characterizing Online Vandalism: A Rational Choice Perspective

What factors influence the decision to vandalize? Although the harm is c...
07/07/2020

Skeptic: Automatic, Justified and Privacy-Preserving Password Composition Policy Selection

The choice of password composition policy to enforce on a password-prote...