Competition Alleviates Present Bias in Task Completion

TL;DR

This paper demonstrates that introducing competition among present biased agents can reduce their tendency to take overly costly paths, improving task completion outcomes in various settings.

Contribution

It models competition in present bias scenarios, showing that even minimal competition can mitigate the negative effects of present bias on task performance.

Findings

Competition can significantly reduce the cost of paths chosen by biased agents.

A small amount of competition often suffices to improve outcomes for present biased agents.

The results suggest designing competitive environments can protect biased agents from poor decisions.

Abstract

We build upon recent work [Kleinberg and Oren, 2014, Kleinberg et al., 2016, 2017] that considers present biased agents, who place more weight on costs they must incur now than costs they will incur in the future. They consider a graph theoretic model where agents must complete a task and show that present biased agents can take exponentially more expensive paths than optimal. We propose a theoretical model that adds competition into the mix -- two agents compete to finish a task first. We show that, in a wide range of settings, a small amount of competition can alleviate the harms of present bias. This can help explain why biased agents may not perform so poorly in naturally competitive settings, and can guide task designers on how to protect present biased agents from harm. Our work thus paints a more positive picture than much of the existing literature on present bias.