Automation and Task Allocation Under Asymmetric Information

TL;DR

This paper examines how private information of workers influences a firm's task allocation mechanisms and shows that the nature of information frictions significantly affects whether tasks act as substitutes or complements, impacting automation and surplus.

Contribution

It provides a theoretical analysis of task allocation under asymmetric information, highlighting qualitative differences based on the level of information frictions and extending to competitive firm settings.

Findings

Small frictions lead to task substitution and reduced worker surplus.

Large frictions cause tasks to become complements, increasing worker surplus.

Automation impacts vary significantly depending on the level of information asymmetry.

Abstract

A firm can complete the tasks needed to produce output using either machines or workers. Unlike machines, workers have private information about their preferences over tasks. I study how this information asymmetry shapes the mechanism used by the firm to allocate tasks across workers and machines. I identify important qualitative differences between the mechanisms used when information frictions are large versus small. When information frictions are small, tasks are substitutes: automating one task lowers the marginal cost of other tasks and reduces the surplus generated by workers. When frictions are large, tasks can become complements: automation can raise the marginal cost of other tasks and increase the surplus generated by workers. The results extend to a setting with multiple firms competing for workers.