Endogenous AI-tocracy

52 Pages Posted: 30 Nov 2023

See all articles by Lu Bai

Lu Bai

Wuhan University

Lijia Wei

Wuhan University

Lian Xue

Wuhan University

Date Written: November 18, 2023

Abstract

"AI-tocracy" describes a potential governance form shaped by current societal trends and AI advancements (Beraja, Kao, Yang and Yuchtman, 2023). We conducted a series of controlled laboratory experiments to examine what AI-tocracy represents, how decision-makers perceive and respond to it, and why might resistance arise. We find four main results: (i) AI-generated social scores (AI-score) bundled with punitive measures significantly boost group cooperation, driving a 58% increase in contributions to group projects compared to when such a system is absent. (ii) Adoption is polarized. While 50% embrace AI, resulting in heightened cooperation, the remaining half resist, leading to subdued cooperative outcomes. (iii) Predominantly, individuals employ AI-scores to empower their judgments rather than allowing AI full decision-making autonomy, with a 1.3:1 ratio favoring empowerment over replacement. (iv) As decision-makers accrue experience, the chasm between AI predictions and the final human judgments narrows and eventually becomes indistinguishable. We conclude by forecasting AI-tocracy's potential trajectory in the forthcoming era.

Keywords: Artificial intelligence (AI); social score; public goods game.

JEL Classification: C92; D60; H41

Suggested Citation

Bai, Lu and Wei, Lijia and Xue, Lian, Endogenous AI-tocracy (November 18, 2023). Available at SSRN: https://ssrn.com/abstract=4636843 or http://dx.doi.org/10.2139/ssrn.4636843

Lu Bai (Contact Author)

Wuhan University ( email )

Wuhan, 430072
China

Lijia Wei

Wuhan University ( email )

Wuhan
China

Lian Xue

Wuhan University ( email )

Wuhan
China

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
63
Abstract Views
357
Rank
641,931
PlumX Metrics