Perceptions of AI engaging in human expression

Author:

Bower Alexander H.,Steyvers Mark

Abstract

AbstractThough humans should defer to the superior judgement of AI in an increasing number of domains, certain biases prevent us from doing so. Understanding when and why these biases occur is a central challenge for human-computer interaction. One proposed source of such bias is task subjectivity. We test this hypothesis by having both real and purported AI engage in one of the most subjective expressions possible: Humor. Across two experiments, we address the following: Will people rate jokes as less funny if they believe an AI created them? When asked to rate jokes and guess their likeliest source, participants evaluate jokes that they attribute to humans as the funniest and those to AI as the least funny. However, when these same jokes are explicitly framed as either human or AI-created, there is no such difference in ratings. Our findings demonstrate that user attitudes toward AI are more malleable than once thought—even when they (seemingly) attempt the most fundamental of human expressions.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference34 articles.

1. Dawes, R. M., Faust, D. & Meehl, P. E. Clinical versus actuarial judgment. Science 243, 1668–1674 (1989).

2. Grove, W. M., Zald, D. H., Lebow, B. S., Snitz, B. E. & Nelson, C. Clinical versus mechanical prediction: A meta-analysis. Psychol. Assess. 12, 19–30 (2000).

3. Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J. & Mullainathan, S. Human decisions and machine predictions. Q. J. Econ. 133, 237–293 (2018).

4. Burton, J. W., Stein, M.-K. & Jensen, T. B. A systematic review of algorithm aversion in augmented decision making. J. Behav. Decis. Mak. 33, 220–239 (2020).

5. Jussupow, E., Benbasat, I. & Heinzl, A. Why are we averse towards algorithms? A comprehensive literature review on algorithm aversion. In Proceedings of the 28th European Conference on Information Systems (2020).

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3