Yuan, Di
(2023)
Artificial Intelligence, Fairness and Productivity.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The widespread integration of advanced AI systems into business activities has substantially transformed how markets operate. AI in the workplace holds immense potential to enhance productivity and revolutionize how knowledge is disseminated among employees. While the benefits of AI are clear, there are still concerns about its use, particularly in terms of fairness and productivity, creating challenges for policymakers and businesses alike as they seek to ensure that the benefits of AI are shared fairly across society. One issue is that AI adoption can lead to unintended consequences that conflict with fairness. For example, in online advertising, AI has enabled advertisers to target users with greater precision than ever before, leading to concerns about discrimination and the potential for bias. Another issue is that AI may not always lead to expected productivity gains. While AI has the potential to drive productivity and economic growth, it is important to recognize that it may also affect the motivation of the workforce.
To address these concerns, my research examines the economic incentives associated with AI adoption and explores potential remedies to mitigate the associated side effects. Through game theoretical models, my research concludes that the disparity in online advertising display may not necessarily stem from purposeful discrimination on the part of advertisers or algorithmic bias, but rather, may arise from the characteristics of ad-auctions. Furthermore, the study highlights that introducing AI in the workplace may result in undesired consequences if firms do not consider the impact of AI on employees' motivations. Using research findings, we formulate recommendations for policies that can prevent negative outcomes and optimize the benefits of AI implementation. These policy suggestions may include promoting fairness in advertising and redesigning reward schemes.
Overall, this paper aims to provide insights into how organizations can adopt AI efficiently while ensuring fairness and productivity. By understanding the potential pitfalls of AI and the economic incentives of stakeholders affected by AI, policymakers and business owners can develop strategies that maximize the benefits of AI while minimizing its risks.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
29 June 2023 |
| Date Type: |
Publication |
| Defense Date: |
19 April 2023 |
| Approval Date: |
29 June 2023 |
| Submission Date: |
31 May 2023 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
142 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Joseph M. Katz Graduate School of Business > Management of Information Systems |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Artificial Intelligence, Algorithm, Fair Advertising, Algorithmic Fairness, Productivity, Pay-for-performance, Human Capital Management |
| Date Deposited: |
29 Jun 2023 15:52 |
| Last Modified: |
29 Jun 2023 15:52 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/44918 |
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