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Monetization could corrupt algorithmic explanations
期刊文章

Monetization could corrupt algorithmic explanations

T. Greene, S. Goethals, D. Martens 和 G. Shmueli
AI and Society, 卷.40(8), 頁碼.6291-6308
2025

摘要

Advertising AI ethics Data monetization Digital platforms Explainable AI (XAI) Personalization Advertizing AI ethic Algorithmics Automated decision making Data monetization Digital platforms Explainable AI (XAI) Personalizations Pressure changing Regulatory pressure Ethical technology
Explainable artificial intelligence (XAI) aims to provide insights into the logic of automated decisions with the goal of promoting fairer, more transparent, and more trustworthy automated decision-making. Despite mounting regulatory pressure, changing consumer expectations, and a growing stream of XAI-related research, few consumer-facing applications of XAI exist. In anticipation of future XAI-enabled products and services, we use ethical foresight analysis to investigate the possible consequences of monetizing explanations. By developing a conceptual artifact we call an explanation platform, we analyze what could happen when digital advertising is fused with XAI. We explore the platform’s business and design logic, examine its potential social and ethical impact, and describe several plausible explanation manipulation scenarios and strategies. We find that while XAI monetization could incentivize industry adoption of XAI technology and expand algorithmic recourse across society, it could also lead to corrupted forms of explanations optimized for profit-driven objectives. Overall, our foresight analysis makes the case for the economic and technological feasibility of monetized XAI, but raises concerns about its desirability in liberal democratic societies. © The Author(s) 2025.

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https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004739743&doi=10.1007%2fs00146-025-02352-4&partnerID=40&md5=c25e99630939d7b5c9e86deaadb38b5b檢視
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https://doi.org/10.1007/s00146-025-02352-4檢視
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