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Legitimizing Ai: Ethical Ai in Corporate Ethics Statements

Authors: Jiali Zhang; Eyun-Jung Ki; Qinxian Cai;

Legitimizing Ai: Ethical Ai in Corporate Ethics Statements

Abstract

Purpose As global businesses increasingly focus on AI governance, more companies have communicated their commitment to ethical AI practices through corporate AI ethics statements. Drawing on the legitimacy framework, this study investigates how these statements serve as mechanisms to align organizational AI practices with stakeholder expectations, establish ethical benchmarks, and deploy strategic legitimation cues. Design/methodology/approach A quantitative content analysis was conducted on 2024 Fortune Global 500 and Forbes AI 50 companies' AI ethics statements. Findings Findings reveal that explainability, safety, and justice are widely recognized as key ethical AI standards in corporate AI ethics statements. The statements frequently address customers and employees as primary stakeholders, emphasizing explainability and privacy for customers and safety, explainability, and accountability for employees. Substantive cues are more prevalent than symbolic cues in legitimizing these ethical AI standards. Originality/value This study provides an evidence-based legitimacy framework for communicating corporate AI ethics, underscoring the need to align corporate AI practices with universal AI ethics and stakeholder expectations to build stakeholder trust. It offers valuable insights for corporate management and communication professionals for developing and evaluating corporate AI ethics statements.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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