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Ensuring trustworthy AI for sensitive infrastructure using Knowledge Representation

Year: 2024

Type: conference-paper

Abstract: Artificial intelligence (AI) has become increasingly integrated into various aspects of society, from healthcare and finance to law enforcement and hiring processes. More recently, sensitive infrastructure such as nuclear plants is engaging AI in aspects of safety. However, these systems are not immune to biases and ethical concerns. This paper explores the role of knowledge representation in addressing ethics and fairness in AI, examining how biased or incomplete representations can lead to unfair outcomes and unreliable decision-making. It proposes strategies to mitigate these risks.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17801633

Authors: Oumayma, Mejri, Waedt, Karl, Yatagha, Romarick, Eden, Natascha, Sebastiao, Claudia Lemos

Institution: Framatome (Germany)

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7108476151

FWCI:

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