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Ethical Concerns Around AI Require Greater Scrutiny, Say Experts

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Ethical Concerns Around AI Require Greater Scrutiny, Say Experts

by Geraldine S.
12/20/2024
in Artificial Intelligence in Trade

Experts are raising concerns about the ethical implications of Artificial Intelligence (AI) and its broader societal impact, emphasizing the need for greater scrutiny and regulation.

“We are currently in an AI hype cycle, with limited empirical evidence showing how it addresses critical societal and developmental challenges,” said Prof. Amit Prakash, head of the Department of Digital Humanities and Societal Systems (DHSS) at the International Institute of Information Technology – Bangalore (IIIT-B). He pointed out that the perceived benefits of AI and Large Language Models (LLMs) often rely on conjectures rather than solid, ground-level evidence, particularly for marginalized communities.

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Prakash highlighted key issues, including the sourcing of data, robust consent mechanisms, and potential copyright infringement in training generative AI models. While international organizations like UNESCO and professional bodies such as IEEE have issued ethical AI guidelines, he noted that institutional mechanisms to enforce these principles are still in their early stages.

In India, the implementation of the Digital Personal Data Protection (DPDP) Act, 2023, is still pending, leaving a gap in the regulatory framework. Prakash stressed the importance of addressing these ethical questions to ensure transparency and accountability in AI development and deployment.

Critiquing the broad claims about AI’s potential benefits, Prakash questioned its ability to resolve deeply entrenched issues such as maternal health, child malnutrition, and the functioning of primary health centers in rural areas. He argued that these areas require people-focused policies that are yet to be integrated into AI strategies.

“The fascination with AI seems to stem from a centralized, top-down approach, often overlooking critical questions about the sources and use of data,” he added. “Technologies aimed at aiding marginalized communities should undergo stringent regulatory oversight, and the same should apply to AI and LLMs.”

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