Vol. 1 No. 1 (2021): Journal of AI-Assisted Scientific Discovery
Articles

Artificial Intelligence and Unintended Bias: A Call for Responsible Innovation

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  • Dhruvitkumar V. Talati
Dhruvitkumar V. Talati
Independent Researcher, USA
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Published 04-01-2021

Keywords

  • artificial intelligence,
  • prejudice,
  • algorithmic fairness,
  • ethical AI
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

This essay discusses the intricate and multifaceted problem of algorithmic bias in artificial intelligence (AI) systems, and emphasizes its human rights, social, and ethical implications. As AI technologies become increasingly embedded in high-stakes areas of medicine, finance, employment, law enforcement, and social services, risks of discriminatory decision-making remain on the rise. Algorithmic bias may perpetuate existing social biases, adversely affect disadvantaged populations disproportionately, and perpetuate institutional discrimination, and thereby pose serious ethical issues.

The research endeavors to present an extensive comprehension of algorithmic bias through exploration of its cause, mechanism, and societal aspects. It exhaustively analyzes the presence of bias in AI systems, its cause-running from biased input data to defective algorithmic development, as well as the ethical aspects brought by having AI-based decisions influence real-world repercussions. In addition, the study analyzes material and immaterial effects of AI bias on persons and groups and aims at fairness, transparency, and accountability of AI in particular.

In its attempt to deal with these issues, this paper analyzes some measures to mitigate against bias, for instance, technical measures such as bias-aware algorithms, fairness-aware machine learning algorithms, and explainable AI methodologies. Furthermore, it speaks to normative and regulatory regimes that enable responsible AI deployment, as well as grass-roots strategies that enable affected communities to participate in AI stewardship. Through the use of the best of an interdisciplinary approach, the study integrates findings from peer-reviewed literature, international case studies, government policy, and industry standards to provide a comprehensive perspective on the issue.

Finally, the paper emphasizes the need for active, multi-stakeholder responses that make sure AI technologies conform to basic human rights and moral principles. In incorporating technical, ethical, legal, and social considerations into AI, the research demands more inclusive and accountable AI system that maximizes fairness, minimizes disparities, and secures human dignity in the modern fast-changing world of artificial intelligence.

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