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Cognitive Bias and Fairness Challenges in AI Consciousness

Cognitive Bias and Fairness Challenges in AI Consciousness

Ashwini P., Prabir Chandra Padhy
Copyright: © 2024 |Pages: 21
ISBN13: 9798369320150|ISBN13 Softcover: 9798369349021|EISBN13: 9798369320167
DOI: 10.4018/979-8-3693-2015-0.ch005
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MLA

P., Ashwini, and Prabir Chandra Padhy. "Cognitive Bias and Fairness Challenges in AI Consciousness." Comparative Analysis of Digital Consciousness and Human Consciousness: Bridging the Divide in AI Discourse, edited by Remya Lathabhavan and Nidhi Mishra, IGI Global, 2024, pp. 89-109. https://doi.org/10.4018/979-8-3693-2015-0.ch005

APA

P., A. & Padhy, P. C. (2024). Cognitive Bias and Fairness Challenges in AI Consciousness. In R. Lathabhavan & N. Mishra (Eds.), Comparative Analysis of Digital Consciousness and Human Consciousness: Bridging the Divide in AI Discourse (pp. 89-109). IGI Global. https://doi.org/10.4018/979-8-3693-2015-0.ch005

Chicago

P., Ashwini, and Prabir Chandra Padhy. "Cognitive Bias and Fairness Challenges in AI Consciousness." In Comparative Analysis of Digital Consciousness and Human Consciousness: Bridging the Divide in AI Discourse, edited by Remya Lathabhavan and Nidhi Mishra, 89-109. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-2015-0.ch005

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Abstract

As artificial intelligence (AI) continues to permeate various facets of our lives, the intersection of cognitive bias and fairness emerges as a critical concern. This chapter explores the intricate relationship between cognitive biases inherent in AI systems and the pursuit of fairness in their decision-making processes. The evolving landscape of AI consciousness demands a nuanced understanding of these challenges to ensure ethical and unbiased deployment. The presence of cognitive biases in AI systems reflects the data they are trained on. Developing universal standards for fairness that can adapt to diverse contexts remains an ongoing challenge. In conclusion, cognitive bias and fairness in AI consciousness demand a holistic and multidisciplinary approach. Addressing these issues necessitates collaboration between researchers, ethicists, policymakers, and industry. Developing transparent, adaptive, and universally accepted standards for fairness in AI is essential to ensure the responsible and ethical deployment of these technologies in our increasingly interconnected world.

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