The Manifestation and Implications of Bias in Artificial Intelligence on Global Society

Author(s)	Aarav Singh
Country	India
Abstract	Although artificial intelligence (AI) is becoming more and more prevalent, biases from data, algorithms, and feedback loops might still exist. Marginalized groups may be disproportionately affected by these biases, which may result in biased outcomes in areas such as facial recognition, credit scoring, and hiring. Reduced trust, sustained societal inequality, and stifled innovation are some of the effects. It is critical to support transparent development processes, diverse development teams, and ethical oversight in AI design in order to lessen these effects. If these issues are resolved, AI will become a more equitable instrument for advancing society.
Keywords	Artificial Intelligence (AI), bias, algorithmic bias, data bias, feedback loops, discrimination, facial recognition, fairness, diversity, ethics, transparency, societal impact, AI development, inclusive teams, algorithmic transparency, ethical AI.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-08
Cite This	The Manifestation and Implications of Bias in Artificial Intelligence on Global Society - Aarav Singh - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.28477
DOI	https://doi.org/10.36948/ijfmr.2024.v06i05.28477
Short DOI	https://doi.org/g79432

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research