Ethical considerations in AI design and deployment

Prajapati, Sameerkumar Babubhai (2025) Ethical considerations in AI design and deployment. World Journal of Advanced Research and Reviews, 25 (1). pp. 2166-2173. ISSN 2581-9615

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Abstract

The more artificial intelligence (AI) becomes part of industries and societies, the more it has become necessary to think about ethics for its design and deployment. The purpose of this white paper is to explore the key ethical challenges of AI systems and data-centric ontology models with which decisions are made, as well as opportunities for realigning the development of AI with human values. Algorithms involved in making decisions in different settings are discussed, as well as ethical concerns such as algorithmic bias, transparency, privacy and accountability, as well as how improper use of AI can harm fairness, human autonomy and trust in automated systems. The paper then explores important challenges including AI paradoxes in consumer markets where AI systems increase as well as exploit consumers and the ethically problematic questions arising from use of AI in business decisions most notably in the financial sector. We will also analyze how these ethical concerns play out in real world use cases in the practical industry starting from AI applications related to customer service, healthcare etc. and financial services. The paper also shares actionable best practices for the ethical development and deployment of AI. There’s implementing fairness-aware algorithms, increasing the degree of transparency in the decision-making process, and having regulators help guide the responsible adoption of AI. The aim of this exploration is to provide actionable insights to practitioners, researchers and policymakers on developing an ethical roadmap for AI with a goal of maximizing its benefits and mitigating its risks

Item Type: Article
Official URL: https://doi.org/10.30574/wjarr.2025.25.1.0270
Uncontrolled Keywords: Ethical AI; Bias; Fairness; Transparency; Accountability; Inclusivity; Regulation; AI Frameworks; Data Privacy; Stakeholder Collaboration
Depositing User: Editor WJARR
Date Deposited: 11 Jul 2025 17:00
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/440