2018· International Journal of Innovative Research in Humanities & Technology· 0 citations
TL;DR
It is suggested in the paper that a methodology of ethical governance based on principles of responsible AI should be structured, fairness-by-design, transparency, human-in-the-loop oversight, and constant impact assessment, which underscores the fact that AI systems have ethical failures that are seldom technical but rather socio-technical, which necessitate interventions at the policy, organizational governance, and technical design levels.
Abstract
AI has quickly ceased being a supporting computational device and has become a central decision-maker in various spheres of society, such as health care, finances, criminal justice, and government, education, and employment. Decision-making systems based on AI have an increasing impact on the outcomes that have significant ethical, legal, and social implications on society and individuals. Although these systems have efficacy, scalability, and objectiveness, they also introduce some essential ethical dilemmas associated with bias, fairness, transparency, accountability, privacy, autonomy, and social justice. The paper will be a systematic review of the ethical issues of AI-controlled decision-making in the society. The investigation is an interdisciplinary synthesis of the literature in the domain of computer science, philosophy, law, and social sciences in order to distinguish the major ethical hazards and novel normative structures. It analyzes the origin of algorithmic bias in data, structural model design and institutional conditions and how explainability and trust are endangered through the lack of transparency in complex machine learning models. Specific focus is made on the asymmetries of power that the AI implementation causes in which automated systems impact vulnerable and marginalized people unequally. It is suggested in the paper that a methodology of ethical governance based on principles of responsible AI should be structured, fairness-by-design, transparency, human-in-the-loop oversight, and constant impact assessment. The conceptual model of ethical risk assessment is presented to consider AI systems throughout its lifecycle, including data collection and after-deployment language. The findings underscore the fact that AI systems have ethical failures that are seldom technical but rather socio-technical, which necessitate interventions at the policy, organizational governance, and technical design levels. The paper highlights the necessity of ethical norms that are enforceable, interdisciplinary cooperation, and international harmonization of regulations to make sure that the decisions made by AI could be consistent with the basic human values. The paper ends by identifying the future research directions/decision-making, as well as determining the policy implications of transforming AI systems into trustworthy, accountable, and socially beneficial systems.
Artificial Intelligence (AI) is rapidly transforming judicial systems worldwide by enhancing the efficiency, consistency, and accessibility of legal decision-making. AI-powered technologies such as predictive analytics, natural language processing, legal research tools, and decision-support systems are increasingly being integrated into courts to reduce case backlogs, improve administrative efficiency, and assist judges in analyzing complex legal data. While these technological advancements offer significant benefits, they also raise important legal and ethical concerns regarding fairness, transparency, accountability, privacy, judicial independence, and algorithmic bias. Unlike conventional decision-making processes, AI systems often function through complex algorithms that may lack explainability, making it difficult to understand how judicial recommendations are generated. Such opacity challenges fundamental principles of due process, equality before the law, and the right to a fair trial. Furthermore, concerns regarding data protection, cybersecurity, discrimination, and the allocation of legal responsibility for AI-generated decisions have intensified debates among policymakers, legal scholars, and judicial institutions. This paper critically examines the legal and ethical dimensions of AI in judicial decision-making through a comparative analysis of emerging regulatory approaches in jurisdictions such as the European Union, the United States, China, and India. It explores the evolving role of AI as a judicial support mechanism while emphasizing that judicial discretion and constitutional values must remain central to legal adjudication. The study concludes that responsible AI governance requires transparent algorithms, human oversight, ethical safeguards, robust regulatory frameworks, and international cooperation to ensure that technological innovation strengthens rather than undermines the rule of law, judicial independence, and public confidence in the administration of justice.
Research Author· International Journal of Leg...· 0 citations
Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the twenty-first century, revolutionizing governance, healthcare, finance, education, criminal justice, employment, and public administration. AI-driven decision-making systems increasingly influence legal and administrative processes by automating decisions that affect individuals' rights and opportunities. While these technologies offer significant advantages in terms of efficiency, consistency, and innovation, they also raise serious legal and ethical concerns regarding algorithmic bias, discrimination, transparency, accountability, and the protection of fundamental rights. Algorithmic bias may arise from biased datasets, flawed design, or unequal representation, leading to discriminatory outcomes against individuals based on race, gender, ethnicity, disability, age, religion, or socio-economic status. Such outcomes challenge the constitutional principle of equality before the law and undermine public confidence in automated decision-making systems. International organizations and national governments have responded by developing legal and ethical frameworks that promote fairness, transparency, explainability, and human oversight in AI governance. This paper critically examines the relationship between artificial intelligence, algorithmic bias, and equality before the law through an analysis of international legal standards, comparative constitutional principles, judicial developments, and emerging regulatory approaches. It further evaluates contemporary challenges associated with AI governance and proposes legal reforms aimed at ensuring responsible, transparent, and non-discriminatory deployment of artificial intelligence while safeguarding human dignity, equality, and the rule of law in an increasingly digital society.
Research Author· European Journal of Law, Int...· 0 citations
Many studies involving the effects of unethical AI on humans center around life-or-death situations. While there are benefits in examining unambiguously unethical AI, the everyday person does not encounter these extreme situations. More commonly, large language models (LLMs) may give unethical advice to its users, and the effects of this are not well studied. Furthermore, there does not exist a task to assess the impact of unethical AI advice in lower stakes settings. For this study, we designed a decision-making task in the context of supply delivery to remote outposts. We then systematically created 54 vignettes consisting of financial risk and ethical risk vignettes and had participants (
N
= 59) rate them on the levels of financial and ethical risk. We ended with 50 vignettes total (23 financial, 27 ethical) that were differentiated on these risks, and demonstrated how they can be organized into matched sets for repeated measures studies.
Irene Y. Feng, Gerald Matthews· Proceedings of the Human Fac...· 0 citations
A Multi-Layer Social-Theoretical AI Ethics Framework (MLST-AEF) that integrates normative ethical reasoning, stakeholder analysis, institutional context, bias and power assessment, and structured decision support is developed.
M. Fakrudeen, J. Otieno· AI and Ethics· 0 citations
Artificial Intelligence (AI) and digital technologies have become integral to modern society, transforming healthcare, education, finance, governance, transportation, business, and communication. While these technologies improve efficiency, innovation, and decision-making, they also raise significant ethical issues, privacy concerns, and challenges related to public trust. The increasing use of AI-driven systems for data collection, facial recognition, predictive analytics, automated decision-making, and surveillance has intensified concerns regarding data security, algorithmic bias, transparency, accountability, discrimination, and individual privacy rights. This study assesses the ethical issues, privacy concerns, and public trust associated with Artificial Intelligence and digital technologies. It examines how responsible AI development, ethical governance, privacy protection, transparency, fairness, and regulatory compliance influence public acceptance and confidence in intelligent systems. The study further explores the role of governments, technology companies, educational institutions, policymakers, and civil society in promoting ethical AI practices and safeguarding personal information. Additionally, it highlights the importance of digital literacy, informed consent, cybersecurity measures, explainable AI, and human oversight in reducing privacy risks and strengthening public trust. The study concludes that sustainable adoption of Artificial Intelligence depends not only on technological advancement but also on ethical responsibility, legal accountability, transparent governance, and respect for fundamental human rights. Building trustworthy AI ecosystems requires collaborative efforts among all stakeholders to ensure that technological innovation benefits society while protecting privacy, promoting fairness, and supporting inclusive and responsible digital transformation.
Research Author· Global Journal of Computing...· 0 citations
In recent years, the term “artificial intelligence” (AI) has become ubiquitous, sparking wide-ranging discussions among scientists, policymakers, and practitioners across multiple fields. AI has the potential to revolutionize nearly all sectors by enhancing transparency, accountability, and decision-making. However, like any powerful technology, it can be used for both beneficial and harmful purposes. While AI creates unprecedented opportunities, it also introduces significant risks that can negatively affect individuals and society. These risks include systematic bias, digital exclusion, misuse by authoritarian actors, loss of privacy, discrimination, arbitrary detention, disinformation, election manipulation, mass surveillance, as well as concerns around human rights protection, safety, liability, security, and fairness. Given these profound implications, effective regulation of AI has become essential. Two emerging regulatory frameworks – the Fundamental Rights Impact Assessment (FRIA) under the European Union AI Act and the Human Rights Due Diligence for AI (HUDERIA) – seek to address this need by embedding fundamental rights considerations into corporate AI governance. FRIA, as a mandatory assessment mechanism, requires companies to proactively identify and mitigate AI-related human rights risks. In contrast, HUDERIA offers a voluntary framework aligned with broader ethical principles. However, the coexistence of these approaches remains fragmented, raising concerns about inconsistent corporate compliance and enforcement. The article examines how the ongoing debate over the horizontal application of human rights in AI governance is shaping corporate responsibilities. It argues that a unified AI governance framework integrating FRIA and HUDERIA could not only enhance regulatory compliance but also catalyse a strategic shift in corporate approaches to fundamental rights.
N. Mushak, V. Muraviov, M. Jackowski· Reality of Politics· 0 citations
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