Category: TheRAIN Recommended Read
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To be forgotten or to be fair: unveiling fairness implications of machine unlearning methods
Machine unlearning, a tool for RTBF (Right to be Forgotten), can impact AI fairness. This study explores two common methods (SISA, AmnesiacML) vs. retraining (ORTR) across fairness datasets and deletion strategies. Results show non-uniform deletion with SISA yields better fairness outcomes, while other methods have mixed effects. These findings inform…
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Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics
AI ethics toolkits promise guidance, but fall short! They lack support for navigating complex power dynamics within organizations, leaving practitioners unprepared to tackle real-world ethical challenges. Future toolkits need to address these issues for truly responsible AI development. Read article here >
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From ethical AI frameworks to tools: a review of approaches
AI ethics: Drowning in principles, lacking solutions. Many guidelines exist, but they’re too vague and don’t translate well to real-world AI. This analysis highlights the need for concrete methods and tools that address specific ethical issues beyond just “explainability, fairness, privacy, and accountability.” We need to move from principles to…
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The uselessness of AI ethics
AI ethics are drowning in a sea of ineffective principles. While guidelines abound, they’re often vague, ignored, and lack teeth, failing to address the real dangers of AI. We need better solutions! Instead of relying solely on principles, we must tackle systemic issues of oppression and prioritize rigorous accuracy checks.…
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AI Ethics: An Empirical Study on the Views of Practitioners and Lawmakers
AI ethics debate rages on! Survey reveals key concerns: transparency, accountability, privacy are top priorities, but challenges like lack of knowledge, regulation, and monitoring bodies hinder progress. Practitioners and lawmakers differ in their views on some principles and challenges. More research needed to bridge the gap and build ethical AI…
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Where is the human in human-centered AI? Insights from developer priorities and user experiences
HCAI aims to prioritize users, but a survey shows a gap between developers’ focus on tech and users’ valuing AI’s social impact and functionality. HCAI needs to bridge this gap by ensuring AI meets user needs and improves lives. Read article here >
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The blended future of automation and AI: Examining some long-term societal and ethical impact features
AI’s two faces: While its rapid growth creates new jobs in healthcare, transport, and more, concerns about job losses, dehumanization, and societal impact grow. This study delves into both sides, exploring its potential benefits and drawbacks for businesses, jobs, and the future of humanity. Read article here >
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The blended future of automation and AI: Examining some long-term societal and ethical impact features
AI’s rapid growth sparks debate on its societal impact. While creating opportunities in transportation, health, and more, concerns like job losses and dehumanization rise. This review explores AI’s potential benefits and drawbacks, analyzing its impact on businesses, jobs, and human well-being. Read the article >
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Where is the human in human-centered AI? Insights from developer priorities and user experiences
Human-centered AI (HCAI) aims to prioritize users, but a survey of developers and users reveals discrepancies in focus. While users value AI’s social impact and functionality, developers prioritize technical aspects and avoiding harm. HCAI needs to bridge this gap by ensuring AI meets user needs and improves their lives. Read…
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Using Artificial Intelligence to Address Criminal Justice Needs
AI is rapidly transforming everyday life, impacting everything from smartphones and cars to healthcare and finance. Its applications extend across various industries, including agriculture, education, and law enforcement. AI-powered systems help analyze data and predict outcomes, leading to improved efficiency and accuracy in various fields. Read article here >
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