Halt the use of facial-recognition technology until it is regulated

Author: Crawford, Kate Description: Until appropriate safeguards are in place, we need a moratorium on biometric technology that identifies individuals. Subject headings: Facial recognition; Biometric technology; Privacy; Ethics; Artificial intelligence; AI Publication year: 2019 Journal or book title: Nature Volume: 572 Issue: 7771 Pages: 565 Find the full text: https://www.nature.com/articles/d41586-019-02514-7 Find more like this one (cited by): https://scholar.google.com/scholar?cites=5918763303809055830&as_sdt=1000005&sciodt=0,16&hl=en Serial number: 4051

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The ethical application of biometric facial recognition technology

Author: Smith, Marcus; Miller, Seumas Description: Biometric facial recognition is an artificial intelligence technology involving the automated comparison of facial features, used by law enforcement to identify unknown suspects from photographs and closed circuit television. Its capability is expanding rapidly in association with artificial intelligence and has great potential to solve crime. However, it also carries significant privacy and other ethical implications that require law and regulation. This article examines the rise of biometric facial recognition, current applications and legal developments, and conducts an ethical analysis of the issues that…

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Facial Recognition Technology: Current Capabilities, Future Prospects, and Governance

Author: National Academies of Sciences, Engineering, and Medicine Description: Facial recognition technology is increasingly used for identity verification and identification, from aiding law enforcement investigations to identifying potential security threats at large venues. However, advances in this technology have outpaced laws and regulations, raising significant concerns related to equity, privacy, and civil liberties. This report explores the current capabilities, future possibilities, and necessary governance for facial recognition technology. Facial Recognition Technology discusses legal, societal, and ethical implications of the technology, and recommends ways that federal agencies and others developing and…

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The benefits, risks and bounds of personalizing the alignment of large language models to individuals

Author: Kirk, Hannah Rose; Vidgen, Bertie; Rottger, Paul; Hale, Scott A. Description: Large language models (LLMs) undergo ‘alignment’ so that they better reflect human values or preferences, and are safer or more useful. However, alignment is intrinsically difficult because the hundreds of millions of people who now interact with LLMs have different preferences for language and conversational norms, operate under disparate value systems and hold diverse political beliefs. Typically, few developers or researchers dictate alignment norms, risking the exclusion or under-representation of various groups. Personalization is a new frontier in…

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Why human-AI relationships need socioaffective alignment

Author: Kirk, Hannah Rose; Gabriel, Iason; Summerfield, Chris; Vidgen, Bertie; Hale, Scott A. Description: Humans strive to design safe AI systems that align with our goals and remain under our control. However, as AI capabilities advance, we face a new challenge: the emergence of deeper, more persistent relationships between humans and AI systems. We explore how increasingly capable AI agents may generate the perception of deeper relationships with users, especially as AI becomes more personalised and agentic. This shift, from transactional interaction to ongoing sustained social engagement with AI, necessitates…

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One is the loneliest number … Two can be as bad as one. The influence of AI Friendship Apps on users’ well-being and addiction

Author: Marriott, Hannah R.; Pitardi, Valentina Description: Although technology advancements provide opportunities for social interactions, reports show that people have never felt so alone and are increasingly adopting AI friendship and therapy-related well-being apps. By adopting a mixed-method approach (i.e., netnography and quantitative survey), we investigate the extent AI friendship apps enhance users’ well-being–and to what extent they further exacerbate issues of using technology for social needs. Findings show that users of AI friendship apps report well-being benefits from the relationship with the AI friend and, at the same time,…

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Artificial Intelligence, Trust, and Perceptions of Agency

Author: Vanneste, Bart S.; Puranam, Phanish Description: Modern artificial intelligence (AI) technologies based on deep learning architectures are often perceived as agentic to varying degrees–typically, as more agentic than other technologies but less agentic than humans. We theorize how different levels of perceived agency of AI affect human trust in AI. We do so by investigating three causal pathways. First, an AI (and its designer) perceived as more agentic will be seen as more capable, and therefore will be perceived as more trustworthy. Second, the more the AI is perceived…

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Risks and Benefits of AI-generated Text Summarization for Expert Level Content in Graduate Health Informatics

Author: Merine, Regina; Purkayastha, Saptarshi Description: AI-generated text summarization (AI-GTS) is now a popular topic in applied computer science education. It has proven helpful in various sectors, but its benefits and risks in education have not been thoroughly investigated. Few researchers have demonstrated the benefits of employing AI-generated text summaries in learning to generate ideas swiftly and to explore insights and hidden knowledge. AI-GTS has made it easier for students to understand electronically-available critical information. On the other hand, the risks linked with its implementation in education are understudied. Some…

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Perceived Trustworthiness of Natural Language Generators

Author: Cabrero-Daniel, Beatriz; Cabrero, Andrea Sanagustin Description: Natural Language Generation tools, such as chatbots that can generate human-like conversational text, are becoming more common both for personal and professional use. However, there are concerns about their trustworthiness and ethical implications. The paper addresses the problem of understanding how different users (e.g., linguists, engineers) perceive and adopt these tools and their perception of machine-generated text quality. It also discusses the perceived advantages and limitations of Natural Language Generation tools, as well as users’ beliefs on governance strategies. The main findings of…

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Does distrust in humans predict greater trust in AI? Role of individual differences in user responses to content moderation

Author: Molina, Maria D.; Sundar, S. Shyam Description: When evaluating automated systems, some users apply the “positive machine heuristic” (i.e. machines are more accurate and precise than humans), whereas others apply the “negative machine heuristic” (i.e. machines lack the ability to make nuanced subjective judgments), but we do not know much about the characteristics that predict whether a user would apply the positive or negative machine heuristic. We conducted a study in the context of content moderation and discovered that individual differences relating to trust in humans, fear of artificial…

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