Results for 'AI for Social Good'

974 found
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  1. AI for Social Good, AI for Datong.Pak-Hang Wong - 2021 - Informatio 26 (1):42-57.
    The Chinese government and technology companies assume a proactive stance towards digital technologies and AI and their roles in users’—and more generally, people’s—lives. This vision of ‘Tech for Good’, i.e., the development of good digital technologies and AI or the application of them for good, is also shared by major technology companies in the globe, e.g., Google, Microsoft, and Facebook. Interestingly, these initiatives have invited a number of critiques for their feasibility and desirability, particularly in relation to (...)
     
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    Applying AI for social good: Aligning academic journal ratings with the United Nations Sustainable Development Goals (SDGs).David Steingard, Marcello Balduccini & Akanksha Sinha - 2023 - AI and Society 38 (2):613-629.
    This paper offers three contributions to the burgeoning movements of AI for Social Good (AI4SG) and AI and the United Nations Sustainable Development Goals (SDGs). First, we introduce the SDG-Intense Evaluation framework (SDGIE) that aims to situate variegated automated/AI models in a larger ecosystem of computational approaches to advance the SDGs. To foster knowledge collaboration for solving complex social and environmental problems encompassed by the SDGs, the SDGIE framework details a benchmark structure of data-algorithm-output to effectively standardize (...)
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  3. How to design AI for social good: seven essential factors.Luciano Floridi, Josh Cowls, Thomas C. King & Mariarosaria Taddeo - 2020 - Science and Engineering Ethics 26 (3):1771–1796.
    The idea of artificial intelligence for social good is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven (...)
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    Investing in AI for social good: an analysis of European national strategies.Francesca Foffano, Teresa Scantamburlo & Atia Cortés - 2023 - AI and Society 38 (2):479-500.
    Artificial Intelligence (AI) has become a driving force in modern research, industry and public administration and the European Union (EU) is embracing this technology with a view to creating societal, as well as economic, value. This effort has been shared by EU Member States which were all encouraged to develop their own national AI strategies outlining policies and investment levels. This study focuses on how EU Member States are approaching the promise to develop and use AI for the good (...)
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  5.  33
    ‘AI for Social Good’: Whose Good and Who’s Good? Introduction to the Special Issue on Artificial Intelligence for Social Good.Josh Cowls - 2021 - Philosophy and Technology 34 (1):1-5.
    This introduction sets out the aims and scope of the Special Issue and provides an overview of each of the research articles and commentaries that follow.
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  6. A definition, benchmark and database of AI for social good initiatives.Josh Cowls, Andreas Tsmadaos, Mariarosaria Taddeo & Luciano Floridi - 2021 - Nature Machine Intelligence 3:111–⁠115.
    Initiatives relying on artificial intelligence (AI) to deliver socially beneficial outcomes—AI for social good (AI4SG)—are on the rise. However, existing attempts to understand and foster AI4SG initiatives have so far been limited by the lack of normative analyses and a shortage of empirical evidence. In this Perspective, we address these limitations by providing a definition of AI4SG and by advocating the use of the United Nations’ Sustainable Development Goals (SDGs) as a benchmark for tracing the scope and spread (...)
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  7.  11
    Correction to: Investing in AI for social good: an analysis of European national strategies.Francesca Foffano, Teresa Scantamburlo & Atia Cortés - forthcoming - AI and Society:1-1.
  8. Responsible nudging for social good: new healthcare skills for AI-driven digital personal assistants.Marianna Capasso & Steven Umbrello - 2022 - Medicine, Health Care and Philosophy 25 (1):11-22.
    Traditional medical practices and relationships are changing given the widespread adoption of AI-driven technologies across the various domains of health and healthcare. In many cases, these new technologies are not specific to the field of healthcare. Still, they are existent, ubiquitous, and commercially available systems upskilled to integrate these novel care practices. Given the widespread adoption, coupled with the dramatic changes in practices, new ethical and social issues emerge due to how these systems nudge users into making decisions and (...)
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  9. Mapping Value Sensitive Design onto AI for Social Good Principles.Steven Umbrello & Ibo van de Poel - 2021 - AI and Ethics 1 (3):283–296.
    Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, ML (...)
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  10.  56
    Harmonizing Artificial Intelligence for Social Good.Nicolas Berberich, Toyoaki Nishida & Shoko Suzuki - 2020 - Philosophy and Technology 33 (4):613-638.
    To become more broadly applicable, positions on AI ethics require perspectives from non-Western regions and cultures such as China and Japan. In this paper, we propose that the addition of the concept of harmony to the discussion on ethical AI would be highly beneficial due to its centrality in East Asian cultures and its applicability to the challenge of designing AI for social good. We first present a synopsis of different definitions of harmony in multiple contexts, such as (...)
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  11.  50
    AI for the public. How public interest theory shifts the discourse on AI.Theresa Züger & Hadi Asghari - 2023 - AI and Society 38 (2):815-828.
    AI for social good is a thriving research topic and a frequently declared goal of AI strategies and regulation. This article investigates the requirements necessary in order for AI to actually serve a public interest, and hence be socially good. The authors propose shifting the focus of the discourse towards democratic governance processes when developing and deploying AI systems. The article draws from the rich history of public interest theory in political philosophy and law, and develops a (...)
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  12. Socially Good AI Contributions for the Implementation of Sustainable Development in Mountain Communities Through an Inclusive Student-Engaged Learning Model.Tyler Lance Jaynes, Baktybek Abdrisaev & Linda MacDonald Glenn - 2023 - In Francesca Mazzi & Luciano Floridi, The Ethics of Artificial Intelligence for the Sustainable Development Goals. Springer Verlag. pp. 269-289.
    AI is increasingly becoming based upon Internet-dependent systems to handle the massive amounts of data it requires to function effectively regardless of the availability of stable Internet connectivity in every affected community. As such, sustainable development (SD) for rural and mountain communities will require more than just equitable access to broadband Internet connection. It must also include a thorough means whereby to ensure that affected communities gain the education and tools necessary to engage inclusively with new technological advances, whether they (...)
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  13.  55
    Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective.Erik Hermann - 2022 - Journal of Business Ethics 179 (1):43-61.
    Artificial intelligence is shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To (...)
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  14.  17
    (1 other version)Tacit engagement using tablet-mediated learning for social good.Ignacio Nieto, Marcelo Velasco & Christian Miranda - 2021 - AI and Society:1-5.
    We discuss the effectiveness of mediated communication (internet communication via a computer tablet) and tacit engagement in a Project on mental health. The project is aimed at improving the wellbeing of adult women living with chronic mental disorders in long-term psychiatric internment. The computer tablets act as "portals" to provide access and conatct with the outside world for patients who have poor (if any) external social support. This support includes a patient-centred psycho-social care, and accompanying clinical and pharmaceutical (...)
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  15. Big Tech corporations and AI: A Social License to Operate and Multi-Stakeholder Partnerships in the Digital Age.Marianna Capasso & Steven Umbrello - 2023 - In Francesca Mazzi & Luciano Floridi, The Ethics of Artificial Intelligence for the Sustainable Development Goals. Springer Verlag. pp. 231–249.
    The pervasiveness of AI-empowered technologies across multiple sectors has led to drastic changes concerning traditional social practices and how we relate to one another. Moreover, market-driven Big Tech corporations are now entering public domains, and concerns have been raised that they may even influence public agenda and research. Therefore, this chapter focuses on assessing and evaluating what kind of business model is desirable to incentivise the AI for Social Good (AI4SG) factors. In particular, the chapter explores the (...)
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  16.  46
    AI ageism: a critical roadmap for studying age discrimination and exclusion in digitalized societies.Justyna Stypinska - 2023 - AI and Society 38 (2):665-677.
    In the last few years, we have witnessed a surge in scholarly interest and scientific evidence of how algorithms can produce discriminatory outcomes, especially with regard to gender and race. However, the analysis of fairness and bias in AI, important for the debate of AI for social good, has paid insufficient attention to the category of age and older people. Ageing populations have been largely neglected during the turn to digitality and AI. In this article, the concept of (...)
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  17.  58
    Ethical artificial intelligence framework for a good AI society: principles, opportunities and perils.Pradeep Paraman & Sanmugam Anamalah - 2023 - AI and Society 38 (2):595-611.
    The justification and rationality of this paper is to present some fundamental principles, theories, and concepts that we believe moulds the nucleus of a good artificial intelligence (AI) society. The morally accepted significance and utilitarian concerns that stems from the inception and realisation of an AI’s structural foundation are displayed in this study. This paper scrutinises the structural foundation, fundamentals, and cardinal righteous remonstrations, as well as the gaps in mechanisms towards novel prospects and perils in determining resilient fundamentals, (...)
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  18. Can AI Achieve Common Good and Well-being? Implementing the NSTC's R&D Guidelines with a Human-Centered Ethical Approach.Jr-Jiun Lian - 2024 - 2024 Annual Conference on Science, Technology, and Society (Sts) Academic Paper, National Taitung University. Translated by Jr-Jiun Lian.
    This paper delves into the significance and challenges of Artificial Intelligence (AI) ethics and justice in terms of Common Good and Well-being, fairness and non-discrimination, rational public deliberation, and autonomy and control. Initially, the paper establishes the groundwork for subsequent discussions using the Academia Sinica LLM incident and the AI Technology R&D Guidelines of the National Science and Technology Council(NSTC) as a starting point. In terms of justice and ethics in AI, this research investigates whether AI can fulfill human (...)
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  19.  29
    Stream: social data and knowledge collective intelligence platform for TRaining Ethical AI Models.Yuwei Wang, Enmeng Lu, Zizhe Ruan, Yao Liang & Yi Zeng - forthcoming - AI and Society:1-9.
    This paper presents social data and knowledge collective intelligence platform for TRaining Ethical AI Models (STREAM) to address the challenge of aligning AI models with human moral values, and to provide ethics datasets and knowledge bases to help promote AI models “follow good advice as naturally as a stream follows its course”. By creating a comprehensive and representative platform that accurately mirrors the moral judgments of diverse groups including humans and AIs, we hope to effectively portray cultural and (...)
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    AI Literacy: A Primary Good.P. Benton - 2023 - Springer Nature 1976:31–43.
    In this paper, I argue that AI literacy should be added to the list of primary goods developed by political philosopher John Rawls. Primary goods are the necessary resources all citizens need to exercise their two moral powers, namely their sense of justice and their sense of the good. These goods are advantageous for citizens since without them citizens will not be able to fully develop their moral powers. I claim the lack of AI literacy impacts citizens’ ability to (...)
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  21. Reframing Deception for Human-Centered AI.Steven Umbrello & Simone Natale - 2024 - International Journal of Social Robotics 16 (11-12):2223–2241.
    The philosophical, legal, and HCI literature concerning artificial intelligence (AI) has explored the ethical implications and values that these systems will impact on. One aspect that has been only partially explored, however, is the role of deception. Due to the negative connotation of this term, research in AI and Human–Computer Interaction (HCI) has mainly considered deception to describe exceptional situations in which the technology either does not work or is used for malicious purposes. Recent theoretical and historical work, however, has (...)
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    Four investment areas for ethical AI: Transdisciplinary opportunities to close the publication-to-practice gap.Jana Schaich Borg - 2021 - Big Data and Society 8 (2).
    Big Data and Artificial Intelligence have a symbiotic relationship. Artificial Intelligence needs to be trained on Big Data to be accurate, and Big Data's value is largely realized through its use by Artificial Intelligence. As a result, Big Data and Artificial Intelligence practices are tightly intertwined in real life settings, as are their impacts on society. Unethical uses of Artificial Intelligence are therefore a Big Data problem, at least to some degree. Efforts to address this problem have been dominated by (...)
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  23.  27
    Something AI Should Tell You – The Case for Labelling Synthetic Content.Sarah A. Fisher - 2025 - Journal of Applied Philosophy 42 (1):272-286.
    Synthetic content, which has been produced by generative artificial intelligence, is beginning to spread through the public sphere. Increasingly, we find ourselves exposed to convincing ‘deepfakes’ and powerful chatbots in our online environments. How should we mitigate the emerging risks to individuals and society? This article argues that labelling synthetic content in public forums is an essential first step. While calls for labelling have already been growing in volume, no principled argument has yet been offered to justify this measure (which (...)
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  24. AI and society: a virtue ethics approach.Mirko Farina, Petr Zhdanov, Artur Karimov & Andrea Lavazza - 2024 - AI and Society 39 (3):1127-1140.
    Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and (...)
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  25.  30
    In the Frame: the Language of AI.Helen Bones, Susan Ford, Rachel Hendery, Kate Richards & Teresa Swist - 2020 - Philosophy and Technology 34 (1):23-44.
    In this article, drawing upon a feminist epistemology, we examine the critical roles that philosophical standpoint, historical usage, gender, and language play in a knowledge arena which is increasingly opaque to the general public. Focussing on the language dimension in particular, in its historical and social dimensions, we explicate how some keywords in use across artificial intelligence (AI) discourses inform and misinform non-expert understandings of this area. The insights gained could help to imagine how AI technologies could be better (...)
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  26.  86
    What Makes Work “Good” in the Age of Artificial Intelligence (AI)? Islamic Perspectives on AI-Mediated Work Ethics.Mohammed Ghaly - 2024 - The Journal of Ethics 28 (3):429-453.
    Artificial intelligence (AI) technologies are increasingly creeping into the work sphere, thereby gradually questioning and/or disturbing the long-established moral concepts and norms communities have been using to define what makes work good. Each community, and Muslims make no exception in this regard, has to revisit their moral world to provide well-thought frameworks that can engage with the challenging ethical questions raised by the new phenomenon of AI-mediated work. For a systematic analysis of the broad topic of AI-mediated work ethics (...)
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  27.  7
    AI diagnoses terminal illness care limits: just, or just stingy?Leonard Michael Fleck - 2024 - Journal of Medical Ethics 50 (12):818-819.
    I agree with Jecker et al that “the headline-grabbing nature of existential risk (X-risk) diverts attention away from immediate artificial intelligence (AI) threats…”1 Focusing on very long-term speculative risks associated with AI is both ethically distracting and ethically dangerous, especially in a healthcare context. More specifically, AI in healthcare is generating healthcare justice challenges that are real, imminent and pervasive. These are challenges generated by AI that deserve immediate ethical attention, more than any X-risk issues in the distant future. Almost (...)
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  28.  17
    Towards the Use of Social Robot Furhat and Generative AI in Testing Cognitive Abilities.Róbert Sabo, Štefan Beňuš, Viktória Kevická, Marian Trnka, Milan Rusko, Sakhia Darjaa & Jay Kejriwal - 2024 - Human Affairs 34 (2):224-243.
    Spoken communication between social robotic devices, powered by generative AI tools such as ChatGPT, and the senior population offers great potential for researching social interaction and robot identity perceptions as well as exploring the potential opportunities and challenges when implementing this human-machine interactions in real life situations and health care. In this paper we explore people’s perceptions of the social robot Furhat when administering verbal tasks similar to those used in screening for Alzheimer’s disease. We describe the (...)
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  29.  32
    Applying ethics to AI in the workplace: the design of a scorecard for Australian workplace health and safety.Andreas Cebulla, Zygmunt Szpak, Catherine Howell, Genevieve Knight & Sazzad Hussain - 2023 - AI and Society 38 (2):919-935.
    Artificial Intelligence (AI) is taking centre stage in economic growth and business operations alike. Public discourse about the practical and ethical implications of AI has mainly focussed on the societal level. There is an emerging knowledge base on AI risks to human rights around data security and privacy concerns. A separate strand of work has highlighted the stresses of working in the gig economy. This prevailing focus on human rights and gig impacts has been at the expense of a closer (...)
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  30.  29
    A principle-based approach to AI: the case for European Union and Italy.Francesco Corea, Fabio Fossa, Andrea Loreggia, Stefano Quintarelli & Salvatore Sapienza - 2023 - AI and Society 38 (2):521-535.
    As Artificial Intelligence (AI) becomes more and more pervasive in our everyday life, new questions arise about its ethical and social impacts. Such issues concern all stakeholders involved in or committed to the design, implementation, deployment, and use of the technology. The present document addresses these preoccupations by introducing and discussing a set of practical obligations and recommendations for the development of applications and systems based on AI techniques. With this work we hope to contribute to spreading awareness on (...)
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  31.  33
    Should AI allocate livers for transplant? Public attitudes and ethical considerations.Max Drezga-Kleiminger, Joanna Demaree-Cotton, Julian Koplin, Julian Savulescu & Dominic Wilkinson - 2023 - BMC Medical Ethics 24 (1):1-11.
    Background: Allocation of scarce organs for transplantation is ethically challenging. Artificial intelligence (AI) has been proposed to assist in liver allocation, however the ethics of this remains unexplored and the view of the public unknown. The aim of this paper was to assess public attitudes on whether AI should be used in liver allocation and how it should be implemented. Methods: We first introduce some potential ethical issues concerning AI in liver allocation, before analysing a pilot survey including online responses (...)
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  32.  56
    Nudging for good: robots and the ethical appropriateness of nurturing empathy and charitable behavior.Borenstein Jason & C. Arkin Ronald - 2017 - AI and Society 32 (4):499-507.
    An under-examined aspect of human–robot interaction that warrants further exploration is whether robots should be permitted to influence a user’s behavior for that person’s own good. Yet an even more controversial practice could be on the horizon, which is allowing a robot to “nudge” a user’s behavior for the good of society. In this article, we examine the feasibility of creating companion robots that would seek to nurture a user’s empathy toward other human beings. As more and more (...)
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  33.  51
    Socially responsive technologies: toward a co-developmental path.Daniel W. Tigard, Niël H. Conradie & Saskia K. Nagel - 2020 - AI and Society 35 (4):885-893.
    Robotic and artificially intelligent (AI) systems are becoming prevalent in our day-to-day lives. As human interaction is increasingly replaced by human–computer and human–robot interaction (HCI and HRI), we occasionally speak and act as though we are blaming or praising various technological devices. While such responses may arise naturally, they are still unusual. Indeed, for some authors, it is the programmers or users—and not the system itself—that we properly hold responsible in these cases. Furthermore, some argue that since directing blame or (...)
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  34.  24
    Ethics in Internet (Document).Pontifical Council for Social Communication - 2020 - Journal of Interdisciplinary Studies 32 (1-2):179-192.
    Today, the earth is an interconnected globe humming with electronic transmissions-a chattering planet nestled in the provident silence of space. The ethical question is whether this is contributing to authentic human development and helping individuals and peoples to be true to their transcendent destiny. The new media are powerful tools for education, cultural enrichment, commercial activity, political participation, intercultural dialogue and understanding. They also can serve the cause of religion. Yet the new information technology needs to be informed and guided (...)
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  35.  25
    COVID-19 is spatial: Ensuring that mobile Big Data is used for social good.Tuuli Toivonen, Matthew Zook, Olle Järv & Age Poom - 2020 - Big Data and Society 7 (2).
    The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understanding the broad implications of the pandemic. The avalanche of mobile Big Data makes it possible to study the spatial effects of the crisis with spatiotemporal detail at the national and global scales. However, the current crisis also highlights serious limitations in the readiness to take the (...)
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  36. Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms.Benedetta Giovanola & Simona Tiribelli - 2023 - AI and Society 38 (2):549-563.
    The increasing implementation of and reliance on machine-learning (ML) algorithms to perform tasks, deliver services and make decisions in health and healthcare have made the need for fairness in ML, and more specifically in healthcare ML algorithms (HMLA), a very important and urgent task. However, while the debate on fairness in the ethics of artificial intelligence (AI) and in HMLA has grown significantly over the last decade, the very concept of fairness as an ethical value has not yet been sufficiently (...)
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  37.  29
    Catholic Health Care and AI Ethics: Algorithms for Human Flourishing.Michael Miller - 2022 - The Linacre Quarterly 89 (2):75-89.
    Artificial Intelligence (AI) contributes to common goods and common harms in our everyday lives. In light of the Collingridge dilemma, information about both the actual and potential harm of AI is explored and myths about AI are dispelled. Catholic health care is then presented as being in a unique position to exert its influence to model the use of AI systems that minimizes the risk of harm and promotes human flourishing and the common good.
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  38.  62
    The tragedy of the AI commons.Travis LaCroix & Aydin Mohseni - 2022 - Synthese 200 (4):1-33.
    Policy and guideline proposals for ethical artificial intelligence research have proliferated in recent years. These are supposed to guide the socially-responsible development of AI for a common good. However, there typically exist incentives for non-cooperation ; and, these proposals often lack effective mechanisms to enforce their own normative claims. The situation just described constitutes a social dilemma—namely, a situation where no one has an individual incentive to cooperate, though mutual cooperation would lead to the best outcome for all (...)
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  39.  55
    The Blueprint for an AI Bill of Rights: In Search of Enaction, at Risk of Inaction.Emmie Hine & Luciano Floridi - 2023 - Minds and Machines 33 (2):285-292.
    The US is promoting a new vision of a “Good AI Society” through its recent AI Bill of Rights. This offers a promising vision of community-oriented equity unique amongst peer countries. However, it leaves the door open for potential rights violations. Furthermore, it may have some federal impact, but it is non-binding, and without concrete legislation, the private sector is likely to ignore it.
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  40.  57
    Against AI-improved Personal Memory.Björn Lundgren - 2020 - In Aging between Participation and Simulation. pp. 223–234.
    In 2017, Tom Gruber held a TED talk, in which he presented a vision of improving and enhancing humanity with AI technology. Specifically, Gruber suggested that an AI-improved personal memory (APM) would benefit people by improving their “mental gain”, making us more creative, improving our “social grace”, enabling us to do “science on our own data about what makes us feel good and stay healthy”, and, for people suffering from dementia, it “could make a difference between a life (...)
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  41. On the person-based predictive policing of AI.Tzu-Wei Hung & Chun-Ping Yen - 2020 - Ethics and Information Technology 23 (3):165-176.
    Should you be targeted by police for a crime that AI predicts you will commit? In this paper, we analyse when, and to what extent, the person-based predictive policing (PP) — using AI technology to identify and handle individuals who are likely to breach the law — could be justifiably employed. We first examine PP’s epistemological limits, and then argue that these defects by no means refrain from its usage; they are worse in humans. Next, based on major AI ethics (...)
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  42.  22
    AI and suicide risk prediction: Facebook live and its aftermath.Dolores Peralta - forthcoming - AI and Society:1-13.
    As suicide rates increase worldwide, the mental health industry has reached an impasse in attempts to assess patients, predict risk, and prevent suicide. Traditional assessment tools are no more accurate than chance, prompting the need to explore new avenues in artificial intelligence (AI). Early studies into these tools show potential with higher accuracy rates than previous methods alone. Medical researchers, computer scientists, and social media companies are exploring these avenues. While Facebook leads the pack, its efforts stem from scrutiny (...)
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  43.  43
    Filter Bubbles and the Unfeeling: How AI for Social Media Can Foster Extremism and Polarization.Ermelinda Rodilosso - 2024 - Philosophy and Technology 37 (2):1-21.
    Social media have undoubtedly changed our ways of living. Their presence concerns an increasing number of users (over 4,74 billion) and pervasively expands in the most diverse areas of human life. Marketing, education, news, data, and sociality are just a few of the many areas in which social media play now a central role. Recently, some attention toward the link between social media and political participation has emerged. Works in the field of artificial intelligence have already pointed (...)
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  44.  46
    Toward safe AI.Andres Morales-Forero, Samuel Bassetto & Eric Coatanea - 2023 - AI and Society 38 (2):685-696.
    Since some AI algorithms with high predictive power have impacted human integrity, safety has become a crucial challenge in adopting and deploying AI. Although it is impossible to prevent an algorithm from failing in complex tasks, it is crucial to ensure that it fails safely, especially if it is a critical system. Moreover, due to AI’s unbridled development, it is imperative to minimize the methodological gaps in these systems’ engineering. This paper uses the well-known Box-Jenkins method for statistical modeling as (...)
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  45. AI as Ideology: A Marxist Reading (Crawford, Marx/Engels, Debord, Althusser).Jeffrey Reid - manuscript
    Kate Crawford presents AI as “both reflecting and producing social relations and understandings of the world”; or again, as “a form of exercising power, and a way of seeing… as a manifestation of highly organized capital backed by vast systems of extraction and logistics, with supply chains that wrap around the entire planet”. I interpret these material insights through a Marxist understanding of ideology, with reference to Marx/Engels, Guy Debord and Louis Althusser. In the German Ideology, Marx and Engels (...)
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  46. Will AI take away your job? [REVIEW]Marie Oldfield - 2020 - Tech Magazine.
    Will AI take away your job? The answer is probably not. AI systems can be good predictive systems and be very good at pattern recognition. AI systems have a very repetitive approach to sets of data, which can be useful in certain circumstances. However, AI does make obvious mistakes. This is because AI does not have a sense of context. As Humans we have years of experience in the real world. We have vast amounts of contextual data stored (...)
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  47.  42
    AI, automation and the lightening of work.David A. Spencer - forthcoming - AI and Society:1-11.
    Artificial intelligence (AI) technology poses possible threats to existing jobs. These threats extend not just to the number of jobs available but also to their quality. In the future, so some predict, workers could face fewer and potentially worse jobs, at least if society does not embrace reforms that manage the coming AI revolution. This paper uses the example of Daron Acemoglu and Simon Johnson’s recent book—_Power and Progress_ (2023)—to illustrate some of the dilemmas and options for managing the future (...)
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  48.  71
    Apprehending AI moral purpose in practical wisdom.Mark Graves - 2024 - AI and Society 39 (3):1335-1348.
    Practical wisdom enables moral decision-making and action by aligning one’s apprehension of proximate goods with a distal, socially embedded interpretation of a more ultimate Good. A focus on purpose within the overall process mutually informs human moral psychology and moral AI development in their examinations of practical wisdom. AI practical wisdom could ground an AI system’s apprehension of reality in a sociotechnical moral process committed to orienting AI development and action in light of a pluralistic, diverse interpretation of that (...)
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  49. The Point of Blaming AI Systems.Hannah Altehenger & Leonhard Menges - 2024 - Journal of Ethics and Social Philosophy 27 (2).
    As Christian List (2021) has recently argued, the increasing arrival of powerful AI systems that operate autonomously in high-stakes contexts creates a need for “future-proofing” our regulatory frameworks, i.e., for reassessing them in the face of these developments. One core part of our regulatory frameworks that dominates our everyday moral interactions is blame. Therefore, “future-proofing” our extant regulatory frameworks in the face of the increasing arrival of powerful AI systems requires, among others things, that we ask whether it makes sense (...)
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    Intelligence at any price? A criterion for defining AI.Mihai Nadin - 2023 - AI and Society 38 (5):1813-1817.
    According to how AI has defined itself from its beginning, thinking in non-living matter, i.e., without life, is possible. The premise of symbolic AI is that operating on representations of reality machines can understand it. When this assumption did not work as expected, the mathematical model of the neuron became the engine of artificial “brains.” Connectionism followed. Currently, in the context of Machine Learning success, attempts are made at integrating the symbolic and connectionist paths. There is hope that Artificial General (...)
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