Results for 'AI'

526 found
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  1. Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2021 - Synthese 198 (March):2061-2081.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when (...)
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  2.  49
    How AI Can Be a Force for Good.Mariarosaria Taddeo & Luciano Floridi - 2018 - Science Magazine 361 (6404):751-752.
    This article argues that an ethical framework will help to harness the potential of AI while keeping humans in control.
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  3. The AI GambitLeveraging Artificial Intelligence to Combat Climate Change: Opportunities, Challenges, and Recommendations.Josh Cowls, Andreas Tsamados, Mariarosaria Taddeo & Luciano Floridi - 2021 - In Vodafone Institute for Society and Communications.
    In this article we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that (...)
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  4. 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 (...)
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  5.  39
    AI and its New Winter: From Myths to Realities.Luciano Floridi - 2020 - Philosophy and Technology 33 (1):1-3.
    An AI winter may be defined as the stage when technology, business, and the media come to terms with what AI can or cannot really do as (...)
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  6. AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI.Jose Hernandez-Orallo & Karina Vold - 2019 - In Proceedings of the AAAI/ACM 2019 Conference on AIES. pp. 507-513.
    Humans and AI systems are usually portrayed as separate sys- tems that we need to align in values and goals. However, there is a great deal of (...)
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  7. Why AI Doomsayers Are Like Sceptical Theists and Why It Matters.John Danaher - 2015 - Minds and Machines 25 (3):231-246.
    An advanced artificial intelligence could pose a significant existential risk to humanity. Several research institutes have been set-up to address those risks. And there is an (...)increasing number of academic publications analysing and evaluating their seriousness. Nick Bostroms superintelligence: paths, dangers, strategies represents the apotheosis of this trend. In this article, I argue that in defending the credibility of AI risk, Bostrom makes an epistemic move that is analogous to one made by so-called sceptical theists in the debate about the existence of God. And while this analogy is interesting in its own right, what is more interesting are its potential implications. It has been repeatedly argued that sceptical theism has devastating effects on our beliefs and practices. Could it be that AI-doomsaying has similar effects? I argue that it could. Specifically, and somewhat paradoxically, I argue that it could amount to either a reductio of the doomsayers position, or an important and additional reason to join their cause. I use this paradox to suggest that the modal standards for argument in the superintelligence debate need to be addressed. (shrink)
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  8. Transparent, Explainable, and Accountable AI for Robotics.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - Science (Robotics) 2 (6):eaan6080.
    To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.
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  9.  46
    Prolegomena to a White Paper on an Ethical Framework for a Good AI Society.Josh Cowls & Luciano Floridi - manuscript
    That AI will have a major impact on society is no longer in question. Current debate turns instead on how far this impact will be positive or (...)
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  10. Toward an Ethics of AI Assistants: an Initial Framework.John Danaher - 2018 - Philosophy and Technology 31 (4):629-653.
    Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: (...)
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  11. When AI Meets PC: Exploring the Implications of Workplace Social Robots and a Human-Robot Psychological Contract.Sarah Bankins & Paul Formosa - 2019 - European Journal of Work and Organizational Psychology 2019.
    The psychological contract refers to the implicit and subjective beliefs regarding a reciprocal exchange agreement, predominantly examined between employees and employers. While contemporary contract research is investigating (...)
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  12.  46
    Aiming AI at a Moving Target: Health.Mihai Nadin - 2020 - AI and Society 35 (4):841-849.
    Justified by spectacular achievements facilitated through applied deep learning methodology, theEverything is possibleview dominates this new hour in theboom and bustcurve of AI (...)
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  13. Explaining Explanations in AI.Brent Mittelstadt - forthcoming - FAT* 2019 Proceedings 1.
    Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These (...)
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  14.  35
    The Whiteness of AI.Stephen Cave & Kanta Dihal - 2020 - Philosophy and Technology 33 (4):685-703.
    This paper focuses on the fact that AI is predominantly portrayed as whitein colour, ethnicity, or both. We first illustrate the prevalent Whiteness of real and (...)imagined intelligent machines in four categories: humanoid robots, chatbots and virtual assistants, stock images of AI, and portrayals of AI in film and television. We then offer three interpretations of the Whiteness of AI, drawing on critical race theory, particularly the idea of the White racial frame. First, we examine the extent to which this Whiteness might simply reflect the predominantly White milieus from which these artefacts arise. Second, we argue that to imagine machines that are intelligent, professional, or powerful is to imagine White machines because the White racial frame ascribes these attributes predominantly to White people. Third, we argue that AI racialised as White allows for a full erasure of people of colour from the White utopian imaginary. Finally, we examine potential consequences of the racialisation of AI, arguing it could exacerbate bias and misdirect concern. (shrink)
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  15.  91
    AI Risk Denialism.Roman V. Yampolskiy - manuscript
    In this work, we survey skepticism regarding AI risk and show parallels with other types of scientific skepticism. We start by classifying different types of AI Risk (...)
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  16.  96
    Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles.Steven Umbrello & Roman Yampolskiy - forthcoming - International Journal of Social Robotics:1-15.
    One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and (...) logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents (IAs). This paper explores how decision matrix algorithms, via the belief-desire-intention model for autonomous vehicles, can be designed to minimize the risks of opaque architectures. Primarily through an explicit orientation towards designing for the values of explainability and verifiability. In doing so, this research adopts the Value Sensitive Design (VSD) approach as a principled framework for the incorporation of such values within design. VSD is recognized as a potential starting point that offers a systematic way for engineering teams to formally incorporate existing technical solutions within ethical design, while simultaneously remaining pliable to emerging issues and needs. It is concluded that the VSD methodology offers at least a strong enough foundation from which designers can begin to anticipate design needs and formulate salient design flows that can be adapted to the changing ethical landscapes required for utilisation in autonomous vehicles. (shrink)
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  17. AI and the Mechanistic Forces of Darkness.Eric Dietrich - 1995 - J. Of Experimental and Theoretical AI 7 (2):155-161.
    Under the Superstition Mountains in central Arizona toil those who would rob humankind o f its humanity. These gray, soulless monsters methodically tear away at our meaning, (...)
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  18. Military AI as a Convergent Goal of Self-Improving AI.Alexey Turchin & Denkenberger David - 2018 - In Artificial Intelligence Safety and Security. Louiswille: CRC Press.
    Better instruments to predict the future evolution of artificial intelligence (AI) are needed, as the destiny of our civilization depends on it. One of the ways to (...)
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  19. Saliva Ontology: An Ontology-Based Framework for a Salivaomics Knowledge Base.Jiye Ai, Barry Smith & David Wong - 2010 - BMC Bioinformatics 11 (1):302.
    The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. (...)
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  20.  69
    AI4Peoplean Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations.Luciano Floridi, Josh Cowls, Monica Beltrametti, Raja Chatila, Patrice Chazerand, Virginia Dignum, Christoph Luetge, Robert Madelin, Ugo Pagallo, Francesca Rossi, Burkhard Schafer, Peggy Valcke & Effy Vayena - 2018 - Minds and Machines 28 (4):689-707.
    This article reports the findings of AI4People, an AtomiumEISMD initiative designed to lay the foundations for aGood AI Society”. We introduce the core opportunities and (...)risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendationsto assess, to develop, to incentivise, and to support good AIwhich in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society. (shrink)
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  21. AI, Concepts, and the Paradox of Mental Representation, with a Brief Discussion of Psychological Essentialism.Eric Dietrich - 2001 - J. Of Exper. And Theor. AI 13 (1):1-7.
    Mostly philosophers cause trouble. I know because on alternate Thursdays I am one -- and I live in a philosophy department where I watch all of them cause (...) trouble. Everyone in artificial intelligence knows how much trouble philosophers can cause (and in particular, we know how much trouble one philosopher -- John Searle -- has caused). And, we know where they tend to cause it: in knowledge representation and the semantics of data structures. This essay is about a recent case of this sort of thing. One of the take-home messages will be that AI ought to redouble its efforts t o understand concepts. (shrink)
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  22. AI Alignment Problem: “Human ValuesDonT Actually Exist.Alexey Turchin - manuscript
    Abstract. The main current approach to the AI safety is AI alignment, that is, the creation of AI whose preferences are aligned withhuman values.” Many AI (...)
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  23. AI, Situatedness, Creativity, and Intelligence; or the Evolution of the Little Hearing Bones.Eric Dietrich - 1996 - J. Of Experimental and Theoretical AI 8 (1):1-6.
    Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like (...)
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  24. Making Metaethics Work for AI: Realism and Anti-Realism.Michal Klincewicz & Lily E. Frank - 2018 - In Mark Coeckelbergh, M. Loh, J. Funk, M. Seibt & J. Nørskov (eds.), Envisioning Robots in Society – Power, Politics, and Public Space. Amsterdam, Netherlands: IOS Press. pp. 311-318.
    Engineering an artificial intelligence to play an advisory role in morally charged decision making will inevitably introduce meta-ethical positions into the design. Some of these positions, (...)by informing the design and operation of the AI, will introduce risks. This paper offers an analysis of these potential risks along the realism/anti-realism dimension in metaethics and reveals that realism poses greater risks, but, on the other hand, anti-realism undermines the motivation for engineering a moral AI in the first place. (shrink)
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  25.  69
    A United Framework of Five Principles for AI in Society.Luciano Floridi & Josh Cowls - 2019 - Harvard Data Science Review 1 (1).
    Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles (...)
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  26. Theory and Philosophy of AI (Minds and Machines, 22/2 - Special Volume).Vincent C. Müller (ed.) - 2012 - Springer.
    Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced (...) Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition. (shrink)
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  27. New Developments in the Philosophy of AI.Vincent Müller - 2016 - In Fundamental Issues of Artificial Intelligence. Springer.
    The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear (...)
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  28.  98
    Establishing the Rules for Building Trustworthy AI.Luciano Floridi - 2019 - Nature Machine Intelligence 1:261-262.
    AI is revolutionizing everyones life, and it is crucial that it does so in the right way. AIs profound and far-reaching potential for transformation concerns (...)
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  29. Bioinformatics Advances in Saliva Diagnostics.Ji-Ye Ai, Barry Smith & David T. W. Wong - 2012 - International Journal of Oral Science 4 (2):85--87.
    There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The (...) goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva diagnostics made possible by the Saliva Ontology and SDxMart. (shrink)
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  30.  81
    ExcavatingExcavating AI”: The Elephant in the Gallery.Michael J. Lyons - 2020 - arXiv 2009:1-15.
    Two art exhibitions, “Training HumansandMaking Faces,” and the accompanying essayExcavating AI: The politics of images in machine learning training setsby Kate Crawford and (...)
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  31. Limits of Trust in Medical AI.Joshua James Hatherley - 2020 - Journal of Medical Ethics 46 (7):478-481.
    Artificial intelligence is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting (...)
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  32. Value Sensitive Design to Achieve the UN SDGs with AI: A Case of Elderly Care Robots.Steven Umbrello, Marianna Capasso, Maurizio Balistreri, Alberto Pirni & Federica Merenda - forthcoming - Minds and Machines:1-25.
    The increasing automation and ubiquity of robotics deployed within the field of care boasts promising advantages. However, challenging ethical issues arise also as a consequence. This paper (...)
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  33.  45
    From What to How: an Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles Into Practices.Jessica Morley, Luciano Floridi, Libby Kinsey & Anat Elhalal - 2020 - Science and Engineering Ethics 26 (4):2141-2168.
    The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741742, 1960; Wiener in Cybernetics: or control and communication in the animal and (...)the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principlesthewhatof AI ethicsrather than on practices, thehow.’ Awareness of the potential issues is increasing at a fast rate, but the AI communitys ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (shrink)
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  34.  60
    Unpredictability of AI.Roman Yampolskiy - manuscript
    The young field of AI Safety is still in the process of identifying its challenges and limitations. In this paper, we formally describe one such impossibility result, (...)
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  35. AI Human Impact: Toward a Model for Ethical Investing in AI-Intensive Companies.James Brusseau - manuscript
    Does AI conform to humans, or will we conform to AI? An ethical evaluation of AI-intensive companies will allow investors to knowledgeably participate in the decision. (...)The evaluation is built from nine performance indicators that can be analyzed and scored to reflect a technologys human-centering. When summed, the scores convert into objective investment guidance. The strategy of incorporating ethics into financial decisions will be recognizable to participants in environmental, social, and governance investing, however, this paper argues that conventional ESG frameworks are inadequate for AI-intensive companies. To fully account for contemporary technology, the following categories of evaluation will be developed and featured as vital investing criteria: autonomy, dignity, privacy, performance. With these priorities established, the larger goal is a model for humanitarian investing in AI-intensive companies that is intellectually robust, manageable for analysts, useful for portfolio managers, and credible for investors. (shrink)
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  36.  98
    Good AI for the Present of Humanity Democratizing AI Governance.Nicholas Kluge Corrêa - manuscript
    What does Cyberpunk and AI Ethics have to do with each other? Cyberpunk is a sub-genre of science fiction that explores the post-human relationships between human (...) experience and technology. One similarity between AI Ethics and Cyberpunk literature is that both seek a dialogue in which the reader may inquire about the future and the ethical and social problems that our technological advance may bring upon society. In recent years, an increasing number of ethical matters involving AI have been pointed and debated, and several ethical principles and guides have been suggested as governance policies for the tech industry. However, would this be the role of AI Ethics? To serve as a soft and ambiguous version of the law? I would like to promote in this article a more Cyberpunk way of doing AI Ethics, whit a more anarchic way of governance. In this study, I will seek to expose some of the deficits of the underlying power structures of our society, and suggest that AI governance be subject to public opinion, so thatgood AIcan becomegood AI for all’. (shrink)
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  37. Making AI Philosophical Again: On Philip E. Agre's Legacy.Jethro Masís - 2014 - Continent 4 (1):58-70.
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  38.  27
    Should We Be Afraid of AI?Luciano Floridi - 2019 - Aeon Magazine.
    Machines seem to be getting smarter and smarter and much better at human jobs, yet true AI is utterly implausible. This article explains the reasons why this (...)
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  39. There is No General AI.Jobst Landgrebe & Barry Smith - 2020 - arXiv.
    The goal of creating Artificial General Intelligence (AGI) – or in other words of creating Turing machines (modern computers) that can behave in a way that mimics human (...) intelligencehas occupied AI researchers ever since the idea of AI was first proposed. One common theme in these discussions is the thesis that the ability of a machine to conduct convincing dialogues with human beings can serve as at least a sufficient criterion of AGI. We argue that this very ability should be accepted also as a necessary condition of AGI, and we provide a description of the nature of human dialogue in particular and of human language in general against this background. We then argue that it is for mathematical reasons impossible to program a machine in such a way that it could master human dialogue behaviour in its full generality. This is (1) because there are no traditional explicitly designed mathematical models that could be used as a starting point for creating such programs; and (2) because even the sorts of automated models generated by using machine learning, which have been used successfully in areas such as machine translation, cannot be extended to cope with human dialogue. If this is so, then we can conclude that a Turing machine also cannot possess AGI, because it fails to fulfil a necessary condition thereof. At the same time, however, we acknowledge the potential of Turing machines to master dialogue behaviour in highly restricted contexts, where what is callednarrowAI can still be of considerable utility. (shrink)
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  40.  24
    Existential Risk From AI and Orthogonality: Can We Have It Both Ways?Vincent C. Müller & Michael Cannon - 2021 - Ratio:1-12.
    The standard argument to the conclusion that artificial intelligence (AI) constitutes an existential risk for the human species uses two premises: (1) AI may reach superintelligent levels, (...)
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  41. AI Methods in Bioethics.Joshua August Skorburg, Walter Sinnott-Armstrong & Vincent Conitzer - 2020 - American Journal of Bioethics: Empirical Bioethics 1 (11):37-39.
    Commentary about the role of AI in bioethics for the 10th anniversary issue of AJOB: Empirical Bioethics.
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  42.  13
    Ethics-Based Auditing to Develop Trustworthy AI.Jakob Mökander & Luciano Floridi - 2021 - Minds and Machines 31 (2):323-327.
    A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions (...)
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  43. Mapping Value Sensitive Design Onto AI for Social Good Principles.Steven Umbrello & Ibo van de Poel - 2021 - AI and Ethics 1:1-14.
    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 (...)
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  44. AI Governance and the Policymaking Process: Key Considerations for Reducing AI Risk.Brandon Perry & Risto Uuk - 2019 - Big Data and Cognitive Computing 3 (2):1-17.
    This essay argues that a new subfield of AI governance should be explored that examines the policy-making process and its implications for AI governance. A growing (...)number of researchers have begun working on the question of how to mitigate the catastrophic risks of transformative artificial intelligence, including what policies states should adopt. However, this essay identifies a preceding, meta-level problem of how the space of possible policies is affected by the politics and administrative mechanisms of how those policies are created and implemented. This creates a new set of key considerations for the field of AI governance and should influence the action of future policymakers. This essay examines some of the theories of the policymaking process, how they compare to current work in AI governance, and their implications for the field at large and ends by identifying areas of future research. (shrink)
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  45.  21
    Ethics-Based Auditing to Develop Trustworthy AI.Jakob Mökander & Luciano Floridi - 2021 - Minds and Machines.
    A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions (...)
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  46. AI Extenders and the Ethics of Mental Health.Karina Vold & Jose Hernandez-Orallo - forthcoming - In Marcello Ienca & Fabrice Jotterand (eds.), Ethics of Artificial Intelligence in Brain and Mental Health.
    The extended mind thesis maintains that the functional contributions of tools and artefacts can become so essential for our cognition that they can be constitutive parts of (...)
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  47.  36
    Innovating with Confidence: Embedding AI Governance and Fairness in a Financial Services Risk Management Framework.Luciano Floridi, Michelle Seng Ah Lee & Alexander Denev - 2020 - Berkeley Technology Law Journal 34.
    An increasing number of financial services (FS) companies are adopting solutions driven by artificial intelligence (AI) to gain operational efficiencies, derive strategic insights, and improve customer engagement. (...)
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  48. The Ethics of AI in Health Care: a Mapping Review.Jessica Morley, Caio C. V. Machado, Christopher Burr, Josh Cowls, Indra Joshi, Mariarosaria Taddeo & Luciano Floridi - 2020 - Social Science & Medicine 260.
    This article presents a mapping review of the literature concerning the ethics of artificial intelligence (AI) in health care. The goal of this review is to summarise (...)
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  49. AI Can Help Us Live More Deliberately.Julian Friedland - 2019 - MIT Sloan Management Review 60 (4).
    Our rapidly increasing reliance on frictionless AI interactions may increase cognitive and emotional distance, thereby letting our adaptive resilience slacken and our ethical virtues atrophy from disuse. (...)
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  50.  69
    How AI Can AID Bioethics.Walter Sinnott Armstrong & Joshua August Skorburg - forthcoming - Journal of Practical Ethics.
    This paper explores some ways in which artificial intelligence (AI) could be used to improve human moral judgments in bioethics by avoiding some of the most common (...)
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