Results for 'Jiye Ai'

760 found
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  1.  98
    The Blood Ontology: An Ontology in the Domain of Hematology.Almeida Mauricio Barcellos, Proietti Anna Barbara de Freitas Carneiro, Ai Jiye & Barry Smith - 2011 - In Proceedings of the Second International Conference on Biomedical Ontology, Buffalo, NY, July 28-30, 2011 (CEUR 883). pp. (CEUR Workshop Proceedings, 833).
    Despite the importance of human blood to clinical practice and research, hematology and blood transfusion data remain scattered throughout a range of disparate sources. This lack of systematization concerning the use and definition of terms poses problems for physicians and biomedical professionals. We are introducing here the Blood Ontology, an ongoing initiative designed to serve as a controlled vocabulary for use in organizing information about blood. The paper describes the scope of the Blood Ontology, its stage of development and some (...)
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  2. Towards a Body Fluids Ontology: A Unified Application Ontology for Basic and Translational Science.Jiye Ai, Mauricio Barcellos Almeida, André Queiroz De Andrade, Alan Ruttenberg, David Tai Wai Wong & Barry Smith - 2011 - Second International Conference on Biomedical Ontology , Buffalo, Ny 833:227-229.
    We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how the (...)
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  3. 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. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...)
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  4. 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 technology’s 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 (...)
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  5.  17
    AI and the Expert; a Blueprint for the Ethical Use of Opaque AI.Amber Ross - forthcoming - AI and Society.
    The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...)
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  6.  41
    Can AI Mind Be Extended?Alice C. Helliwell - 2019 - Evental Aesthetics 8 (1):93-120.
    Andy Clark and David Chalmers’s theory of extended mind can be reevaluated in today’s world to include computational and Artificial Intelligence (AI) technology. This paper argues that AI can be an extension of human mind, and that if we agree that AI can have mind, it too can be extended. It goes on to explore the example of Ganbreeder, an image-making AI which utilizes human input to direct behavior. Ganbreeder represents one way in which AI extended mind could be achieved. (...)
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  7.  41
    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 in our (...)
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  8.  70
    Certifiable AI.Jobst Landgrebe - 2022 - Applied Sciences 12 (3):1050.
    Implicit stochastic models, including both ‘deep neural networks’ (dNNs) and the more recent unsupervised foundational models, cannot be explained. That is, it cannot be determined how they work, because the interactions of the millions or billions of terms that are contained in their equations cannot be captured in the form of a causal model. Because users of stochastic AI systems would like to understand how they operate in order to be able to use them safely and reliably, there has emerged (...)
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  9.  53
    AI Decision Making with Dignity? Contrasting Workers’ Justice Perceptions of Human and AI Decision Making in a Human Resource Management Context.Sarah Bankins, Paul Formosa, Yannick Griep & Deborah Richards - forthcoming - Information Systems Frontiers.
    Using artificial intelligence (AI) to make decisions in human resource management (HRM) raises questions of how fair employees perceive these decisions to be and whether they experience respectful treatment (i.e., interactional justice). In this experimental survey study with open-ended qualitative questions, we examine decision making in six HRM functions and manipulate the decision maker (AI or human) and decision valence (positive or negative) to determine their impact on individuals’ experiences of interactional justice, trust, dehumanization, and perceptions of decision-maker role appropriate- (...)
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  10. 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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  11. 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 skepticism and analyze their root causes. We conclude by suggesting some intervention approaches, which may be successful in reducing AI risk skepticism, at least amongst artificial intelligence researchers.
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  12. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi (ed.), Guide to Deep Learning Basics. Springer. pp. 117-130.
    Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...)
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  13.  47
    Medical AI and Human Dignity: Contrasting Perceptions of Human and Artificially Intelligent (AI) Decision Making in Diagnostic and Medical Resource Allocation Contexts.Paul Formosa, Wendy Rogers, Yannick Griep, Sarah Bankins & Deborah Richards - 2022 - Computers in Human Behaviour 133.
    Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions of being (...)
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  14. Good AI for the Present of Humanity Democratizing AI Governance.Nicholas Kluge Corrêa & Nythamar De Oliveira - 2021 - AI Ethics Journal 2 (2):1-16.
    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 (...)
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  15. 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 AI technology found in non-autonomous systems that are used as cognitive tools by humans. Under the extended mind thesis, the functional contributions of these tools become as essential to our cognition as our brains. But AI can take cognitive extension towards totally new capabil- ities, posing new philosophical, ethical and technical chal- lenges. To (...)
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  16. 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 genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...)
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  17.  40
    Can AI Help Us to Understand Belief? Sources, Advances, Limits, and Future Directions.Andrea Vestrucci, Sara Lumbreras & Lluis Oviedo - 2021 - International Journal of Interactive Multimedia and Artificial Intelligence 7 (1):24-33.
    The study of belief is expanding and involves a growing set of disciplines and research areas. These research programs attempt to shed light on the process of believing, understood as a central human cognitive function. Computational systems and, in particular, what we commonly understand as Artificial Intelligence (AI), can provide some insights on how beliefs work as either a linear process or as a complex system. However, the computational approach has undergone some scrutiny, in particular about the differences between what (...)
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  18. AI Extenders and the Ethics of Mental Health.Karina Vold & Jose Hernandez-Orallo - forthcoming - In Marcello Ienca & Fabrice Jotterand (eds.), Artificial Intelligence in Brain and Mental Health: Philosophical, Ethical & Policy Issues. Springer International Publishing.
    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 our minds. In other words, our tools can be on a par with our brains: our minds and cognitive processes can literally ‘extend’ into the tools. Several extended mind theorists have argued that this ‘extended’ view of the mind offers unique insights into how we understand, assess, and treat certain cognitive conditions. In this (...)
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  19. 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 (...)
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  20. AI-Aesthetics and the Anthropocentric Myth of Creativity.Emanuele Arielli & Lev Manovich - 2022 - NODES 1 (19-20).
    Since the beginning of the 21st century, technologies like neural networks, deep learning and “artificial intelligence” (AI) have gradually entered the artistic realm. We witness the development of systems that aim to assess, evaluate and appreciate artifacts according to artistic and aesthetic criteria or by observing people’s preferences. In addition to that, AI is now used to generate new synthetic artifacts. When a machine paints a Rembrandt, composes a Bach sonata, or completes a Beethoven symphony, we say that this is (...)
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  21. 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 a wider range of exchanges employees may hold, such as with team members and clients, it remains silent on a rapidly emerging form of workplace relationship: employees’ increasing engagement with technically, socially, and emotionally sophisticated forms of artificially intelligent (AI) technologies. In this paper we examine social robots (also termed humanoid robots) as likely (...)
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  22. NHS AI Lab: Why We Need to Be Ethically Mindful About AI for Healthcare.Jessica Morley & Luciano Floridi - unknown
    On 8th August 2019, Secretary of State for Health and Social Care, Matt Hancock, announced the creation of a £250 million NHS AI Lab. This significant investment is justified on the belief that transforming the UK’s National Health Service (NHS) into a more informationally mature and heterogeneous organisation, reliant on data-based and algorithmically-driven interactions, will offer significant benefit to patients, clinicians, and the overall system. These opportunities are realistic and should not be wasted. However, they may be missed (one may (...)
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  23. AI Alignment Problem: “Human Values” Don’T 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 with “human values.” Many AI safety researchers agree that the idea of “human values” as a constant, ordered sets of preferences is at least incomplete. However, the idea that “humans have values” underlies a lot of thinking in the field; it appears again and again, sometimes popping up as an uncritically accepted truth. Thus, it deserves a thorough deconstruction, (...)
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  24. 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 such prediction is the analysis of the convergent drives of any future AI, started by Omohundro. We show that one of the convergent drives of AI is a militarization drive, arising from AI’s need to wage a war against its potential rivals by either physical or software means, or to increase its bargaining power. (...)
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  25. AI with Alien Content and Alien Metasemantics.Herman Cappelen & Joshua Dever - forthcoming - In Ernest Lepore (ed.), Oxford Handbook of Applied Philosophy of Language. OUP.
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  26.  76
    Explainable AI Lacks Regulative Reasons: Why AI and Human Decision‑Making Are Not Equally Opaque.Uwe Peters - forthcoming - AI and Ethics.
    Many artificial intelligence (AI) systems currently used for decision-making are opaque, i.e., the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity. In response to this problem, several researchers have argued that human decision-making is equally opaque and since simplifying, reason-giving explanations (rather than exhaustive causal accounts) of a decision are typically viewed as sufficient in the human case, the same should hold for algorithmic decision-making. Here, I contend that this argument (...)
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  27. Designing AI with Rights, Consciousness, Self-Respect, and Freedom.Eric Schwitzgebel & Mara Garza - 2020 - In Ethics of Artificial Intelligence. New York, NY, USA: pp. 459-479.
    We propose four policies of ethical design of human-grade Artificial Intelligence. Two of our policies are precautionary. Given substantial uncertainty both about ethical theory and about the conditions under which AI would have conscious experiences, we should be cautious in our handling of cases where different moral theories or different theories of consciousness would produce very different ethical recommendations. Two of our policies concern respect and freedom. If we design AI that deserves moral consideration equivalent to that of human beings, (...)
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  28.  72
    RESPONSIBLE AI: INTRODUCTION OF “NOMADIC AI PRINCIPLES” FOR CENTRAL ASIA.Ammar Younas - 2020 - Conference Proceeding of International Conference Organized by Jizzakh Polytechnical Institute Uzbekistan.
    We think that Central Asia should come up with its own AI Ethics Principles which we propose to name as “Nomadic AI Principles”.
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  29. 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 sources of error in moral judgment, including ignorance, confusion, and bias. It surveys three existing proposals for building human morality into AI: Top-down, bottom-up, and hybrid approaches. Then it proposes a multi-step, hybrid method, using the example of kidney allocations for transplants as a test case. The paper concludes with brief remarks about how (...)
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  30. 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. Many trends already well underway involve the offloading of cognitive, emotional, and ethical labor to AI software in myriad social, civil, personal, and professional contexts. Gradually, we may lose the inclination and capacity to engage in critically reflective thought, making us more cognitively and emotionally vulnerable and thus more anxious and prone to manipulation (...)
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  31. Why AI Will Never Rule the World (Interview).Luke Dormehl, Jobst Landgrebe & Barry Smith - 2022 - Digital Trends.
    Call it the Skynet hypothesis, Artificial General Intelligence, or the advent of the Singularity — for years, AI experts and non-experts alike have fretted (and, for a small group, celebrated) the idea that artificial intelligence may one day become smarter than humans. -/- According to the theory, advances in AI — specifically of the machine learning type that’s able to take on new information and rewrite its code accordingly — will eventually catch up with the wetware of the biological brain. (...)
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  32. 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 to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these days, (...)
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  33. 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 (...)
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  34. 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, our subjectivity, our essence as transcendent beings. With each advance, they steal our freedom and dignity. Who are these denizens of darkness, these usurpers of all that is good and holy? None other than humanity’s arch-foe: The Cognitive Scientists -- AI researchers, fallen philosophers, psychologists, and other benighted lovers of computers. Unless they are (...)
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  35. The AI Gambit — Leveraging 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 AI offers in this domain: it can help improve and expand current understanding of climate change and it contribute to combating the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the (...)
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  36. Combating Disinformation with AI: Epistemic and Ethical Challenges.Benjamin Lange & Ted Lechterman - 2021 - IEEE International Symposium on Ethics in Engineering, Science and Technology (ETHICS) 1:1-5.
    AI-supported methods for identifying and combating disinformation are progressing in their development and application. However, these methods face a litany of epistemic and ethical challenges. These include (1) robustly defining disinformation, (2) reliably classifying data according to this definition, and (3) navigating ethical risks in the deployment of countermeasures, which involve a mixture of harms and benefits. This paper seeks to expose and offer preliminary analysis of these challenges.
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  37.  65
    “Excavating AI” Re-Excavated: Debunking a Fallacious Account of the JAFFE Dataset.Michael J. Lyons - 2021 - arXiv 2107:1-20.
    Twenty-five years ago, my colleagues Miyuki Kamachi and Jiro Gyoba and I designed and photographed JAFFE, a set of facial expression images intended for use in a study of face perception. In 2019, without seeking permission or informing us, Kate Crawford and Trevor Paglen exhibited JAFFE in two widely publicized art shows. In addition, they published a nonfactual account of the images in the essay “Excavating AI: The Politics of Images in Machine Learning Training Sets.” The present article recounts the (...)
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  38.  31
    AI-Assisted Euthanasia and the Issue of Autonomy.Tam-Tri Le - 2022 - Mindsponge Portal.
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  39. Making AI Philosophical Again: On Philip E. Agre's Legacy.Jethro Masís - 2014 - Continent 4 (1):58-70.
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  40.  30
    AI’s Role in Creative Processes: A Functionalist Approach.Leonardo Arriagada & Gabriela Arriagada-Bruneau - 2022 - Odradek. Studies in Philosophy of Literature, Aesthetics, and New Media Theories 8 (1):77-110.
    From 1950 onwards, the study of creativity has not stopped. Today, AI has revitalised debates on the subject. That is especially controversial in the artworld, as the 21st century already features AI-generated artworks. Without discussing issues about AI agency, this article argues for AI’s creativity. For this, we first present a new functionalist understanding of Margaret Boden’s definition of creativity. This is followed by an analysis of empirical evidence on anthropocentric barriers in the perception of AI’s creative capabilities, which is (...)
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  41.  78
    AI Powered Anti-Cyber Bullying System Using Machine Learning Algorithm of Multinomial Naïve Bayes and Optimized Linear Support Vector Machine.Tosin Ige & Sikiru Adewale - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 5.
    Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue.” ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation (...)
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  42.  97
    AI Powered Anti-Cyber Bullying System Using Machine Learning Algorithm of Multinomial Naïve Bayes and Optimized Linear Support Vector Machine.Tosin Ige - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 5.
    Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue.” ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation (...)
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  43. Narrow AI Nanny: Reaching Strategic Advantage Via Narrow AI to Prevent Creation of the Dangerous Superintelligence.Alexey Turchin - manuscript
    Abstract: As there are no currently obvious ways to create safe self-improving superintelligence, but its emergence is looming, we probably need temporary ways to prevent its creation. The only way to prevent it is to create a special type of AI that is able to control and monitor the entire world. The idea has been suggested by Goertzel in the form of an AI Nanny, but his Nanny is still superintelligent, and is not easy to control. We explore here ways (...)
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  44. 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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  45. Classical AI Linguistic Understanding and the Insoluble Cartesian Problem.Rodrigo González - 2020 - AI and Society 35 (2):441-450.
    This paper examines an insoluble Cartesian problem for classical AI, namely, how linguistic understanding involves knowledge and awareness of u’s meaning, a cognitive process that is irreducible to algorithms. As analyzed, Descartes’ view about reason and intelligence has paradoxically encouraged certain classical AI researchers to suppose that linguistic understanding suffices for machine intelligence. Several advocates of the Turing Test, for example, assume that linguistic understanding only comprises computational processes which can be recursively decomposed into algorithmic mechanisms. Against this background, in (...)
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  46.  69
    AI and Medicine.Mihai Nadin - unknown
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  47. The AI Human Condition is a Dilemma Between Authenticity and Freedom.James Brusseau - manuscript
    Big data and predictive analytics applied to economic life is forcing individuals to choose between authenticity and freedom. The fact of the choice cuts philosophy away from the traditional understanding of the two values as entwined. This essay describes why the split is happening, how new conceptions of authenticity and freedom are rising, and the human experience of the dilemma between them. Also, this essay participates in recent philosophical intersections with Shoshana Zuboff’s work on surveillance capitalism, but the investigation connects (...)
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  48.  56
    AI, Opacity, and Personal Autonomy.Bram Vaassen - 2022 - Philosophy and Technology 35 (4):1-20.
    Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive a (...)
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  49.  75
    Ethical Funding for Trustworthy AI: Proposals to Address the Responsibilities of Funders to Ensure That Projects Adhere to Trustworthy AI Practice.Marie Oldfield - 2021 - AI and Ethics 1 (1):1.
    AI systems that demonstrate significant bias or lower than claimed accuracy, and resulting in individual and societal harms, continue to be reported. Such reports beg the question as to why such systems continue to be funded, developed and deployed despite the many published ethical AI principles. This paper focusses on the funding processes for AI research grants which we have identified as a gap in the current range of ethical AI solutions such as AI procurement guidelines, AI impact assessments and (...)
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  50. 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 a technology without exaggeration. Through discussion of previous AI winters, this paper examines the hype cycle (which by turn characterises AI as a social panacea or a nightmare of apocalyptic proportions) and argues that AI should be treated as a normal technology, neither as a miracle nor as a plague, but rather as of (...)
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