Philosophy of Artificial Intelligence

Edited by Eric Dietrich (State University of New York at Binghamton)
Assistant editor: Michelle Thomas (University of Western Ontario)
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Summary

The philosophy of artificial intelligence is a collection of issues primarily concerned with whether or not AI is possible -- with whether or not it is possible to build an intelligent thinking machine.  Also of concern is whether humans and other animals are best thought of as machines (computational robots, say) themselves. The most important of the "whether-possible" problems lie at the intersection of theories of the semantic contents of thought and the nature of computation. A second suite of problems surrounds the nature of rationality. A third suite revolves around the seeming “transcendent” reasoning powers of the human mind. These problems derive from Kurt Gödel's famous Incompleteness Theorem.  A fourth collection of problems concerns the architecture of an intelligent machine.  Should a thinking computer use discrete or continuous modes of computing and representing, is having a body necessary, and is being conscious necessary.  This takes us to the final set of questions. Can a computer be conscious?  Can a computer have a moral sense? Would we have duties to thinking computers, to robots?  For example, is it moral for humans to even attempt to build an intelligent machine?  If we did build such a machine, would turning it off be the equivalent of murder?  If we had a race of such machines, would it be immoral to force them to work for us?

Key works Probably the most important attack on whether AI is possible is John Searle's famous Chinese Room Argument: Searle 1980.  This attack focuses on the semantic aspects (mental semantics) of thoughts, thinking, and computing.   For some replies to this argument, see the same 1980 journal issue as Searle's original paper.  For the problem of the nature of rationality, see Pylyshyn 1987.  An especially strong attack on AI from this angle is Jerry Fodor's work on the frame problem: Fodor 1987.  On the frame problem in general, see McCarthy & Hayes 1969.  For some replies to Fodor and advances on the frame problem, see Ford & Pylyshyn 1996.  For the transcendent reasoning issue, a central and important paper is Hilary Putnam's Putnam 1960.  This paper is arguably the source for the computational turn in 1960s-70s philosophy of mind.  For architecture-of-mind issues, see, for starters: M. Spivey's The Contintuity of Mind, Oxford, which argues against the notion of discrete representations. See also, Gelder & Port 1995.  For an argument for discrete representations, see, Dietrich & Markman 2003.  For an argument that the mind's boundaries do not end at the body's boundaries, see, Clark & Chalmers 1998.  For a statement of and argument for computationalism -- the thesis that the mind is a kind of computer -- see Shimon Edelman's excellent book Edelman 2008. See also Chapter 9 of Chalmers's book Chalmers 1996.
Introductions Chinese Room Argument: Searle 1980. Frame problem: Fodor 1987, Computationalism and Godelian style refutation: Putnam 1960. Architecture: M. Spivey's The Contintuity of Mind, Oxford and Shimon Edelman's Edelman 2008. Ethical issues: Anderson & Anderson 2011 and Müller 2020.  Conscious computers: Chalmers 2011.
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  1. Was ist, was kann, was soll KI? Ein philosophisches Gespräch.Vincent C. Müller & Martin Hähnel - 2024 - Hamburg: Felix Meiner.
    Teil I: Philosophie und KI Teil II: Ethik, Recht und Ökonomie der KI Teil III: KI zwischen Öffentlichkeit und persönlicher Lebenswelt Teil IV: Letzte Fragen.
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  2. Community, solidarity and care through data? An ethical analysis of the interpersonal dimension of self-tracking.Michał Wieczorek - forthcoming - AI and Society:1-13.
    This paper discusses the interpersonal dimension of self-tracking technologies from the standpoint of Dewey’s pragmatist ethics. Users of self-tracking routinely exchange data with others, interact through social features embedded in their tools, and form communities focused on the sharing and discussion of data. I employ Dewey’s notion of transaction to discuss how self-quantification impacts users’ perception of others and how it mediates interpersonal relations. In Dewey’s ethics engagement with others is a fundamental part of moral life and individual flourishing can (...)
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  3. Toward a Responsible Fairness Analysis: From Binary to Multiclass and Multigroup Assessment in Graph Neural Network-Based User Modeling Tasks.Erasmo Purificato, Ludovico Boratto & Ernesto William De Luca - 2024 - Minds and Machines 34 (3):1-34.
    User modeling is a key topic in many applications, mainly social networks and information retrieval systems. To assess the effectiveness of a user modeling approach, its capability to classify personal characteristics (e.g., the gender, age, or consumption grade of the users) is evaluated. Due to the fact that some of the attributes to predict are multiclass (e.g., age usually encompasses multiple ranges), assessing fairness in user modeling becomes a challenge since most of the related metrics work with binary attributes. As (...)
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  4. The meaningfulness gap in AI ethics: a guide on how to think through a complex challenge.Markus Rüther - forthcoming - AI and Society:1-13.
    Technological outsourcing is increasingly prevalent, with AI systems taking over many tasks once performed by humans. This shift has led to various discussions within AI ethics. A question that was largely ignored until recently, but is now increasingly being discussed, concerns the meaningfulness of such a lifestyle. The literature largely features skeptical views, raising several challenges. Many of these challenges can be grouped under what I identify as the “meaningfulness gap”. Although this gap is widely acknowledged, there is a notable (...)
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  5. Guiding the way: a comprehensive examination of AI guidelines in global media.Mathias-Felipe de-Lima-Santos, Wang Ngai Yeung & Tomás Dodds - forthcoming - AI and Society:1-19.
    With the increasing adoption of artificial intelligence (AI) technologies in the news industry, media organizations have begun publishing guidelines that aim to promote the responsible, ethical, and unbiased implementation of AI-based technologies. These guidelines are expected to serve journalists and media workers by establishing best practices and a framework that helps them navigate ever-evolving AI tools. Drawing on institutional theory and digital inequality concepts, this study analyzes 37 AI guidelines for media purposes in 17 countries. Our analysis reveals key thematic (...)
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  6. Dreaming of AI: environmental sustainability and the promise of participation.Nicolas Zehner & André Ullrich - forthcoming - AI and Society:1-13.
    There is widespread consensus among policymakers that climate change and digitalisation constitute the most pressing global transformations shaping human life in the 21st century. Seeking to address the challenges arising at this juncture, governments, technologists and scientists alike increasingly herald artificial intelligence (AI) as a vehicle to propel climate change mitigation and adaptation. In this paper, we explore the intersection of digitalisation and climate change by examining the deployment of AI in government-led climate action. Building on participant observations conducted in (...)
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  7. On Informational Injustice and Epistemic Exclusions.Abbas Bagwala - 2024 - Synthese 203.
    Information is a unique resource. Asymmetries that arise out of information access or processing capacities, therefore, enable a distinctive form of injustice. This paper builds a working conception of such injustice and explores it further. Let us call it informational injustice. Informational injustice is a consequence of informational asymmetries between at least two agents, which are deeply exacerbated due to modern information and communication technologies but do not necessarily originate with them. Informational injustice is the injustice of having information from (...)
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  8. Neues System der philosophischen Wissenschaften im Grundriss. Band V: Psychologie und Geisteswissenschaft.Dirk Hartmann - 2024 - Paderborn: mentis.
    Hegel called the object of psychology the "subjective spirit" and the object of the humanities the "objective spirit". In accordance with this distinction, the overarching theme of Volume V is the conceptual analysis of the mental and cultural domain in the form of a special philosophy of science of psychology (§25) and a general philosophy of science of the humanities (§26). Regarding psychology, philosophy of science is specifically facing the question: "How is an objective empirical science of the subjective possible?" (...)
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  9. Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena.Timo Freiesleben, Gunnar König, Christoph Molnar & Álvaro Tejero-Cantero - 2024 - Minds and Machines 34 (3):1-39.
    To learn about real world phenomena, scientists have traditionally used models with clearly interpretable elements. However, modern machine learning (ML) models, while powerful predictors, lack this direct elementwise interpretability (e.g. neural network weights). Interpretable machine learning (IML) offers a solution by analyzing models holistically to derive interpretations. Yet, current IML research is focused on auditing ML models rather than leveraging them for scientific inference. Our work bridges this gap, presenting a framework for designing IML methods—termed ’property descriptors’—that illuminate not just (...)
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  10. Machine agency.James Mattingly & Beba Cibralic - 2024 - Cambridge, Massachusetts: The MIT Press. Edited by Beba Cibralic.
    An accessible philosophy of technology textbook intended for interested students who don't necessarily have a background in philosophy of science.
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  11. The disruptive AlphaGeometry: is it the beginning of the end of mathematics education?Quan-Hoang Vuong & Manh-Tung Ho - 2024 - AI and Society:1-3.
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  12. Net versus relative impacts in public policy automation: a conjoint analysis of attitudes of Black Americans.Ryan Kennedy, Amanda Austin, Michael Adams, Carroll Robinson & Peter Salib - forthcoming - AI and Society:1-13.
    The use of algorithms and automated systems, especially those leveraging artificial intelligence (AI), has been exploding in the public sector, but their use has been controversial. Ethicists, public advocates, and legal scholars have debated whether biases in AI systems should bar their use or if the potential net benefits, especially toward traditionally disadvantaged groups, justify even greater expansion. While this debate has become voluminous, no scholars of which we are aware have conducted experiments with the groups affected by these policies (...)
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  13. Mitigating implicit and explicit bias in structured data without sacrificing accuracy in pattern classification.Fabian Hoitsma, Gonzalo Nápoles, Çiçek Güven & Yamisleydi Salgueiro - forthcoming - AI and Society:1-20.
    Using biased data to train Artificial Intelligence (AI) algorithms will lead to biased decisions, discriminating against certain groups or individuals. Bias can be explicit (one or several protected features directly influence the decisions) or implicit (one or several protected features indirectly influence the decisions). Unsurprisingly, biased patterns are difficult to detect and mitigate. This paper investigates the extent to which explicit and implicit against one or more protected features in structured classification data sets can be mitigated simultaneously while retaining the (...)
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  14. Unveiling AI in the courtroom: exploring ChatGPT’s impact on judicial decision-making through a pilot Colombian case study.Riccardo Perona & Yezid Carrillo de la Rosa - forthcoming - AI and Society:1-8.
    This article examines the impact of ChatGPT on judicial reasoning, focusing on a recent Colombian case where the judge utilized ChatGPT in the decision-making process. The case, decided in January 2023, provides a unique “pilot case study” on the subject, as the judge, in the decision, openly referenced the questions he posed to ChatGPT and the responses of the system. The article explores the case’s implications, the initial reactions to it, and its meaning and implications within the evolving Colombian legal (...)
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  15. Risk and artificial general intelligence.Federico L. G. Faroldi - forthcoming - AI and Society:1-9.
    Artificial General Intelligence (AGI) is said to pose many risks, be they catastrophic, existential and otherwise. This paper discusses whether the notion of risk can apply to AGI, both descriptively and in the current regulatory framework. The paper argues that current definitions of risk are ill-suited to capture supposed AGI existential risks, and that the risk-based framework of the EU AI Act is inadequate to deal with truly general, agential systems.
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  16. Experts or Authorities? The Strange Case of the Presumed Epistemic Superiority of Artificial Intelligence Systems.Andrea Ferrario, Alessandro Facchini & Alberto Termine - 2024 - Minds and Machines 34 (3):1-27.
    The high predictive accuracy of contemporary machine learning-based AI systems has led some scholars to argue that, in certain cases, we should grant them epistemic expertise and authority over humans. This approach suggests that humans would have the epistemic obligation of relying on the predictions of a highly accurate AI system. Contrary to this view, in this work we claim that it is not possible to endow AI systems with a genuine account of epistemic expertise. In fact, relying on accounts (...)
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  17. Submarine Cables and the Risks to Digital Sovereignty.Abra Ganz, Martina Camellini, Emmie Hine, Claudio Novelli, Huw Roberts & Luciano Floridi - 2024 - Minds and Machines 34 (3):1-23.
    The international network of submarine cables plays a crucial role in facilitating global telecommunications connectivity, carrying over 99% of all internet traffic. However, submarine cables challenge digital sovereignty due to their ownership structure, cross-jurisdictional nature, and vulnerabilities to malicious actors. In this article, we assess these challenges, current policy initiatives designed to mitigate them, and the limitations of these initiatives. The nature of submarine cables curtails a state’s ability to regulate the infrastructure on which it relies, reduces its data security, (...)
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  18. Now you see me, now you don’t: why the UK must ban police facial recognition.Jinqian Li - forthcoming - AI and Society:1-2.
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  19. The work of art in the age of AI reproducibility.Misha Rabinovich & Caitlin Foley - forthcoming - AI and Society:1-3.
    Walter Benjamin wrote his prophetic essay, “The Work of Art in the Age of Mechanical Reproduction,” almost a century ago, yet it is still pertinent today. Benjamin warned that as art becomes devoid of aura through reproduction, less attention is needed to engage with it. What role does aura play in AI-generated work? Despite recent advances in AI it produces “artwork” that for the most part operates as entertainment. It can’t produce work that has grown out of reckoning with culture (...)
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  20. Balancing progress and preservation: can AI harmonize efficiency with the human experience in retail?Ashwin Tambe - forthcoming - AI and Society:1-2.
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  21. Intentionality gap and preter-intentionality in generative artificial intelligence.Roberto Redaelli - forthcoming - AI and Society:1-8.
    The emergence of generative artificial intelligence, such as large language models and text-to-image models, has had a profound impact on society. The ability of these systems to simulate human capabilities such as text writing and image creation is radically redefining a wide range of practices, from artistic production to education. While there is no doubt that these innovations are beneficial to our lives, the pervasiveness of these technologies should not be underestimated, and raising increasingly pressing ethical questions that require a (...)
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  22. Autonomous military systems beyond human control: putting an empirical perspective on value trade-offs for autonomous systems design in the military.Christine Boshuijzen-van Burken, Martijn de Vries, Jenna Allen, Shannon Spruit, Niek Mouter & Aylin Munyasya - forthcoming - AI and Society:1-17.
    The question of human control is a key concern in autonomous military systems debates. Our research qualitatively and quantitatively investigates values and concerns of the general public, as they relate to autonomous military systems, with particular attention to the value of human control. Using participatory value evaluation (PVE), we consulted 1980 Australians about which values matter in relation to two specific technologies: an autonomous minesweeping submarine and an autonomous drone that can drop bombs. Based on value sensitive design, participants were (...)
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  23. Imagination machines, Dartmouth-based Turing tests, & a potted history of responses.Melvin Chen - 2020 - AI and Society 35 (1):283-287.
    Mahadevan (2018, AAAI Conference. https://people.cs.umass.edu/~mahadeva/papers/aaai2018-imagination.pdf) proposes that we are at the cusp of imagination science, one of whose primary concerns will be the design of imagination machines. Programs have been written that are capable of generating jokes (Kim Binsted’s JAPE), producing line-drawings that have been exhibited at such galleries as the Tate (Harold Cohen’s AARON), composing music in several styles reminiscent of such greats as Vivaldi and Mozart (David Cope’s Emmy), proving geometry theorems (Herb Gelernter’s IBM program), and inducing quantitative (...)
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  24. Apriori Knowledge in an Era of Computational Opacity: The Role of AI in Mathematical Discovery.Eamon Duede & Kevin Davey - forthcoming - Philosophy of Science.
    Computation is central to contemporary mathematics. Many accept that we can acquire genuine mathematical knowledge of the Four Color Theorem from Appel and Haken's program insofar as it is simply a repetitive application of human forms of mathematical reasoning. Modern LLMs / DNNs are, by contrast, opaque to us in significant ways, and this creates obstacles in obtaining mathematical knowledge from them. We argue, however, that if a proof-checker automating human forms of proof-checking is attached to such machines, then we (...)
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  25. Virtualism: how AI replaces reality.Jan Söffner - forthcoming - AI and Society:1-13.
    This paper traces the shift from the age of realism to the age of virtualism we are currently witnessing. To do so, I draw on older theories announcing this advent (mostly Baudrillard in Simulacra and simulation. Transl. Sheila Glaser. University of Michigan, Ann Arbor, 1994 [1981]; Serres in Atlas. Édition Julliard, Paris, 1994; Virilio in The vision machine. Transl. Rose J. Indiana UP, Bloomington, 1994). I will describe how AI destabilizes fundamental distinctions upon which reality is built—such as the difference (...)
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  26. ‘Worldview’ of the AIGC systems: stability, tendency and polarization.Hexiang Liu - forthcoming - AI and Society:1-14.
    This study aims to investigate the worldview characteristics of current systems of artificial intelligence generated content (AIGC). Eight representative AIGC systems is selected as research objects and elicited responses and ratings to the viewpoints in Devlin’s CWQ worldview scale through a unified questioning approach. Based on the item-by-item ratings provided by the systems, the worldviews reflected from the AIGC systems were analyzed from three aspects: stability, tendency, and polarity. The research found that AIGC systems demonstrate general stability and relatively consistent (...)
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  27. Measure for Measure: Operationalising Cognitive Realism.Majid D. Beni - 2024 - Minds and Machines 34 (3):1-16.
    This paper develops a measure of realism from within the framework of cognitive structural realism (CSR). It argues that in the context of CSR, realism can be operationalised in terms of balance between accuracy and generality. More specifically, the paper draws on the free energy principle to characterise the measure of realism in terms of the balance between accuracy and generality.
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  28. How to identify and address the real-world risks of large language models.Christopher A. Mouton & Caleb Lucas - forthcoming - AI and Society:1-2.
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  29. Personhood for artificial intelligence? A cautionary tale from Idaho and Utah.Tyler L. Jaynes - forthcoming - AI and Society:1-3.
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  30. Unfairness in AI Anti-Corruption Tools: Main Drivers and Consequences.Fernanda Odilla - 2024 - Minds and Machines 34 (3):1-35.
    This article discusses the potential sources and consequences of unfairness in artificial intelligence (AI) predictive tools used for anti-corruption efforts. Using the examples of three AI-based anti-corruption tools from Brazil—risk estimation of corrupt behaviour in public procurement, among public officials, and of female straw candidates in electoral contests—it illustrates how unfairness can emerge at the infrastructural, individual, and institutional levels. The article draws on interviews with law enforcement officials directly involved in the development of anti-corruption tools, as well as academic (...)
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  31. Algorithmic governance and AI: balancing innovation and oversight in Indonesian policy analyst.Bevaola Kusumasari & Bernardo Nugroho Yahya - forthcoming - AI and Society:1-13.
    The objective of this study is to examine the effects of generative artificial intelligence (AI) tools, with a specific focus on ChatGPT, on the analytical proficiencies of policy analysts operating in Indonesia. Considering the increasing intricacies of contemporary governance and the emergence of "wicked problems," this study investigates the potential of AI to facilitate the development of inventive, data-centric public policies. Involving postgraduate students in a quasi-experimental design, this study investigated the efficacy of ChatGPT in assisting in the development of (...)
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  32. Doubt or punish: on algorithmic pre-emption in acute psychiatry.Chiara Carboni, Rik Wehrens, Romke van der Veen & Antoinette de Bont - forthcoming - AI and Society:1-13.
    Machine learning algorithms have begun to enter clinical settings traditionally resistant to digitalisation, such as psychiatry. This raises questions around how algorithms will be incorporated in professionals’ practices, and with what implications for care provision. This paper addresses such questions by examining the pilot of an algorithm for the prediction of inpatient violence in two acute psychiatric clinics in the Netherlands. Violence is a prominent risk in acute psychiatry, and professional sensemaking, corrective measures (such as patient isolation and sedation), and (...)
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  33. Expert views about missing AI narratives: is there an AI story crisis?Jennifer Chubb, Darren Reed & Peter Cowling - 2024 - AI and Society 39 (3):1107-1126.
    Stories are an important indicator of our vision of the future. In the case of artificial intelligence (AI), dominant stories are polarized between notions of threat and myopic solutionism. The central storytellers—big tech, popular media, and authors of science fiction—represent particular demographics and motivations. Many stories, and storytellers, are missing. This paper details the accounts of missing AI narratives by leading scholars from a range of disciplines interested in AI Futures. Participants focused on the gaps between dominant narratives and the (...)
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  34. EDIBLE MUSHROOMS AND THEIR CULTIVATION.Ali Mubashar - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):98-144.
    Wild mushrooms are of great significance to people of places where they naturally occur, as they provide an essential source of nutrition and contribute to the local economy. Multiple studies have conducted significant studies and classified many kinds of mushrooms to show their unique characteristics. Pleurites spp. and Lentinula eddoes are commonly cultivated plants valued for their floral properties. Mushrooms contain a variety of carbohydrates. Certain carbohydrates have shown the ability to reduce the risk of cancer and prevent the immune (...)
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  35. Graves' Disease: Current Knowledge and Management.Ghaffar Irum - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):145-156.
    This review was conducted to examine the causes, diagnoses, clinical manifestations, and available treatments for Graves' disease. Keywords like "Graves' disease," "radioactive iodine," "etiology," and "treatment" were used to search for data pertaining to Textbooks on endocrinology and other papers from these sources were also located. The introduction, etiology, risk factors, symptoms, diagnosis, course of treatment, and the contribution of many factors to the beginning of Graves' disease are all covered in this review article.
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  36. Consumption of flowers and their medicinal properties.Laila Umme - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):157-175.
    The human being has selected a variety of domesticated plants that gives a benefit, and also significant in food production. The origin of these plants mostly in Central Asia such as China having great variety of crops such as oats, barley, sesame, pumpkin, sorghum, asparagus, pear, apple and citrus etc. While centers of origin such as Mexico and Central America have great diversity in corn, beans, squash, maguey, nopal, sunflower, avocado, cocoa etc. In many countries poor nutrition is a current (...)
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  37. Human Autonomy at Risk? An Analysis of the Challenges from AI.Carina Prunkl - 2024 - Minds and Machines 34 (3):1-21.
    Autonomy is a core value that is deeply entrenched in the moral, legal, and political practices of many societies. The development and deployment of artificial intelligence (AI) have raised new questions about AI’s impacts on human autonomy. However, systematic assessments of these impacts are still rare and often held on a case-by-case basis. In this article, I provide a conceptual framework that both ties together seemingly disjoint issues about human autonomy, as well as highlights differences between them. In the first (...)
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  38. EXPLORING SERVER-LESS COMPUTING FOR EFFICIENT RESOURCE MANAGEMENT IN CLOUD ARCHITECTURES.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):77-83.
    Server-less computing, also known as Function as a Service (FaaS), revolutionizes cloud architecture by allowing developers to focus on code and functionality without managing underlying infrastructure. This paradigm enhances resource management efficiency by dynamically allocating resources only when needed, thus optimizing cost and performance. Server-less models, epitomized by platforms like AWS Lambda, Google Cloud Functions, and Azure Functions, provide automatic scaling and fine-grained billing, making them ideal for applications with variable workloads. While challenges such as cold start latency and complex (...)
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  39. OPTIMIZING DATA SCIENCE WORKFLOWS IN CLOUD COMPUTING.Tummalachervu Chaitanya Kanth - 2024 - Journal of Science Technology and Research (JSTAR) 4 (1):71-76.
    This paper explores the challenges and innovations in optimizing data science workflows within cloud computing environments. It begins by highlighting the critical role of data science in modern industries and the pivotal contribution of cloud computing in enabling scalable and efficient data processing. The primary focus lies in identifying and analyzing the key challenges encountered in current data science workflows deployed in cloud infrastructures. These challenges include scalability issues related to handling large volumes of data, resource management complexities in optimizing (...)
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  40. EFFICIENT STRATEGIES FOR SEAMLESS CLOUD MIGRATIONS USING ADVANCED DEPLOYMENT AUTOMATIONS.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):61-70.
    The increasing complexity and scale of modern computing needs have led to the development and adoption of cloud computing as a ubiquitous paradigm for data storage and processing. The hybrid cloud model, which combines both public and private cloud infrastructures, has been particularly appealing to organizations that require both the scalability offered by public clouds and the security features of private clouds. Various strategies for configuring and managing resources have been developed to optimize the hybrid cloud environment. These strategies aim (...)
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  41. The pitfalls of probes: are our earthly ethical principles lost in space?Helen Smith - forthcoming - AI and Society:1-3.
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  42. CONTEMPORARY DEVOPS STRATEGIES FOR AUGMENTING SCALABLE AND RESILIENT APPLICATION DEPLOYMENT ACROSS MULTI-CLOUD ENVIRONMENTS.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):54-60.
    Containerization in a multi-cloud environment facilitates workload portability and optimized resource uti-lization. Containerization in multi-cloud environments has received significant attention in recent years both from academic research and industrial development perspectives. However, there exists no effort to systematically investigate the state of research on this topic. The aim of this research is to systematically identify and categorize the multiple aspects of containerization in multi-cloud environment. We conducted the Systematic Mapping Study (SMS) on the literature published between January 2013 and March (...)
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  43. SOLVING CLOUD VULNERABILITIES: ARCHITECTING AIPOWERED CYBERSECURITY SOLUTIONS FOR ENHANCED PROTECTION.Sanagana Durga Prasada Rao - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):84-90.
    The rapid adoption of cloud computing has revolutionized the way organizations operate, offering unparalleled flexibility, scalability, and efficiency. However, it also introduces a new set of vulnerabilities and security challenges. This manuscript explores the integration of artificial intelligence (AI) in cybersecurity solutions to address these cloud vulnerabilities. By examining the current landscape, AI methodologies, and practical implementation strategies, we aim to provide a roadmap for enhancing cloud security through AI-powered solutions. -/- .
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  44. HARNESSING AI FOR EVOLVING THREATS: FROM DETECTION TO AUTOMATED RESPONSE.Sanagana Durga Prasada Rao - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):91-97.
    The landscape of cybersecurity is constantly evolving, with adversaries becoming increasingly sophisticated and persistent. This manuscript explores the utilization of artificial intelligence (AI) to address these evolving threats, focusing on the journey from threat detection to autonomous response. By examining AI-driven detection methodologies, advanced threat analytics, and the implementation of autonomous response systems, this paper provides insights into how organizations can leverage AI to strengthen their cybersecurity posture against modern threats. Key words: Ransomware, Anomaly Detection, Advanced Persistent Threats (APTs), Automated (...)
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  45. “The Human Must Remain the Central Focus”: Subjective Fairness Perceptions in Automated Decision-Making.Daria Szafran & Ruben L. Bach - 2024 - Minds and Machines 34 (3):1-37.
    The increasing use of algorithms in allocating resources and services in both private industry and public administration has sparked discussions about their consequences for inequality and fairness in contemporary societies. Previous research has shown that the use of automated decision-making (ADM) tools in high-stakes scenarios like the legal justice system might lead to adverse societal outcomes, such as systematic discrimination. Scholars have since proposed a variety of metrics to counteract and mitigate biases in ADM processes. While these metrics focus on (...)
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  46. AI governance: a review of the Oxford handbook of AI governance. [REVIEW]Vahid Nick Pay - forthcoming - AI and Society:1-3.
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  47. Artificial Intelligence and content analysis: the large language models (LLMs) and the automatized categorization.Ana Carolina Carius & Alex Justen Teixeira - forthcoming - AI and Society:1-12.
    The growing advancement of Artificial Intelligence models based on deep learning and the consequent popularization of large language models (LLMs), such as ChatGPT, place the academic community facing unprecedented dilemmas, in addition to corroborating questions involving research activities and human beings. In this work, Content Analysis was chosen as the object of study, an important technique for analyzing qualitative data and frequently used among Brazilian researchers. The objective of this work was to compare the process of categorization by themes carried (...)
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  48. Computational frameworks for zoonotic disease control in Society 5.0: opportunities, challenges and future research directions. [REVIEW]Anil Kumar Bag & Diganta Sengupta - forthcoming - AI and Society:1-30.
    This study investigates the intersection of existing computational frameworks for zoonotic disease control within the emerging societal paradigm, Society 5.0. Technologies in human-centric computing can facilitate real-time data collection and analysis, enabling early detection and rapid response to zoonotic disease outbreaks, thereby enhancing surveillance and containment efforts for public health protection. It aims to explore challenges and opportunities within these frameworks and delineate future research directions to serve as a benchmark. Conducting a three-layered analysis, the study identifies high-level technologies, second-layer (...)
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  49. Robotics in place and the places of robotics: productive tensions across human geography and human–robot interaction.Casey R. Lynch, Bethany N. Manalo & Àlex Muñoz-Viso - forthcoming - AI and Society:1-14.
    Bringing human–robot interaction (HRI) into conversation with scholarship from human geography, this paper considers how socially interactive robots become important agents in the production of social space and explores the utility of core geographic concepts of _scale_ and _place_ to critically examine evolving robotic spatialities. The paper grounds this discussion through reflections on a collaborative, interdisciplinary research project studying the development and deployment of interactive museum tour-guiding robots on a North American university campus. The project is a collaboration among geographers, (...)
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  50. Anthropomorphizing Machines: Reality or Popular Myth?Simon Coghlan - 2024 - Minds and Machines 34 (3):1-25.
    According to a widespread view, people often anthropomorphize machines such as certain robots and computer and AI systems by erroneously attributing mental states to them. On this view, people almost irresistibly believe, even if only subconsciously, that machines with certain human-like features really have phenomenal or subjective experiences like sadness, happiness, desire, pain, joy, and distress, even though they lack such feelings. This paper questions this view by critiquing common arguments used to support it and by suggesting an alternative explanation. (...)
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