Results for 'Jingyi Ai'

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  1.  4
    Cardiorespiratory Fitness, Age, and Multiple Aspects of Executive Function Among Preadolescent Children.Zhuxuan Zhan, Jingyi Ai, Feifei Ren, Lin Li, Chien-Heng Chu & Yu-Kai Chang - 2020 - Frontiers in Psychology 11.
  2.  2
    Acute High-Intensity Interval Exercise Improves Inhibitory Control Among Young Adult Males With Obesity.Chun Xie, Brandon L. Alderman, Fanying Meng, Jingyi Ai, Yu-Kai Chang & Anmin Li - 2020 - Frontiers in Psychology 11.
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  3.  27
    Anthropomorphizing AlphaGo: A Content Analysis of the Framing of Google DeepMind’s AlphaGo in the Chinese and American Press.Nathaniel Ming Curran, Jingyi Sun & Joo-Wha Hong - 2020 - AI and Society 35 (3):727-735.
    This article conducts a mixed-method content analysis of Chinese and American news media coverage of Google DeepMind’s Go playing computer program, AlphaGo. Drawing on humanistic approaches to artificial intelligence, combined with an empirically rigorous content analysis, it examines the differences and overlap in coverage by the Chinese and American press in their accounts of AlphaGo, and its historic match with Korea’s Lee Sedol in March, 2016. The event was not only followed intensely in China, but also made the front page (...)
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  4. Ai Silin Lun Wen Xuan.Silin Ai - 2011 - Zhonghua Shu Ju.
  5. Epistemic Advantage on the Margin: A Network Standpoint Epistemology.Jingyi Wu - 2022 - Philosophy and Phenomenological Research:1-23.
    ​I use network models to simulate social learning situations in which the dominant group ignores or devalues testimony from the marginalized group. I find that the marginalized group ends up with several epistemic advantages due to testimonial ignoration and devaluation. The results provide one possible explanation for a key claim of standpoint epistemology, the inversion thesis, by casting it as a consequence of another key claim of the theory, the unidirectional failure of testimonial reciprocity. Moreover, the results complicate the understanding (...)
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  6.  17
    How Should We Promote Transient Diversity in Science?Jingyi Wu & Cailin O'Connor - manuscript
    Diversity of practice is widely recognized as crucial to scientific progress. If all scientists perform the same tests in their research, they might miss important insights that other tests would yield. If all scientists adhere to the same theories, they might fail to explore other options which, in turn, might be superior. But the mechanisms that lead to this sort of diversity can also generate epistemic harms when scientific communities fail to reach swift consensus on successful theories. In this paper, (...)
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  7. AI for Social Good, AI for Datong.Pak-Hang Wong - 2021 - Informatio 26 (1):42-57.
    The Chinese government and technology companies assume a proactive stance towards digital technologies and AI and their roles in users’—and more generally, people’s—lives. This vision of ‘Tech for Good’, i.e., the development of good digital technologies and AI or the application of them for good, is also shared by major technology companies in the globe, e.g., Google, Microsoft, and Facebook. Interestingly, these initiatives have invited a number of critiques for their feasibility and desirability, particularly in relation to the social and (...)
     
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  8. Effects of Culture on the Balance Between Mathematics Achievement and Subjective Wellbeing.Jingyi Meng & Simiao Liu - 2022 - Frontiers in Psychology 13.
    Previous studies suggested that culture have impact on students' mathematics achievement and subjective wellbeing, but few investigated the effects of culture on the balance between them. Drawing on Hofstede's cultural dimensions theory, this study investigated the effects of culture on balance between students' mathematics achievement and subjective wellbeing. Results showed the significant effects of cultural dimensions of long-term orientation vs. short-term orientation and indulgence vs. restraint. Students from countries of high long-term orientation and low indulgence culture were more likely to (...)
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  9.  1
    The Significance of Green Entrepreneurial Self-Efficacy: Mediating and Moderating Role of Green Innovation and Green Knowledge Sharing Culture.Jingyi Guo - 2022 - Frontiers in Psychology 13.
    Green entrepreneurial self-efficacy refers to individuals’ conviction that they can contribute to solving environmental issues and shows self-assurance in their efforts to protect the environment. The present investigation attempts to determine the role of employees’ green ESE in the green innovation of SMEs. It is also proposed that GI positively impacts organizational environmental, economic, and social performance. This study also evaluates the mediating role of GI and moderating role of the green knowledge-sharing culture. This study tested the hypothesis using a (...)
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  10. 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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  11.  7
    The Path to Innovation: The Antecedent Perspective of Intellectual Capital and Organizational Character.Jingyi Li & Dengke Yu - 2018 - Frontiers in Psychology 9.
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  12. The Writing of Innocence: Blanchot and the Deconstruction of Christianity.Aïcha Liviana Messina - 2022 - Albany: State University of New York Press.
    An original reading of Blanchot's thought with far-reaching philosophical and literary implications.
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  13.  5
    A Turn to the Many: Ai Weiwei.Chang Tan & Ai Weiwei - 2021 - Diacritics 49 (1):150-155.
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  14. Explaining Universality: Infinite Limit Systems in the Renormalization Group Method.Jingyi Wu - 2021 - Synthese (5-6):14897-14930.
    I analyze the role of infinite idealizations used in the renormalization group (RG hereafter) method in explaining universality across microscopically different physical systems in critical phenomena. I argue that despite the reference to infinite limit systems such as systems with infinite correlation lengths during the RG process, the key to explaining universality in critical phenomena need not involve infinite limit systems. I develop my argument by introducing what I regard as the explanatorily relevant property in RG explanations: linearization* property; I (...)
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  15.  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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  16. 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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  17.  17
    Eagerness and Optimistically Biased Metaperception: The More Eager to Learn Others’ Evaluations, the Higher the Estimation of Others’ Evaluations.Jingyi Lu, Hebing Duan & Xiaofei Xie - 2018 - Frontiers in Psychology 9.
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  18.  2
    Increased Complexities in Visual Search Behavior in Skilled Players for a Self-Paced Aiming Task.Jingyi S. Chia, Stephen F. Burns, Laura A. Barrett & Jia Y. Chow - 2017 - Frontiers in Psychology 8.
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  19. 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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  20.  18
    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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  21.  33
    Against AI-Improved Personal Memory.Björn Lundgren - 2020 - In Aging between Participation and Simulation. pp. 223–234.
    In 2017, Tom Gruber held a TED talk, in which he presented a vision of improving and enhancing humanity with AI technology. Specifically, Gruber suggested that an AI-improved personal memory (APM) would benefit people by improving their “mental gain”, making us more creative, improving our “social grace”, enabling us to do “science on our own data about what makes us feel good and stay healthy”, and, for people suffering from dementia, it “could make a difference between a life of isolation (...)
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  22. AI As a Moral Right-Holder.Joseph Bowen & John Basl - 2020 - In Markus Dubber, Frank Pasquale & Sunit Das (eds.), The Oxford Handbook of Ethics of AI. New York: Oxford University Press.
    This chapter evaluates whether AI systems are or will be rights-holders, explaining the conditions under which people should recognize AI systems as rights-holders. It develops a skeptical stance toward the idea that current forms of artificial intelligence are holders of moral rights, beginning with an articulation of one of the most prominent and most plausible theories of moral rights: the Interest Theory of rights. On the Interest Theory, AI systems will be rights-holders only if they have interests or a well-being. (...)
     
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  23. Language of Conflict: Discourses of the Ukrainian Crisis.Jingyi Huang - forthcoming - Critical Discourse Studies:1-3.
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  24. 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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  25.  44
    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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  26.  42
    Apocalyptic Ai: Visions of Heaven in Robotics, Artificial Intelligence, and Virtual Reality.Robert Geraci - 2010 - Oup Usa.
    Apocalyptic AI, the hope that we might one day upload our minds into machines and live forever in cyberspace, has become commonplace. This view now affects robotics and AI funding, play in online games, and philosophical and theological conversations about morality and human dignity.
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  27.  20
    Acceleration AI Ethics, the Debate Between Innovation and Safety, and Stability AI’s Diffusion Versus OpenAI’s Dall-E.James Brusseau - manuscript
    One objection to conventional AI ethics is that it slows innovation. This presentation responds by reconfiguring ethics as an innovation accelerator. The critical elements develop from a contrast between Stability AI’s Diffusion and OpenAI’s Dall-E. By analyzing the divergent values underlying their opposed strategies for development and deployment, five conceptions are identified as common to acceleration ethics. Uncertainty is understood as positive and encouraging, rather than discouraging. Innovation is conceived as intrinsically valuable, instead of worthwhile only as mediated by social (...)
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  28. 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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  29.  71
    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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  30.  55
    Making AI Intelligible: Philosophical Foundations.Herman Cappelen & Josh Dever - 2021 - New York, USA: Oxford University Press.
    Can humans and artificial intelligences share concepts and communicate? Making AI Intelligible shows that philosophical work on the metaphysics of meaning can help answer these questions. Herman Cappelen and Josh Dever use the externalist tradition in philosophy to create models of how AIs and humans can understand each other. In doing so, they illustrate ways in which that philosophical tradition can be improved. The questions addressed in the book are not only theoretically interesting, but the answers have pressing practical implications. (...)
  31.  48
    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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  32.  54
    Responsible AI: Two Frameworks for Ethical Design and Practice.Dorian Peters, Karina Vold, Diana Robinson & Rafael Calvo - 2020 - IEEE Transactions on Technology and Society 1 (1).
    In 2019, the IEEE launched the P7000 standards projects intended to address ethical issues in the design of autonomous and intelligent systems. This move came amidst a growing public concern over the unintended consequences of artificial intelligence (AI), compounded by the lack of an anticipatory process for attending to ethical impact within professional practice. However, the difficulty in moving from principles to practice presents a significant challenge to the implementation of ethical guidelines. Herein, we describe two complementary frameworks for integrating (...)
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  33. 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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  34. Feminist AI: Can We Expect Our AI Systems to Become Feminist?Galit Wellner & Tiran Rothman - 2020 - Philosophy and Technology 33 (2):191-205.
    The rise of AI-based systems has been accompanied by the belief that these systems are impartial and do not suffer from the biases that humans and older technologies express. It becomes evident, however, that gender and racial biases exist in some AI algorithms. The question is where the bias is rooted—in the training dataset or in the algorithm? Is it a linguistic issue or a broader sociological current? Works in feminist philosophy of technology and behavioral economics reveal the gender bias (...)
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  35.  16
    Rebooting Ai: Building Artificial Intelligence We Can Trust.Gary Marcus & Ernest Davis - 2019 - Vintage.
    Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the (...)
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  36.  28
    AI Systems and Respect for Human Autonomy.Arto Laitinen & Otto Sahlgren - 2021 - Frontiers in Artificial Intelligence.
    This study concerns the sociotechnical bases of human autonomy. Drawing on recent literature on AI ethics, philosophical literature on dimensions of autonomy, and on independent philosophical scrutiny, we first propose a multi-dimensional model of human autonomy and then discuss how AI systems can support or hinder human autonomy. What emerges is a philosophically motivated picture of autonomy and of the normative requirements personal autonomy poses in the context of algorithmic systems. Ranging from consent to data collection and processing, to computational (...)
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  37.  46
    AI Assistants and the Paradox of Internal Automaticity.William A. Bauer & Veljko Dubljević - 2019 - Neuroethics 13 (3):303-310.
    What is the ethical impact of artificial intelligence assistants on human lives, and specifically how much do they threaten our individual autonomy? Recently, as part of forming an ethical framework for thinking about the impact of AI assistants on our lives, John Danaher claims that if the external automaticity generated by the use of AI assistants threatens our autonomy and is therefore ethically problematic, then the internal automaticity we already live with should be viewed in the same way. He takes (...)
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  38. 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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  39.  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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  40.  87
    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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  41. 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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  42. 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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  43. 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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  44. 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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  45. The Effect of Chinese Proficiency on Determining Temporal Adverb Position by Native Japanese Speakers Learning Chinese.Katsuo Tamaoka & Jingyi Zhang - 2022 - Frontiers in Psychology 12.
    The present study aimed to investigate how native Japanese speakers learning Chinese choose preferred positions for temporal adverbs depending on their level of Chinese proficiency. A naturalness judgment task conducted on native Chinese speakers showed that the most natural position for Chinese temporal adverbs was before the subject and that placement after the locative prepositional phrase was incorrect. The same task applied to native Japanese speakers found the most natural position for Japanese temporal adverbs was also before the subject. Further, (...)
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  46.  12
    Ai Love You : Developments in Human-Robot Intimate Relationships.Yuefang Zhou & Martin H. Fischer (eds.) - 2019 - Springer Verlag.
    Using an interdisciplinary approach, this book explores the emerging topics and rapid technological developments of robotics and artificial intelligence through the lens of the evolving role of sex robots, and how they should best be designed to serve human needs. An international panel of authors provides the most up-to-date, evidence-based empirical research on the potential sexual applications of artificial intelligence. Early chapters discuss the objections to sexual activity with robots while also providing a counterargument to each objection. Subsequent chapters present (...)
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  47. Governing AI-Driven Health Research: Are IRBs Up to the Task?Phoebe Friesen, Rachel Douglas-Jones, Mason Marks, Robin Pierce, Katherine Fletcher, Abhishek Mishra, Jessica Lorimer, Carissa Véliz, Nina Hallowell, Mackenzie Graham, Mei Sum Chan, Huw Davies & Taj Sallamuddin - 2021 - Ethics and Human Research 2 (43):35-42.
    Many are calling for concrete mechanisms of oversight for health research involving artificial intelligence (AI). In response, institutional review boards (IRBs) are being turned to as a familiar model of governance. Here, we examine the IRB model as a form of ethics oversight for health research that uses AI. We consider the model's origins, analyze the challenges IRBs are facing in the contexts of both industry and academia, and offer concrete recommendations for how these committees might be adapted in order (...)
     
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  48.  30
    AI Systems Under Criminal Law: a Legal Analysis and a Regulatory Perspective.Francesca Lagioia & Giovanni Sartor - 2020 - Philosophy and Technology 33 (3):433-465.
    Criminal liability for acts committed by AI systems has recently become a hot legal topic. This paper includes three different contributions. The first contribution is an analysis of the extent to which an AI system can satisfy the requirements for criminal liability: accomplishing an actus reus, having the corresponding mens rea, possessing the cognitive capacities needed for responsibility. The second contribution is a discussion of criminal activity accomplished by an AI entity, with reference to a recent case involving an online (...)
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  49.  1
    The Art of Pain: A Quantitative Color Analysis of the Self-Portraits of Frida Kahlo.Federico E. Turkheimer, Jingyi Liu, Erik D. Fagerholm, Paola Dazzan, Marco L. Loggia & Eric Bettelheim - 2022 - Frontiers in Human Neuroscience 16.
    Frida Kahlo was a Mexican artist who is remembered for her self-portraits, pain and passion, and bold, vibrant colors. This work aims to use her life story and her artistic production in a longitudinal study to examine with quantitative tools the effects of physical and emotional pain on artistic expression. Kahlo suffered from polio as a child, was involved in a bus accident as a teenager where she suffered multiple fractures of her spine and had 30 operations throughout her lifetime. (...)
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  50.  90
    In AI We Trust? Perceptions About Automated Decision-Making by Artificial Intelligence.Theo Araujo, Natali Helberger, Sanne Kruikemeier & Claes H. de Vreese - 2020 - AI and Society 35 (3):611-623.
    Fueled by ever-growing amounts of data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, health, and judicial contexts. Data (...)
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