当前期刊: Minds and Machines Go to current issue    加入关注   
显示样式:        排序: IF: - GO 导出
我的关注
我的收藏
您暂时未登录!
登录
  • A Normative Approach to Artificial Moral Agency
    Minds Mach. (IF 1.4) Pub Date : 2020-05-19
    Dorna Behdadi, Christian Munthe

    This paper proposes a methodological redirection of the philosophical debate on artificial moral agency (AMA) in view of increasingly pressing practical needs due to technological development. This “normative approach” suggests abandoning theoretical discussions about what conditions may hold for moral agency and to what extent these may be met by artificial entities such as AI systems and robots.

    更新日期:2020-05-19
  • Moral Gridworlds: A Theoretical Proposal for Modeling Artificial Moral Cognition
    Minds Mach. (IF 1.4) Pub Date : 2020-04-25
    Julia Haas

    I describe a suite of reinforcement learning environments in which artificial agents learn to value and respond to moral content and contexts. I illustrate the core principles of the framework by characterizing one such environment, or “gridworld,” in which an agent learns to trade-off between monetary profit and fair dealing, as applied in a standard behavioral economic paradigm. I then highlight

    更新日期:2020-04-25
  • Towards the Ethical Publication of Country of Origin Information (COI) in the Asylum Process
    Minds Mach. (IF 1.4) Pub Date : 2020-03-28
    Nikita Aggarwal, Luciano Floridi

    This article addresses the question of how ‘Country of Origin Information’ (COI) reports—that is, research developed and used to support decision-making in the asylum process—can be published in an ethical manner. The article focuses on the risk that published COI reports could be misused and thereby harm the subjects of the reports and/or those involved in their development. It supports a situational

    更新日期:2020-04-18
  • The Abstraction/Representation Account of Computation and Subjective Experience
    Minds Mach. (IF 1.4) Pub Date : 2020-03-26
    Jochen Szangolies

    I examine the abstraction/representation theory of computation put forward by Horsman et al., connecting it to the broader notion of modeling, and in particular, model-based explanation, as considered by Rosen. I argue that the ‘representational entities’ it depends on cannot themselves be computational, and that, in particular, their representational capacities cannot be realized by computational

    更新日期:2020-04-18
  • What is a Simulation Model?
    Minds Mach. (IF 1.4) Pub Date : 2020-03-07
    Juan M. Durán

    Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right,

    更新日期:2020-04-18
  • The Physical Mandate for Belief-Goal Psychology
    Minds Mach. (IF 1.4) Pub Date : 2020-03-09
    Simon McGregor, Ron Chrisley

    This article describes a heuristic argument for understanding certain physical systems in terms of properties that resemble the beliefs and goals of folk psychology. The argument rests on very simple assumptions. The core of the argument is that predictions about certain events can legitimately be based on assumptions about later events, resembling Aristotelian ‘final causation’; however, more nuanced

    更新日期:2020-04-18
  • Ethical Implications of Closed Loop Brain Device: 10-Year Review
    Minds Mach. (IF 1.4) Pub Date : 2020-02-18
    Swati Aggarwal, Nupur Chugh

    Closed Loop medical devices such as Closed Loop Deep Brain Stimulation (CL-DBS) and Brain Computer Interface (BCI) are some of the emerging neurotechnologies. New generations of implantable brain–computer interfaces have recently gained success in human clinical trials. These implants detect specific neuronal patterns and provide the subject with information to respond to these patterns. Further, Closed

    更新日期:2020-04-18
  • Dynamical Emergence Theory (DET): A Computational Account of Phenomenal Consciousness
    Minds Mach. (IF 1.4) Pub Date : 2020-01-23
    Roy Moyal, Tomer Fekete, Shimon Edelman

    Scientific theories of consciousness identify its contents with the spatiotemporal structure of neural population activity. We follow up on this approach by stating and motivating Dynamical Emergence Theory (DET), which defines the amount and structure of experience in terms of the intrinsic topology and geometry of a physical system’s collective dynamics. Specifically, we posit that distinct perceptual

    更新日期:2020-04-18
  • A Puzzle concerning Compositionality in Machines
    Minds Mach. (IF 1.4) Pub Date : 2020-02-23
    Ryan M. Nefdt

    This paper attempts to describe and address a specific puzzle related to compositionality in artificial networks such as Deep Neural Networks and machine learning in general. The puzzle identified here touches on a larger debate in Artificial Intelligence related to epistemic opacity but specifically focuses on computational applications of human level linguistic abilities or properties and a special

    更新日期:2020-04-18
  • Ethical Foresight Analysis: What it is and Why it is Needed?
    Minds Mach. (IF 1.4) Pub Date : 2020-03-09
    Luciano Floridi, Andrew Strait

    An increasing number of technology firms are implementing processes to identify and evaluate the ethical risks of their systems and products. A key part of these review processes is to foresee potential impacts of these technologies on different groups of users. In this article, we use the expression Ethical Foresight Analysis (EFA) to refer to a variety of analytical strategies for anticipating or

    更新日期:2020-04-18
  • “ Oh, Dignity too?” Said the Robot: Human Dignity as the Basis for the Governance of Robotics
    Minds Mach. (IF 1.4) Pub Date : 2020-01-07
    Lexo Zardiashvili, Eduard Fosch-Villaronga

    Healthcare robots enable practices that seemed far-fetched in the past. Robots might be the solution to bridge the loneliness that the elderly often experience; they may help wheelchair users walk again, or may help navigate the blind. European Institutions, however, acknowledge that human contact is an essential aspect of personal care and that the insertion of robots could dehumanize caring practices

    更新日期:2020-04-18
  • The Ethics of AI Ethics: An Evaluation of Guidelines
    Minds Mach. (IF 1.4) Pub Date : 2020-02-01
    Thilo Hagendorff

    Current advances in research, development and application of artificial intelligence (AI) systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation

    更新日期:2020-04-18
  • Ethics of AI and Cybersecurity When Sovereignty is at Stake
    Minds Mach. (IF 1.4) Pub Date : 2019-10-11
    Paul Timmers

    Sovereignty and strategic autonomy are felt to be at risk today, being threatened by the forces of rising international tensions, disruptive digital transformations and explosive growth of cybersecurity incidents. The combination of AI and cybersecurity is at the sharp edge of this development and raises many ethical questions and dilemmas. In this commentary, I analyse how we can understand the ethics

    更新日期:2020-04-18
  • A Common Frame for Formal Imagination
    Minds Mach. (IF 1.4) Pub Date : 2019-10-19
    Joan Casas-Roma, M. Elena Rodríguez, Antonia Huertas

    In this paper, we review three influential theories of imagination in order to understand how the dynamics of imagination acts could be modeled using formal languages. While reviewing them, we notice that they are not detailed enough to account for all the mechanisms involved in creating and developing imaginary worlds. We claim those theories could be further refined into what we call the Common Frame

    更新日期:2020-04-18
  • Algorithmic Decision-Making and the Control Problem
    Minds Mach. (IF 1.4) Pub Date : 2019-12-11
    John Zerilli, Alistair Knott, James Maclaurin, Colin Gavaghan

    The danger of human operators devolving responsibility to machines and failing to detect cases where they fail has been recognised for many years by industrial psychologists and engineers studying the human operators of complex machines. We call it “the control problem”, understood as the tendency of the human within a human–machine control loop to become complacent, over-reliant or unduly diffident

    更新日期:2020-04-18
  • A Misdirected Principle with a Catch: Explicability for AI
    Minds Mach. (IF 1.4) Pub Date : 2019-10-15
    Scott Robbins

    There is widespread agreement that there should be a principle requiring that artificial intelligence (AI) be ‘explicable’. Microsoft, Google, the World Economic Forum, the draft AI ethics guidelines for the EU commission, etc. all include a principle for AI that falls under the umbrella of ‘explicability’. Roughly, the principle states that “for AI to promote and not constrain human autonomy, our

    更新日期:2020-04-18
  • The Design of GDPR-Abiding Drones Through Flight Operation Maps: A Win–Win Approach to Data Protection, Aerospace Engineering, and Risk Management
    Minds Mach. (IF 1.4) Pub Date : 2019-11-26
    Eleonora Bassi, Nicoletta Bloise, Jacopo Dirutigliano, Gian Piero Fici, Ugo Pagallo, Stefano Primatesta, Fulvia Quagliotti

    Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation

    更新日期:2020-04-18
  • The Unbearable Shallow Understanding of Deep Learning
    Minds Mach. (IF 1.4) Pub Date : 2019-12-12
    Alessio Plebe, Giorgio Grasso

    This paper analyzes the rapid and unexpected rise of deep learning within Artificial Intelligence and its applications. It tackles the possible reasons for this remarkable success, providing candidate paths towards a satisfactory explanation of why it works so well, at least in some domains. A historical account is given for the ups and downs, which have characterized neural networks research and its

    更新日期:2020-04-18
  • Qualitative Models in Computational Simulative Sciences: Representation, Confirmation, Experimentation
    Minds Mach. (IF 1.4) Pub Date : 2019-05-30
    Nicola Angius

    The Epistemology Of Computer Simulation (EOCS) has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology (ECB) and Agent-Based Modelling (ABM) are examined to show how one may take advantage of qualitative computational models to evaluate

    更新日期:2020-04-18
  • The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence
    Minds Mach. (IF 1.4) Pub Date : 2019-09-21
    David Watson

    Artificial intelligence (AI) has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic

    更新日期:2020-04-18
  • Can Machines Read our Minds?
    Minds Mach. (IF 1.4) Pub Date : 2019-03-27
    Christopher Burr, Nello Cristianini

    We explore the question of whether machines can infer information about our psychological traits or mental states by observing samples of our behaviour gathered from our online activities. Ongoing technical advances across a range of research communities indicate that machines are now able to access this information, but the extent to which this is possible and the consequent implications have not

    更新日期:2020-04-18
  • The Pragmatic Turn in Explainable Artificial Intelligence (XAI)
    Minds Mach. (IF 1.4) Pub Date : 2019-05-29
    Andrés Páez

    In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say

    更新日期:2020-04-18
  • Predictive Processing and the Representation Wars.
    Minds Mach. Pub Date : 2018-01-01
    Daniel Williams

    Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the "representation wars" of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features

    更新日期:2019-11-01
  • Discovering Brain Mechanisms Using Network Analysis and Causal Modeling.
    Minds Mach. Pub Date : 2018-01-01
    Matteo Colombo,Naftali Weinberger

    Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not

    更新日期:2019-11-01
  • Intervention and Identifiability in Latent Variable Modelling.
    Minds Mach. Pub Date : 2018-01-01
    Jan-Willem Romeijn,Jon Williamson

    We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian

    更新日期:2019-11-01
  • AI4People-An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations.
    Minds Mach. Pub Date : 2018-01-01
    Luciano Floridi,Josh Cowls,Monica Beltrametti,Raja Chatila,Patrice Chazerand,Virginia Dignum,Christoph Luetge,Robert Madelin,Ugo Pagallo,Francesca Rossi,Burkhard Schafer,Peggy Valcke,Effy Vayena

    This article reports the findings of AI4People, an Atomium-EISMD initiative designed to lay the foundations for a "Good AI Society". We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations-to assess, to develop, to incentivise, and to support good AI-which

    更新日期:2019-11-01
  • An Analysis of the Interaction Between Intelligent Software Agents and Human Users.
    Minds Mach. Pub Date : 2018-01-01
    Christopher Burr,Nello Cristianini,James Ladyman

    Interactions between an intelligent software agent (ISA) and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user's access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by

    更新日期:2019-11-01
  • Optimal Behavior is Easier to Learn than the Truth.
    Minds Mach. Pub Date : 2016-09-30
    Ronald Ortner

    We consider a reinforcement learning setting where the learner is given a set of possible models containing the true model. While there are algorithms that are able to successfully learn optimal behavior in this setting, they do so without trying to identify the underlying true model. Indeed, we show that there are cases in which the attempt to find the true model is doomed to failure.

    更新日期:2019-11-01
  • A Chance for Attributable Agency.
    Minds Mach. Pub Date : 2015-01-01
    Hans J Briegel,Thomas Müller

    Can we sensibly attribute some of the happenings in our world to the agency of some of the things around us? We do this all the time, but there are conceptual challenges purporting to show that attributable agency, and specifically one of its most important subspecies, human free agency, is incoherent. We address these challenges in a novel way: rather than merely rebutting specific arguments, we discuss

    更新日期:2019-11-01
Contents have been reproduced by permission of the publishers.
导出
全部期刊列表>>
智控未来
聚焦商业经济政治法律
跟Nature、Science文章学绘图
控制与机器人
招募海内外科研人才,上自然官网
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
湖南大学化学化工学院刘松
上海有机所
李旸
南方科技大学
西湖大学
伊利诺伊大学香槟分校
支志明
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug