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Philosophy of Artificial Intelligence
Edited by Eric Dietrich (State University of New York at Binghamton)
Assistant editor: Michelle Thomas (University of Western Ontario)
About this topic
| 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 2012. Conscious computers: Chalmers 2011. |
Show all references
Related
Subcategories
Artificial Minds (2,102 | 391)
The Turing Test (482)
The Chinese Room (270)
Machine Consciousness (370)
The Singularity* (106)
Mind Uploading* (50)
Artificial Minds, Misc (318)
Representation in Artificial Intelligence (841 | 181)
Areas of Artificial Intelligence (1,297 | 293)
Artificial Life* (257)
Computer Vision (10)
Cybernetics (205)
Dynamical Systems (226)
The Frame Problem (90)
Robotics (310)
Ethics of Artificial Intelligence (2,631 | 9)
Algorithmic Fairness (143)
Autonomous Vehicles (24)
Autonomous Weapons (42)
Machine Ethics (532)
Robot Ethics* (482)
Impact of Artificial Intelligence (1,030 | 111)
Autonomous Weapons* (42)
Autonomous Vehicles* (24)
Cyborgs (26)
Mind Uploading (50)
The Singularity (106)
Transhumanism (436)
Contents
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Material to categorize
- NHỮNG TRIẾT LÝ NHÂN VĂN TRONG TẦM NHÌN XÃ HỘI 5.0 TẠI NHẬT BẢN VÀ MỘT VÀI GỢI Ý CHO VIỆT NAM.Manh-Tung Ho & Phuong Thao Luu - manuscriptBài viết này tóm lược các điểm quan trọng và những triết lý xã hội trong Tầm nhìn Xã hội 5.0 (Society 5.0) của Nhật Bản, đồng thời đưa ra bài học cho Việt Nam trong việc hình thành một xã hội “lấy dân làm gốc”, được hiện thực hoá bởi trí tuệ nhân tạo (AI). Nhằm tiến tới một xã hội nơi con người được đặt làm trung tâm đồng thời chung sống hài hoà với công nghệ ngày càng (...)
- Engineering AI for provable retention of objectives over time.Adeniyi Fasoro - 2024 - AI Magazine 45 (2):1-11.I argue that ensuring artificial intelligence (AI) retains alignment with human values over time is critical yet understudied. Most research focuses on static alignment, neglecting crucial retention dynamics enabling stability during learning and autonomy. This paper elucidates limitations constraining provable retention, arguing key gaps include formalizing dynamics, transparency of advanced systems, participatory scaling, and risks of uncontrolled recursive self-improvement. I synthesize technical and ethical perspectives into a conceptual framework grounded in control theory and philosophy to analyze dynamics. I argue priorities (...)
- Book review: Luca Possati (2021): “The algorithmic unconscious: how psychoanalysis helps in understanding AI” (Routledge). [REVIEW]Marc Cheong - 2024 - AI and Society 39 (2):819-821.
- The misdirected approach of open source algorithms.Joshua L. M. Brand - 2024 - AI and Society 39 (2):807-808.
- Algorithmic biases: caring about teens’ neurorights.José M. Muñoz & José Ángel Marinaro - 2024 - AI and Society 39 (2):809-810.
- The scientist of the scientist.Tomer Simon - 2024 - AI and Society 39 (2):803-804.
- Thinking about the mind-technology problem.Manh-Tung Ho - 2024 - AI and Society 39 (2):823-824.
- Neurorights: the Chilean constitutional change.Allan McCay - 2024 - AI and Society 39 (2):797-798.
- Toward the symbiocene through artificial intelligence.Amar Singh & Shipra Tholia - 2024 - AI and Society 39 (2):805-806.
- From the essence of humanity to the essence of intelligence, and AI in the future society.Yehui Zhang - forthcoming - AI and Society:1-9.Fear and concerns regarding AI and robots have existed for a long time, and the emergence of strong artificial intelligence, on par with human intelligence, is likely just a few decades away. The primary purpose of this article is to establish a theoretical framework for navigating the relationship between humans and this advanced form of artificial intelligence. This article first points out that the most fundamental characteristic of life is its continuous process of evolution and iteration. By analyzing the developmental (...)
- Hic sunt leones. User orientation as a design principle for emerging institutions on social media platforms.Lavinia Marin & Constantin Vică - forthcoming - AI and Society:1-14.The phenomenon of missed interactions between online users is a specific issue occurring when users of different language games interact on social media platforms. We use the lens of institutional theory to analyze this phenomenon and argue that current online institutions will necessarily fail to regulate user interactions in a way that creates common meanings because online institutions are not set up to deal with the multiplicity of language games and forms of life co-existing in the online social space. We (...)
- The open texture of ‘algorithm’ in legal language.Davide Baldini & Matteo De Benedetto - forthcoming - AI and Society.In this paper, we will survey the different uses of the term algorithm in contemporary legal practice. We will argue that the concept of algorithm currently exhibits a substantial degree of open texture, co-determined by the open texture of the concept of algorithm itself and by the open texture inherent to legal discourse. We will substantiate our argument by virtue of a case study, in which we analyze a recent jurisprudential case where the first and second-degree judges have carved-out contrasting (...)
- Citizens’ data afterlives: Practices of dataset inclusion in machine learning for public welfare.Helene Friis Ratner & Nanna Bonde Thylstrup - forthcoming - AI and Society:1-11.Public sector adoption of AI techniques in welfare systems recasts historic national data as resource for machine learning. In this paper, we examine how the use of register data for development of predictive models produces new ‘afterlives’ for citizen data. First, we document a Danish research project’s practical efforts to develop an algorithmic decision-support model for social workers to classify children’s risk of maltreatment. Second, we outline the tensions emerging from project members’ negotiations about which datasets to include. Third, we (...)
- Sticks and stones may break my bones, but words will never hurt me!—Navigating the cybersecurity risks of generative AI.Abdur Rahman Bin Shahid & Ahmed Imteaj - forthcoming - AI and Society:1-2.
- Opening the black boxes of the black carpet in the era of risk society: a sociological analysis of AI, algorithms and big data at work through the case study of the Greek postal services.Christos Kouroutzas & Venetia Palamari - forthcoming - AI and Society:1-14.This article draws on contributions from the Sociology of Science and Technology and Science and Technology Studies, the Sociology of Risk and Uncertainty, and the Sociology of Work, focusing on the transformations of employment regarding expanded automation, robotization and informatization. The new work patterns emerging due to the introduction of software and hardware technologies, which are based on artificial intelligence, algorithms, big data gathering and robotic systems are examined closely. This article attempts to “open the black boxes” of the “black (...)
- The shift of Artificial Intelligence research from academia to industry: implications and possible future directions.Miguel Angelo de Abreu de Sousa - forthcoming - AI and Society:1-10.The movement of Artificial Intelligence (AI) research from universities to big corporations has had a significant impact on the development of the field. In the past, AI research was primarily conducted in academic institutions, which foster a culture of peer reviewing and collaboration to enhance quality improvements. The growing interest in AI among corporations, especially regarding Machine Learning (ML) technology, has shifted the focus of research from quality to quantity. Corporations have the resources to invest in large-scale ML projects and (...)
- Assessing the impact of heat vulnerability on urban public spaces using a fuzzy-based unified computational technique.Rajeev Kumar & Saswat Kishore Mishra - forthcoming - AI and Society:1-18.Over the years, the urban heat vulnerability has evolved as a pressing global concern for researchers and policymakers alike. Numerous studies have aimed at mitigating the adverse effects of urban heat vulnerability on public health and safety. However, the critical task of selecting the most fitting indicator for urban heat islands in public spaces is not emphasized in the existing studies, considering the diverse indices available. Beyond identification, studies that delve into the prioritization of these indices and the determination of (...)
- Emerging contours of geopolitics and state in the digital era.Arun Teja Polcumpally, Megha Shrivastava & Shashank S. Patel - forthcoming - AI and Society:1-5.This review essay provides a critical analysis of the book ‘The Great Tech Game,’ authored by Anirudh Suri. For the analysis, other literature published in a similar area is considered and pitched the arguments against the ones made in the book. During the year this book was released, there were numerous debates on accountability and trust in frontier digital technologies like AI. These debates have reached a systemic level where the entire global community is divided into two camps headed by (...)
- When will the blind be able to take their first steps with GDR guidance under artificial intelligence?Meimei Chen & Bin Hong - forthcoming - AI and Society:1-3.
- Using rhetorical strategies to design prompts: a human-in-the-loop approach to make AI useful.Nupoor Ranade, Marly Saravia & Aditya Johri - forthcoming - AI and Society:1-22.The growing capabilities of artificial intelligence (AI) word processing models have demonstrated exceptional potential to impact language related tasks and functions. Their fast pace of adoption and probable effect has also given rise to controversy within certain fields. Models, such as GPT-3, are a particular concern for professionals engaged in writing, particularly as their engagement with these technologies is limited due to lack of ability to control their output. Most efforts to maximize and control output rely on a process known (...)
- Eliza and the artist.Karamjit S. Gill - forthcoming - AI and Society:1-4.
- Give the machine a chance, human experts ain’t that great….Petr Špecián & Lucy Císař Brown - 2024 - AI and Society 2024:1-2.Despite their flaws, large language models (LLMs) deserve a fair chance to prove their mettle against human experts, who are often plagued with biases, conflicts of interest, and other frailties. For epistemically unprivileged laypeople struggling to access expert knowledge, the accessibility advantages of LLMs could prove crucial. While complaints about LLMs' inconsistencies and arguments for human superiority are often justified (for now), they distract from the urgent need to prepare for the likely scenario of LLMs' continued ascent. Experimentation with both (...)
- AI safety: necessary, but insufficient and possibly problematic.Deepak P. - forthcoming - AI and Society:1-3.
- Bridging divides: Empathy-augmenting technologies and cultural soul-searching.Manh-Tung Ho & Manh-Toan Ho - forthcoming - AI and Society:1-3.
- AI statecraft heating-up: the automation of governance through Canada’s Chinook case study.Nicolas Chartier-Edwards, Marek Blottiere & Jonathan Roberge - forthcoming - AI and Society:1-10.In the years 2020–2021, journalists, lawyers, scholars, and civil society actors noticed an unusual spike in the refusal of francophone African immigrants in Québec, Canada. While Immigration, refugee and citizenship Canada’s systemic racism problem were already documented, the novelty appeared to be how standardized and sometimes, “nonsensical” the reasons given to many of the applicants were. This eventually prompted a lawsuit against IRCC in which it was revealed that a new piece of software called “Chinook” had been deployed since 2018, (...)
- Responsible automatically processable regulation.Clement Guitton, Simon Mayer, Aurelia Tamo-Larrieux, Dimitri Van Landuyt, Eduard Fosch-Villaronga, Irene Kamara & Przemysław Pałka - forthcoming - AI and Society:1-16.Driven by the increasing availability and deployment of ubiquitous computing technologies across our private and professional lives, implementations of automatically processable regulation (APR) have evolved over the past decade from academic projects to real-world implementations by states and companies. There are now pressing issues that such encoded regulation brings about for citizens and society, and strategies to mitigate these issues are required. However, _comprehensive yet practically operationalizable_ frameworks to navigate the complex interactions and evaluate the risks of projects that implement (...)
- The work of art in the age of artificial intelligibility.John McLoughlin - forthcoming - AI and Society:1-13.The emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical, aesthetic, epistemological and legal frameworks we have so far used to categorise art. To begin tackling these issues and identifying a role for AI in the production and protection of human artwork, it is necessary to take a multidisciplinary approach which considers current legal precedents, (...)
- Human presencing: an alternative perspective on human embodiment and its implications for technology.Marie-Theres Fester-Seeger - forthcoming - AI and Society:1-19.Human presencing explores how people’s past encounters with others shape their present actions. In this paper, I present an alternative perspective on human embodiment in which the re-evoking of the absent can be traced to the intricate interplay of bodily dynamics. By situating the phenomenon within distributed, embodied, and dialogic approaches to language and cognition, I am overcoming the theoretical and methodological challenges involved in perceiving and acting upon what is not perceptually present. In a case study, I present strong (...)
- Technology impact model: a transition from the technology acceptance model.Peterson K. Ozili - forthcoming - AI and Society:1-3.
- Trust, risk perception, and intention to use autonomous vehicles: an interdisciplinary bibliometric review.Mohammad Naiseh, Jediah Clark, Tugra Akarsu, Yaniv Hanoch, Mario Brito, Mike Wald, Thomas Webster & Paurav Shukla - forthcoming - AI and Society:1-21.Autonomous vehicles (AV) offer promising benefits to society in terms of safety, environmental impact and increased mobility. However, acute challenges persist with any novel technology, inlcuding the perceived risks and trust underlying public acceptance. While research examining the current state of AV public perceptions and future challenges related to both societal and individual barriers to trust and risk perceptions is emerging, it is highly fragmented across disciplines. To address this research gap, by using the Web of Science database, our study (...)
- Can AI determine its own future?Aybike Tunç - forthcoming - AI and Society:1-12.This article investigates the capacity of artificial intelligence (AI) systems to claim the right to self-determination while exploring the prerequisites for individuals or entities to exercise control over their own destinies. The paper delves into the concept of autonomy as a fundamental aspect of self-determination, drawing a distinction between moral and legal autonomy and emphasizing the pivotal role of dignity in establishing legal autonomy. The analysis examines various theories of dignity, with a particular focus on Hannah Arendt’s perspective. Additionally, the (...)
- Yet Another Impossibility Theorem in Algorithmic Fairness.Fabian Beigang - 2023 - Minds and Machines 33 (4):715-735.In recent years, there has been a surge in research addressing the question which properties predictive algorithms ought to satisfy in order to be considered fair. Three of the most widely discussed criteria of fairness are the criteria called equalized odds, predictive parity, and counterfactual fairness. In this paper, I will present a new impossibility result involving these three criteria of algorithmic fairness. In particular, I will argue that there are realistic circumstances under which any predictive algorithm that satisfies counterfactual (...)
- Democratizing AI from a Sociotechnical Perspective.Merel Noorman & Tsjalling Swierstra - 2023 - Minds and Machines 33 (4):563-586.Artificial Intelligence (AI) technologies offer new ways of conducting decision-making tasks that influence the daily lives of citizens, such as coordinating traffic, energy distributions, and crowd flows. They can sort, rank, and prioritize the distribution of fines or public funds and resources. Many of the changes that AI technologies promise to bring to such tasks pertain to decisions that are collectively binding. When these technologies become part of critical infrastructures, such as energy networks, citizens are affected by these decisions whether (...)
- Not “what”, but “where is creativity?”: towards a relational-materialist approach to generative AI.Claudio Celis Bueno, Pei-Sze Chow & Ada Popowicz - forthcoming - AI and Society:1-13.The recent emergence of generative AI software as viable tools for use in the cultural and creative industries has sparked debates about the potential for “creativity” to be automated and “augmented” by algorithmic machines. Such discussions, however, begin from an ontological position, attempting to define creativity by either falling prey to universalism (i.e. “creativity is X”) or reductionism (i.e. “only humans can be truly creative” or “human creativity will be fully replaced by creative machines”). Furthermore, such an approach evades addressing (...)
- Manifestations of xenophobia in AI systems.Nenad Tomasev, Jonathan Leader Maynard & Iason Gabriel - forthcoming - AI and Society:1-23.Xenophobia is one of the key drivers of marginalisation, discrimination, and conflict, yet many prominent machine learning fairness frameworks fail to comprehensively measure or mitigate the resulting xenophobic harms. Here we aim to bridge this conceptual gap and help facilitate safe and ethical design of artificial intelligence (AI) solutions. We ground our analysis of the impact of xenophobia by first identifying distinct types of xenophobic harms, and then applying this framework across a number of prominent AI application domains, reviewing the (...)
- Collaborative route map and navigation of the guide dog robot based on optimum energy consumption.Bin Hong, Yihang Guo, Meimei Chen, Yahui Nie, Changyuan Feng & Fugeng Li - forthcoming - AI and Society:1-7.The guide dog robot (GDR) is a low-speed companion robot that serves visually impaired people and is used to guide blind people to walk steadily, carrying a variety of intelligent technologies and needing to have the ability to guide with optimal energy consumption in specific scenarios. This paper proposes an innovative technique for virtual-real collaborative path planning and navigation of the GDR specific indoor scenarios, and designs an experimental method for virtual-real collaborative path planning of the GDR specific scenarios. The (...)
- Abundance of words versus poverty of mind: the hidden human costs co-created with LLMs.Quan-Hoang Vuong & Manh-Tung Ho - forthcoming - AI and Society:1-2.
- Beyond the physical self: understanding the perversion of reality and the desire for digital transcendence via digital avatars in the context of Baudrillard’s theory.Lucas Freund - forthcoming - AI and Society:1-17.This paper explores the perversion of reality in the context of advanced technologies, such as AI, VR, and AR, through the lens of Jean Baudrillard’s theory of hyperreality and the precession of simulacra. By examining the transformative effects of these technologies on our perception of reality, with a particular focus on the usage of digital avatars, the paper highlights the blurred distinction between the real and the simulated, where the copy becomes more ‘real’ than the original. Drawing on Baudrillard’s concept (...)
- The Principle-at-Risk Analysis (PaRA): Operationalising Digital Ethics by Bridging Principles and Operations of a Digital Ethics Advisory Panel.André T. Nemat, Sarah J. Becker, Simon Lucas, Sean Thomas, Isabel Gadea & Jean Enno Charton - 2023 - Minds and Machines 33 (4):737-760.Recent attempts to develop and apply digital ethics principles to address the challenges of the digital transformation leave organisations with an operationalisation gap. To successfully implement such guidance, they must find ways to translate high-level ethics frameworks into practical methods and tools that match their specific workflows and needs. Here, we describe the development of a standardised risk assessment tool, the Principle-at-Risk Analysis (PaRA), as a means to close this operationalisation gap for a key level of the ethics infrastructure at (...)
- Computing Cultures: Historical and Philosophical Perspectives.Juan Luis Gastaldi - 2024 - Minds and Machines 34 (1):1-10.
- The Role of Naturalness in Concept Learning: A Computational Study.Igor Douven - 2023 - Minds and Machines 33 (4):695-714.This paper studies the learnability of natural concepts in the context of the conceptual spaces framework. Previous work proposed that natural concepts are represented by the cells of optimally partitioned similarity spaces, where optimality was defined in terms of a number of constraints. Among these is the constraint that optimally partitioned similarity spaces result in easily learnable concepts. While there is evidence that systems of concepts generally regarded as natural satisfy a number of the proposed optimality constraints, the connection between (...)
- Encoding Ethics to Compute Value-Aligned Norms.Marc Serramia, Manel Rodriguez-Soto, Maite Lopez-Sanchez, Juan A. Rodriguez-Aguilar, Filippo Bistaffa, Paula Boddington, Michael Wooldridge & Carlos Ansotegui - 2023 - Minds and Machines 33 (4):761-790.Norms have been widely enacted in human and agent societies to regulate individuals’ actions. However, although legislators may have ethics in mind when establishing norms, moral values are only sometimes explicitly considered. This paper advances the state of the art by providing a method for selecting the norms to enact within a society that best aligns with the moral values of such a society. Our approach to aligning norms and values is grounded in the ethics literature. Specifically, from the literature’s (...)
- A Pragmatic Theory of Computational Artefacts.Alessandro G. Buda & Giuseppe Primiero - 2024 - Minds and Machines 34 (1):139-170.Some computational phenomena rely essentially on pragmatic considerations, and seem to undermine the independence of the specification from the implementation. These include software development, deviant uses, esoteric languages and recent data-driven applications. To account for them, the interaction between pragmatics, epistemology and ontology in computational artefacts seems essential, indicating the need to recover the role of the language metaphor. We propose a User Levels (ULs) structure as a pragmatic complement to the Levels of Abstraction (LoAs)-based structure defining the ontology and (...)
- Online Altruism: What it is and how it Differs from Other Kinds of Altruism.Katherine Lou & Luciano Floridi - 2023 - Minds and Machines 33 (4):641-666.Altruism is a well-studied phenomenon in the social sciences, but online altruism has received relatively little attention. In this article, we examine several cases of online altruism, and analyse the key characteristics of the phenomenon, in particular comparing and contrasting it against models of traditional donor behaviour. We suggest a novel definition of online altruism, and provide an in-depth, mixed-method study of a significant case, represented by the r/Assistance subreddit. We argue that online altruism can be characterized by its differing (...)
- The Ethics of Online Controlled Experiments (A/B Testing).Andrea Polonioli, Riccardo Ghioni, Ciro Greco, Prathm Juneja, Jacopo Tagliabue, David Watson & Luciano Floridi - 2023 - Minds and Machines 33 (4):667-693.Online controlled experiments, also known as A/B tests, have become ubiquitous. While many practical challenges in running experiments at scale have been thoroughly discussed, the ethical dimension of A/B testing has been neglected. This article fills this gap in the literature by introducing a new, soft ethics and governance framework that explicitly recognizes how the rise of an experimentation culture in industry settings brings not only unprecedented opportunities to businesses but also significant responsibilities. More precisely, the article (a) introduces a (...)
- Natural and Artificial Intelligence: A Comparative Analysis of Cognitive Aspects.Francesco Abbate - 2023 - Minds and Machines 33 (4):791-815.Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be interpreted. (...)
- True Turing: A Bird’s-Eye View.Edgar Daylight - 2024 - Minds and Machines 34 (1):29-49.Alan Turing is often portrayed as a materialist in secondary literature. In the present article, I suggest that Turing was instead an idealist, inspired by Cambridge scholars, Arthur Eddington, Ernest Hobson, James Jeans and John McTaggart. I outline Turing’s developing thoughts and his legacy in the USA to date. Specifically, I contrast Turing’s two notions of computability (both from 1936) and distinguish between Turing’s “machine intelligence” in the UK and the more well-known “artificial intelligence” in the USA. According to my (...)
- Limits of Optimization.Cesare Carissimo & Marcin Korecki - 2024 - Minds and Machines 34 (1):117-137.Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become readily available to most people, optimization and optimized processes play a very broad role in societies. It is not obvious, however, that the optimization processes that work for mathematics and abstract objects should be readily applied to (...)
- From Monitors to Monitors: A Primitive History.Troy K. Astarte - 2024 - Minds and Machines 34 (1):51-71.As computers became multi-component systems in the 1950s, handling the speed differentials efficiently was identified as a major challenge. The desire for better understanding and control of ‘concurrency’ spread into hardware, software, and formalism. This paper examines the way in which the problem emerged and was handled across various computing cultures from 1955 to 1985. In the machinic culture of the late 1950s, system programs called ‘monitors’ were used for directly managing synchronisation. Attempts to reframe synchronisation in the subsequent algorithmic (...)
- Informational Equivalence but Computational Differences? Herbert Simon on Representations in Scientific Practice.David Waszek - 2024 - Minds and Machines 34 (1):93-116.To explain why, in scientific problem solving, a diagram can be “worth ten thousand words,” Jill Larkin and Herbert Simon (1987) relied on a computer model: two representations can be “informationally” equivalent but differ “computationally,” just as the same data can be encoded in a computer in multiple ways, more or less suited to different kinds of processing. The roots of this proposal lay in cognitive psychology, more precisely in the “imagery debate” of the 1970s on whether there are image-like (...)
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