How Humans Conceptualize Machines

A special issue of Philosophies (ISSN 2409-9287).

Deadline for manuscript submissions: closed (25 April 2022) | Viewed by 13236

Special Issue Editors


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Guest Editor
Department of Cognitive Sciences, University of Messina, 98122 Messina, Italy
Interests: philosophy of science; neural computation; cognitive science

E-Mail Website
Guest Editor
Department of Cognitive Sciences, University of Messina, 98122 Messina, Italy
Interests: philosophy of mind; social cognition; consciousness

Special Issue Information

Dear Colleagues,

Never before have machines been so ubiquitous and pervasive as they are at present. With the advancement of artificial intelligence, machines are taking on increasingly diverse roles in human society, changing the landscape of our life. Intelligent vehicles cooperate with human drivers at various levels, including fully autonomous driving. Conversational assistants interact with people in providing troubleshooting guidance, recommending travel directions or shopping products. More and more news is created by machines, with the broader incorporation of automation in journalism.

There are robots taking on social roles and engaging in daily activities such as education, elderly assistance, and health care. Others serve as sex robots, and it is not clear whether their presence in the contemporary scene can be considered as an opportunity for the freedom of sex workers or a threat to human dignity (Kathleen Richardson).

The huge artificial intelligence market has given birth to a number of new research areas, in the effort to foster the acceptance of machines, and to improve the interaction experience of humans with machines. This research intersects disciplines from engineering, psychology, computer science, economy, and sociology. There is, however, a fundamental issue that boils down all of the studies about humans’ interaction with machines: the understanding of how humans conceptualize machines.

This sort of investigation involves crucial aspects of how in general humans construct concepts of minds with which they interact, therefore, it pertains first and foremost to philosophy of mind and cognitive science. It is especially important to assess the evolution of the mental image of machines due to the new artificial intelligence. People may now attribute machines with properties such as conscious experience and a kind of moral status. Such attributes might in turn affect the evolution of social attitude towards machines.

In the past, a prevailing attitude towards machines, developed in mid-eighteenth-century England and later in United States, was of machines as slaves, replacing the labor of men in the harshest conditions. In the same period, a group, called the Luddites, raged against machines, and they did everything they could to resist them. Intellectual technophobic caveats abound in modernist thinking, from Spengler to Heidegger and Benjamin. On the opposite side, at the beginning of the past century the Italian Futurist movement promoted a radical machine culture. Today too there are supporters of technophilia and technophobia; within the former there are the singularists, posthumanists, and transhumanists. Probably, the prevailing conceptualization of machines by lay people is yet to be discovered.

We welcome papers exploring all aspects that contribute to answering the question of how humans conceptualize machines.

Dr. Alessio Plebe
Prof. Dr. Pietro Perconti
Guest Editors

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Keywords

  • trust in automation
  • artificial intelligence
  • machine consciousness
  • machine morality
  • artificial intelligence ethics
  • social robotics

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Published Papers (2 papers)

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Research

12 pages, 243 KiB  
Article
Conceptualizing Machines in an Eco-Cognitive Perspective
by Lorenzo Magnani
Philosophies 2022, 7(5), 94; https://doi.org/10.3390/philosophies7050094 - 25 Aug 2022
Viewed by 1996
Abstract
Eco-cognitive computationalism explores computing in context, adhering to some of the key ideas presented by modern cognitive science perspectives on embodied, situated, and distributed cognition. First of all, when physical computation is seen from the perspective of the ecology of cognition it is [...] Read more.
Eco-cognitive computationalism explores computing in context, adhering to some of the key ideas presented by modern cognitive science perspectives on embodied, situated, and distributed cognition. First of all, when physical computation is seen from the perspective of the ecology of cognition it is possible to clearly understand the role Turing assigned to the process of “education” of the machine, paralleling it to the education of human brains, in the invention of the Logical Universal Machine. It is this Turing’s emphasis on education that furnishes the justification of the conceptualization of machines as “domesticated ignorant entities”, that is proposed in this article. I will show that conceptualizing machines as dynamically active in distributed physical entities of various kinds suitably transformed so that data can be encoded and decoded to obtain appropriate results sheds further light on my eco-cognitive perspective. Furthermore, it is within this intellectual framework that I will usefully analyze the recent attention in computer science devoted to the importance of the simplification of cognitive and motor tasks caused in organic entities thanks to morphological features: ignorant bodies can be computationally domesticated to make an intertwined computation simpler, relying on the “simplexity” of animal embodied cognition, which represents one of the main qualities of organic agents. Finally, eco-cognitive computationalism allows us to clearly acknowledge that the concept of computation evolves over time as a result of historical and contextual factors, and we can construct an epistemological view that depicts the “emergence” of new types of computations that exploit new substrates. This new viewpoint demonstrates how the computational domestication of ignorant entities might result in the emergence of novel unconventional cognitive embodiments. Full article
(This article belongs to the Special Issue How Humans Conceptualize Machines)
11 pages, 217 KiB  
Article
The AI Carbon Footprint and Responsibilities of AI Scientists
by Guglielmo Tamburrini
Philosophies 2022, 7(1), 4; https://doi.org/10.3390/philosophies7010004 - 5 Jan 2022
Cited by 26 | Viewed by 10073
Abstract
This article examines ethical implications of the growing AI carbon footprint, focusing on the fair distribution of prospective responsibilities among groups of involved actors. First, major groups of involved actors are identified, including AI scientists, AI industry, and AI infrastructure providers, from datacenters [...] Read more.
This article examines ethical implications of the growing AI carbon footprint, focusing on the fair distribution of prospective responsibilities among groups of involved actors. First, major groups of involved actors are identified, including AI scientists, AI industry, and AI infrastructure providers, from datacenters to electrical energy suppliers. Second, responsibilities of AI scientists concerning climate warming mitigation actions are disentangled from responsibilities of other involved actors. Third, to implement these responsibilities nudging interventions are suggested, leveraging on AI competitive games which would prize research combining better system accuracy with greater computational and energy efficiency. Finally, in addition to the AI carbon footprint, it is argued that another ethical issue with a genuinely global dimension is now emerging in the AI ethics agenda. This issue concerns the threats that AI-powered cyberweapons pose to the digital command, control, and communication infrastructure of nuclear weapons systems. Full article
(This article belongs to the Special Issue How Humans Conceptualize Machines)
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