The first part (“Is there a future?”), discusses the idea of the future in the context of Carl Schmitt’s vision for the spatial revolutions of modernity, and then the idea of Anthropocene, as a synonym for an environmental crisis endangering the very survival of humankind. From this point of view, the conquest of space and the colonization of Mars at the center of futuristic and technocratic visions appear to be an attempt to escape from human responsibilities on Earth. The second (...) part (“AI and other hyperobjects”) discusses the extent of intellectual hubris expressed in computation, AI (Garvin Minsky e Ray Kurzweil), and the philosophy of computing and information (Eric Fredkin), involved in the elaboration of new theoretical assessments on the ultimate nature of reality. Their vision is then contrasted and made to interact with that of philosopher Timothy Morton. He has taken the perspective of global warming and the possibility of ecological catastrophe seriously, avoiding all the futuristic enthusiasms and instead emphasizing the radical nature of the transformations that humans experience in the present. In this perspective, AI becomes one of the “hyperobjects,” like the Internet or climate change, in which humans are immersed. Morton’s hyperobjects delineate an uncanny view of the future; this uncanniness is not related to the supernatural but to the environment. The third section (“More-than-human-humanism”) further reflects on the “uncanniness” that human perceive in the encounters with the manifestations of hyperobjects. It also seeks to understand the human position in the face of the radical technological transformations induced by cybernetics and AI. This section discusses Anti-humanism, Transhumanism, and Posthumanism within the broader category of more-than-human thought, which seems to be a more appropriate term to clarify the possible misunderstandings induced by the word “posthuman” and “transhuman.” The central question is not to empower (Transhumanism) or disempower (Posthumanism) humans, but to see them in relation to what is not human, including other animals, the environment, and the machine. The analysis considers the works of Cary Wolfe, Jane Bennet, Bryant Levi, among others, and introduces ethical debates on cyborgs, robots, and Autonomous weapons systems (AWS). The fourth section (“Ethical Perspectives”) continues this inquiry, concentrating on the non-standard ethical theories of Luciano Floridi (Computer and Information Ethics) and David Gunkel (The question of the Machine). It examines the opportunity and feasibility of including in the discussion on the ethics of our time - characterized by the pervasiveness of AI - the notions of consciousness as theorized by Emmanuel Levinas’s Humanism of the Other and Paul Ricoeur’s Oneself as Another. Finally, the last section (“The time of the end?”) reflects on how the hyperobject, Anthropocene, re-establishes a sense of limits in human history and confirms the special responsibility of human beings, and supports the need for a more-than-human-humanism. The latter, in other words, means intertwining ourselves with a unique ecosystem which cannot be overlooked and which restores meaning to our relationship with the past, present, and future. The awareness of the current challenges of technology can and must express itself in different forms of resistance to the adverse effects of AI in our lives. The ethical approach based on the persisting role of human consciousness is essential, but it must be coupled with human decision-making and political action. (shrink)

This paper is about Artificial Intelligence (AI) attempts at writing poetry, usually referred to with the term “poetry generation”. Poetry generation started out from Digital Humanities, which developed out of humanities computing; nowadays, however, it is part of Computational Creativity, a field that tackles several areas of art and science. In the paper it is examined, first, why poetry was chosen among other literary genres as a field for experimentation. Mention is made to the characteristics of poetry (namely arbitrariness and (...) absurdity) that make it fertile ground for such endeavors and also to various text- and reader-centered literary approaches that favored experimentation even by human poets. Then, a rough historic look at poetry generation is attempted, followed by a review of the methods employed, either for fun or as academic projects, along Lamb et al.’s (2017) taxonomy which distinguishes between mere poetry generation and result enhancement. Another taxonomy by Gonçalo Oliveira (2017), dividing between form and content issues in poetry generation, is also briefly presented. The results of poetry generators are evaluated as generally poor and the reasons for this failure are examined: inability of computers to understand any word as a sign with a signified, lack of general intelligence, process- (rather than output-) driven attempts, etc. Then, computer-like results from a number of human poetic movements are also presented as a juxtaposition: DADA, stream of consciousness, OuLiPo, LangPo, Flarf, blackout/erasure poetry. The equivalence between (i) human poets that are concerned more with experimentation more than with good results and (ii) computer scientists who are process-driven leads to a discussion of the characteristics of humanness, of the possibility of granting future AI personhood and of the need to see our world in terms of a new, more refined ontology. (shrink)

The Southern Journal of Philosophy, Volume 60, Issue 1, Page 88-117, March 2022.

Karl Marx took technological development to be the heart of capitalism’s drive and, ultimately, its undoing. Machines are initially engineered to perform functions that otherwise would be performed by human workers. The economic logic pushed to its limits leads to the prospect of full automation: a world in which all labor required to meet human needs is superseded and performed by machines. To explore the future of automation, the paper considers a specific point of resemblance between human beings and machines: (...) intelligence. Examining the development of machine intelligence through the Marxist concepts of alienation and reification reveals a tension between certain technophilic post-labor visions and the reality of capitalistic development oriented towards intelligent technology. If the prospect of a post-labor world depends on technologies that closely resemble humans, the world can no longer be described as post-labor. The tension has implications for the potential moral status of machines and the possibility of full automation. The paper considers these implications by outlining four possible futures of automation. (shrink)

The topic of this dissertation is the nature of linguistic competence, the capacity to understand and produce sentences of natural language. I defend the empiricist account of linguistic competence embedded in the connectionist cognitive science. This strand of cognitive science has been opposed to the traditional symbolic cognitive science, coupled with transformational-generative grammar, which was committed to nativism due to the view that human cognition, including language capacity, should be construed in terms of symbolic representations and hardwired rules. Similarly, linguistic (...) competence in this framework was regarded as being innate, rule-governed, domain-specific, and fundamentally different from performance, i.e., idiosyncrasies and factors governing linguistic behavior. I analyze state-of-the-art connectionist, deep learning models of natural language processing, most notably large language models, to see what they can tell us about linguistic competence. Deep learning is a statistical technique for the classification of patterns through which artificial intelligence researchers train artificial neural networks containing multiple layers that crunch a gargantuan amount of textual and/or visual data. I argue that these models suggest that linguistic competence should be construed as stochastic, pattern-based, and stemming from domain-general mechanisms. Moreover, I distinguish syntactic from semantic competence, and I show for each the ramifications of the endorsement of a connectionist research program as opposed to the traditional symbolic cognitive science and transformational-generative grammar. I provide a unifying front, consisting of usage-based theories, a construction grammar approach, and an embodied approach to cognition to show that the more multimodal and diverse models are in terms of architectural features and training data, the stronger the case is for the connectionist linguistic competence. I also propose to discard the competence vs. performance distinction as theoretically inferior so that a novel and integrative account of linguistic competence originating in connectionism and empiricism that I propose and defend in the dissertation could be put forward in scientific and philosophical literature. (shrink)

The problem of personal identity is a longstanding philosophical topic albeit without final consensus. In this article the somewhat similar problem of AI identity is discussed, which has not gained much traction yet, although this investigation is increasingly relevant for different fields, such as ownership issues, personhood of AI, AI welfare, brain–machine interfaces, the distinction between singletons and multi-agent systems as well as to potentially support finding a solution to the problem of personal identity. The AI identity problem analyses the (...) criteria for two AIs to be considered the same at different points in time. Two approaches to tackle the problem are proposed: One is based on the personal identity problem and the concept of computational irreducibility, while the other one applies multi-factor authentication to the AI identity problem. Also, a range of scenarios is examined regarding AI identity, such as replication, fission, fusion, switch off, resurrection, change of hardware, transition from non-sentient to sentient, journey to the past, offspring and identity change. (shrink)