Strolling up the garden path (original) (raw)
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Chapter 1 of Why Machines Will Never Rule the World
Why Machines Will Never Rule the World, 2022
The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory?
Project De/light me! is a reader on new patterns of second order theory, or meta-theory, but applyed not on meta as supra level, not higher, but lower or down theory, underground theory of weird productions, applications, and phenomenas, on their patterns. So, it is about experimenting in a B-production level of theory, non-academic or second handed thought, concerned with the processing of theory on its new abut with technology.
If we look back 50 years in computing history, we can compare Vannevar Bush's vision of what information technology might one day be able to accomplish to what it has since become. Bush foresaw the use of the computer as an effective memory system, with which humans could store and retrieve information, as well as sort data, and trace a kind of hyperlink trail of reasoning. Not only that, but in Bush's memex machine, one would even be able to print off or magnetically store an information set for delivery to others. Everything Bush described has come to pass, and in nearly every case exceeds what he imagined. Bush was prescient indeed, but he also occupied a good vantage point: he directed certain military research in the war effort. He was familiar with rapid developments in prototype feedback experiments such as fire control and communications theory, among other things. In early fire control a system's state advanced through iterative looping of feedback through the system. Output was re-entered as input. Refinements in such processes led to the birth of cybernetics. In this phase of the information revolution cybernetic systems combined machines doing environmental scanning with human intervention providing the intentionality, or wisdom, to the system. Machines appeared fully capable of combining data structures into information constructs. Information domains were defined by task.
On the Relation of Computing to the World
Philosophical studies series, 2017
I survey a common theme that pervades the philosophy of computer science (and philosophy more generally): the relation of computing to the world. Are algorithms merely certain procedures entirely characterizable in an "indigenous", "internal', "intrinsic", "local", "narrow", "syntactic" (more generally: "intra-system") purely Turing-machine language? Or must they interact with the real world, with a purpose that is expressible only in a language with an "external", "extrinsic", "global", "wide", "inherited" (more generally: "extra-" or "inter-"sytem) semantics? If you begin with Computer Science, you will end with Philosophy. 1 I was simultaneously surprised and deeply honored to receive the 2015 Covey Award from the International Association for Computing and Philosophy. 2 The honor is due in part to linking me to the illustrious predecessors who have received this award, but also to its having been named for Preston Covey, 3 whom I knew and who inspired me as I began my twin journeys in philosophy and computing. 1.1 From Philosophy to Computer Science, and Back Again Contrary to the motto above, I began with philosophy, found my way to computer science, and have returned to a mixture of the two. Inspired by Douglas Hofstadter's review [Hofstatder, 1980] of Aaron Sloman's The Computer Revolution in Philosophy [Sloman, 1978], which quoted Sloman to the effect that a philosopher of mind who knew no AI was like a philosopher of physics who knew no quantum mechanics, 4 my philosophical interests in philosophy of mind led me to study AI at SUNY Buffalo with Stuart C. Shapiro. 5 This eventually led to a faculty appointment in computer science at Buffalo. (Along the way, my philosophy colleagues and I at SUNY Fredonia published one of the first introductory logic textbooks to use a computational approach [Schagrin et al., 1985].) At Buffalo, I was amazed to discover that my relatively arcane philosophy dissertation on Alexius Meinong was directly relevant to Shapiro's work in AI, providing an intensional semantics for his SNePS semantic-network processing system (see, e.g., [Shapiro and Rapaport, 1987], [Shapiro and Rapaport, 1991]). 6 And then I realized that the discovery of quasi-indexicals ('he himself', 'she herself', etc.; [Castañeda, 1966]) by my dissertation advisor, Hector-Neri Castañeda 1 "Clicking on the first link in the main text of a Wikipedia article, and then repeating the process for subsequent articles, usually eventually gets you to the Philosophy article. As of May 26, 2011, 94.52% of all articles in Wikipedia lead eventually to the article Philosophy" (http://en.wikipedia.org/wiki/Wikipedia:Getting to Philosophy). If you begin with "Computer Science", you will end with "Philosophy" (in 12 links). 2 http://www.iacap.org/awards/ 3 http://en.wikipedia.org/wiki/Covey Award 4 "I am prepared to go so far as to say that within a few years, if there remain any philosophers who are not familiar with some of the main developments in artificial intelligence, it will be fair to accuse them of professional incompetence, and that to teach courses in philosophy of mind, epistemology, aesthetics, philosophy of science, philosophy of language, ethics, metaphysics, and other main areas of philosophy, without discussing the relevant aspects of artificial intelligence will be as irresponsible as giving a degree course in physics which includes no quantum theory" [Sloman, 1978, p. 5].
The decline of the feudal system and the progressive rise of the medieval bourgeoisie to power roles and government functions, leads the West (17 th century) to theorize and assume a materialistic, reductionist and mechanistic model of thought, based on a privileged, tendentially exclusive, relationship with Science (Galilean scientific method), technique and technology. This paper takes into account the historical, sociological, and anthropological elements (such as the unlimited perfectibility of humanity advocated by the French Enlightenment and the mechanization of the production cycle envisaged by English proto-liberalism) of this paradigmatic revolution, which more than others help us understanding the causal process that led to contemporary techno-centrism 4.0. It is highlighted that thanks to the interweav-ing between the ideals of the French Enlightenment, with its two souls (Natu-rophilus and Technophilus), and the Anglo-Saxon entrepreneurial foresight (proved successful with the Industrial Revolution 1.0), takes shape the Posi-tivist paradigm, and with it the Positivist secular religion, whose affirmation and diffusion generate a stream of widely shared thought throughout the West, i.e. Eugenics, which radicalizes the most ambivalent (pseudo-scientific) and reactionary (philocolonialist) instances of Enlightenment and Positivism, leading to a series of crimes against the person and against humanity, which will result in the mass eliminations conducted, in particular but not only, by Nazi-fascism and Stalinism (two totalitarian regimes that share the same Posi-tivist roots and the same passion for Eugenics thought). It is highlighted that the heart of the industrialization process begins to throb in factories, where the introduction of mechanical systems into the production cycle triggers the man-machine integration process, which soon becomes the fulcrum, the economic , social and cultural driving factor of the western civilization. It will be thanks to the evolution of the mechanical systems employed in the production chains and to the establishment of the Liberalist economic model, that between the second and third Industrial Revolution consolidates the alliance between academic, industrial and military (the academic/industrial/military iron triangle). An alliance destined to play a decisive role in the two World