The Hard Problem (But Not That Hard) Mike Arnautov
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Stephen Lumsden B1 15.1.18
Stephen Lumsden, essay for Units 1-3, Program B: Philosophy Of Mind (Essay for Question 5. What is the philosophical significance of the idea of disembodiment and/or the idea of a ‘zombie’?) What is the philosophical significance of the idea of the idea of a ‘zombie In this essay I will briefly summarise the origin of the idea of philosophical zombies and explain what they are. Arguments for their relevance in philosophical enquiry will be then made in order to gauge whether they are a useful tool to use. The idea of a philosophical zombie is a fully functioning person who exists without any inner life or consciousness. This was first put forward by David Chalmers a form of thought experiment and goes as follows: P1: I can consistently conceive of a beings that are physically identical with us, yet have no conscious experience. P2: Conceivability implies possibility C: Therefore we are not purely physical beings In accepting the conceivability of the argument this implies possibility and therefore zombies are possible. In turn the possibility of the zombies will counter the physicalist view that consciousness can be solely defined in functional terms. In turn this can be seen as a victory for supporters of Cartesian Dualism (the idea that the mind is a separate immaterial entity which exists independently of the physical body, as outlined by Descartes in his Meditations on First Philosophy). This argument raises questions in relation to two areas in the philosophy of mind, namely that of Dualism vs physicalism and the problem of other minds. -
Russellian Panpsychism: Do We Need It and Is It Enough?
Russellian Panpsychism: Do We Need It and Is It Enough? By Damian Aleksiev Submitted to Central European University Department of Philosophy In partial fulfillment of the requirements for the degree of Master of Philosophy Supervisor: Philip Goff CEU eTD Collection May 2016 Abstract The main aim of this thesis is to clarify the ontological status of phenomenal experience. In order to do this, I first examine how pure physicalism explains phenomenality. Pure physicalism relies on the structural and causal vocabulary of physics, and is compatible with the causal closure of the physical. Nonetheless, I argue that pure physicalism is false since it cannot account for our intuitive understating of phenomenal experience as something beyond-structural. I supplement these intuitions, first with the knowledge and conceivability arguments, and second with my own argument for the transparency of phenomenal concepts called the argument from solipsism. Then, I investigate Russellian panpsychism as a promising alternative to pure physicalism that attempts to solve its problems without any drawbacks. Russellian panpsychism places phenomenal experience at the fundamental ontological level, and at the same time remains compatible with the causal closure of the physical. Finally, I argue against Russellian panpsychism based on the combination problem, as well as my own: reverse conceivability argument, and combination problem for value. The conclusion of this enquiry is that neither pure physicalism nor Russellian panpsychism can provide a satisfactory account of phenomenal experience. CEU eTD Collection I Acknowledgments I would like to thank my supervisor Philip Goff for his continual support and willingness to discuss my ideas during the entire academic year. -
An Introduction to Philosophy
An Introduction to Philosophy W. Russ Payne Bellevue College Copyright (cc by nc 4.0) 2015 W. Russ Payne Permission is granted to copy, distribute and/or modify this document with attribution under the terms of Creative Commons: Attribution Noncommercial 4.0 International or any later version of this license. A copy of the license is found at http://creativecommons.org/licenses/by-nc/4.0/ 1 Contents Introduction ………………………………………………. 3 Chapter 1: What Philosophy Is ………………………….. 5 Chapter 2: How to do Philosophy ………………….……. 11 Chapter 3: Ancient Philosophy ………………….………. 23 Chapter 4: Rationalism ………….………………….……. 38 Chapter 5: Empiricism …………………………………… 50 Chapter 6: Philosophy of Science ………………….…..… 58 Chapter 7: Philosophy of Mind …………………….……. 72 Chapter 8: Love and Happiness …………………….……. 79 Chapter 9: Meta Ethics …………………………………… 94 Chapter 10: Right Action ……………………...…………. 108 Chapter 11: Social Justice …………………………...…… 120 2 Introduction The goal of this text is to present philosophy to newcomers as a living discipline with historical roots. While a few early chapters are historically organized, my goal in the historical chapters is to trace a developmental progression of thought that introduces basic philosophical methods and frames issues that remain relevant today. Later chapters are topically organized. These include philosophy of science and philosophy of mind, areas where philosophy has shown dramatic recent progress. This text concludes with four chapters on ethics, broadly construed. I cover traditional theories of right action in the third of these. Students are first invited first to think about what is good for themselves and their relationships in a chapter of love and happiness. Next a few meta-ethical issues are considered; namely, whether they are moral truths and if so what makes them so. -
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in the Psychology of Comp
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in The Psychology of Computer Vision, P. Winston (Ed.), McGraw-Hill, 1975. Shorter versions in J. Haugeland, Ed., Mind Design, MIT Press, 1981, and in Cognitive Science, Collins, Allan and Edward E. Smith (eds.) Morgan-Kaufmann, 1992 ISBN 55860-013-2] FRAMES It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities. Similar feelings seem to be emerging in several centers working on theories of intelligence. They take one form in the proposal of Papert and myself (1972) to sub-structure knowledge into "micro-worlds"; another form in the "Problem-spaces" of Newell and Simon (1972); and yet another in new, large structures that theorists like Schank (1974), Abelson (1974), and Norman (1972) assign to linguistic objects. I see all these as moving away from the traditional attempts both by behavioristic psychologists and by logic-oriented students of Artificial Intelligence in trying to represent knowledge as collections of separate, simple fragments. I try here to bring together several of these issues by pretending to have a unified, coherent theory. The paper raises more questions than it answers, and I have tried to note the theory's deficiencies. -
The Knowledge and Zombie Arguments
Thought Experiments in Philosophy 5 1. The Knowledge Argument Against Physicalism (1) If physicalism is true, then to know all the physical facts in domain D is to know all facts in D. “A complete account of what our world is like can in principle be told in terms of a relatively small set of favoured particulars, properties, and relations—the ‘physical’ ones. The world is entirely physical in nature; it is nothing but, or nothing over and above, the physical world. A full inven- tory of the instantiated physical properties and relations would be a full inventory simpliciter.”1 “Any world which is a minimal physical duplicate of our world is a dupli- cate simpliciter of our world.” “Every mental fact is entailed by the physical facts, i.e. by how the physical (or micro-physical) world is.” (2) It is possible to know all physical facts in D without knowing all facts in D: Mary the colour scientist. (3) Therefore, physicalism is false. 2. The Conceivability Argument Against Physicalism This argument concludes from the possibility of a creature that lacks subjective pheno- menal experience to the falsity of physicalism. Preliminaries (1) In our world, there are conscious experiences (mental realism). (2) A (philosophical) zombie is a creature that is a molecule for molecule duplicate of me, but it lacks subjective conscious experience completely. (3) Zombies are conceivable. (4) If zombies are conceivable, then zombies are metaphysically (absolutely) possible. (5) Therefore, zombies are metaphysically (absolutely) possible. (from 3 and 4) First way to complete the argument (6) If physicalism is true, then a physical duplicate of our world is a complete duplicate (a duplicate simpliciter). -
Mccarthy As Scientist and Engineer, with Personal Recollections
Articles McCarthy as Scientist and Engineer, with Personal Recollections Edward Feigenbaum n John McCarthy, professor emeritus of com - n the late 1950s and early 1960s, there were very few people puter science at Stanford University, died on actually doing AI research — mostly the handful of founders October 24, 2011. McCarthy, a past president (John McCarthy, Marvin Minsky, and Oliver Selfridge in of AAAI and an AAAI Fellow, helped design the I Boston, Allen Newell and Herbert Simon in Pittsburgh) plus foundation of today’s internet-based computing their students, and that included me. Everyone knew everyone and is widely credited with coining the term, artificial intelligence. This remembrance by else, and saw them at the few conference panels that were held. Edward Feigenbaum, also a past president of At one of those conferences, I met John. We renewed contact AAAI and a professor emeritus of computer sci - upon his rearrival at Stanford, and that was to have major con - ence at Stanford University, was delivered at the sequences for my professional life. I was a faculty member at the celebration of John McCarthy’s accomplish - University of California, Berkeley, teaching the first AI courses ments, held at Stanford on 25 March 2012. at that university, and John was doing the same at Stanford. As – AI Magazine Stanford moved toward a computer science department under the leadership of George Forsythe, John suggested to George, and then supported, the idea of hiring me into the founding fac - ulty of the department. Since we were both Advanced Research Project Agency (ARPA) contract awardees, we quickly formed a close bond concerning ARPA-sponsored AI research and gradu - ate student teaching. -
Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration. -
WHY PEOPLE THINK COMPUTERS CAN't Marvin
WHY PEOPLE THINK COMPUTERS CAN'T Marvin Minsky, MIT First published in AI Magazine, vol. 3 no. 4, Fall 1982. Reprinted in Technology Review, Nov/Dec 1983, and in The Computer Culture, (Donnelly, Ed.) Associated Univ. Presses, Cranbury NJ, 1985 Most people think computers will never be able to think. That is, really think. Not now or ever. To be sure, most people also agree that computers can do many things that a person would have to be thinking to do. Then how could a machine seem to think but not actually think? Well, setting aside the question of what thinking actually is, I think that most of us would answer that by saying that in these cases, what the computer is doing is merely a superficial imitation of human intelligence. It has been designed to obey certain simple commands, and then it has been provided with programs composed of those commands. Because of this, the computer has to obey those commands, but without any idea of what's happening. Indeed, when computers first appeared, most of their designers intended them for nothing only to do huge, mindless computations. That's why the things were called "computers". Yet even then, a few pioneers -- especially Alan Turing -- envisioned what's now called "Artificial Intelligence" - or "AI". They saw that computers might possibly go beyond arithmetic, and maybe imitate the processes that go on inside human brains. Today, with robots everywhere in industry and movie films, most people think Al has gone much further than it has. Yet still, "computer experts" say machines will never really think. -
The Qualia Manifesto (C) Ken Mogi 1998 [email protected] the Qualia Manifesto Summar
The Qualia Manifesto (c) Ken Mogi 1998 [email protected] http://www.qualia-manifesto.com The Qualia Manifesto Summary It is the greatest intellectual challenge for humanity at present to elucidate the first principles behind the fact that there is such a thing as a subjectiveexperience. The hallmark of our subjective experiences is qualia. It is the challenge to find the natural law behind the neural generation of qualia which constitute the percepts in our mind, or to go beyond the metaphor of a "correspondence" between physical and mental processes. This challenge is necessary to go beyond the present paradigm of natural sciences which is based on the so-called objective point of view of description. In order to pin down the origin of qualia, we need to incorporate the subjective point of view in a non-trivial manner. The clarification of the nature of the way how qualia in our mind are invoked by the physical processes in the brain and how the "subjectivity" structure which supports qualia is originated is an essential step in making compatible the subjective and objective points of view. The elucidation of the origin of qualia rich subjectivity is important not only as an activity in the natural sciences, but also as a foundation and the ultimate justification of the whole world of the liberal arts. Bridging the gap between the two cultures (C.P.Snow) is made possible only through a clear understanding of the origin of qualia and subjectivity. Qualia symbolize the essential intellectual challenge for the humanity in the future. -
A Programming and Problem-Solving Seminar
Dcccm bcr 1983 Report No. STAN-B-83-990 A Programming and Problem-Solving Seminar bY John D. Hobby and Donald E. Knuth Department of Computer Science Stanford University Stanford, CA 94305 . -_ -_y-- _ - Computer Science Department A PROGRAMMING AND PROBLEM-SOLVING SEMINAR bY John D. Hobby and Donald E. Knuth This report contains edited transcripts of the discussions held in Stanford’s course CS204, Problem Seminar, during autumn quarter 1982. Since the topics span a large range of ideas in computer science, and since most of the important research paradigms and programming paradigms were touched on during the discussions, these notes may be ‘of interest to graduate students of computer science at other universities, as well as to their professors and to professional people in the “real world.” The present report is the fifth in a series of such transcripts, continuing the tradi- tion established in STAN-CS-77-606 (Michael J. Clancy, 1977), STAN-CS-79-707 (Chris Van’ Wyk, 1979), STAN-CS-81-863 (Allan A. Miller, 1981), STAN-CS-83-989 (Joseph S. Weening, 1983). The production of this report was partially supported by National Science Foundation grant MCS-8300984. Table of Contents Index to problems in the five seminar transcripts . 3 Cast of characters . 4 Intro due tion . ..*.................................. 5 Problem l-Bulgarian Solitaire ........................................................ 6 October 5 ........................................................................ 6 October 7 ....................................................................... -
Transforming Ad Hoc EDA to Algorithmic EDA
Transforming Ad Hoc EDA to Algorithmic EDA Jason Cong Chancellor’s Professor, UCLA Director, Center for Domain-Specific Computing 1 The Early Years 蔡高中學 成功大學 麻省理工 學 院 Choikou Middle School National Cheng Kung University MIT Macau Taiwan USA 1952 1956 1958 2 Graduate Study at MIT (1958 – 1963) ▪ MS thesis: A Study in Machine-Aided Learning − A pioneer work in distant learning ▪ Advisor: Ronald Howard 3 Graduate Study at MIT ▪ PhD thesis: “Some Memory Aspects of Finite Automata” (1963) ▪ Advisor: Dean Arden − Professor of EE, MIT, 1956-1964 − Involved with Whirlwind Project − Also PhD advisor of Jack Dennis ▪ Jack was PhD advisor of Randy Bryant -- another Phil Kaufman Award Recipient (2009) 4 Side Story: Dean Arden’s Visit to UIUC in 1992 I am glad that I have better students than you 5 Side Story: Dean Arden’s Visit to UIUC in 1992 I feel blessed that I had a better advisor than all of you 6 Two Important Books in Computer Science in 1968 ▪ The Art of Computer Programming, Vol. 1, Fundamental Algorithms, Donald E. Knuth, 1968 ▪ Introduction to Combinatorial Mathematics, C. L. Liu, 1968 7 Sample Chapters in “Introduction to Combinatorial Mathematics” ▪ Chapter 3: Recurrence Relations ▪ Chapter 6: Fundamental Concepts in the Theory of Graphs ▪ Chapter 7: Trees, Circuits, and Cut-sets ▪ Chapter 10: Transport Networks ▪ Chapter 11: Matching Theory ▪ Chapter 12: Linear Programming ▪ Chapter 13: Dynamic Programming 8 Project MAC ▪ Project MAC (Project on Mathematics and Computation) was launched 7/1/1963 − Backronymed for Multiple Access Computer, -
The Logic of Qualia 1 Introduction
The Logic of Qualia Drew McDermott, 2014-08-14 Draft! Comments welcome! Do not quote! Abstract: Logic is useful as a neutral formalism for expressing the contents of mental representations. It can be used to extract crisp conclusions regarding the higher- order theory of phenomenal consciousness developed in (McDermott, 2001, 2007). A key aspect of conscious perceptions is their connection to the distinction between appearance and reality. Perceptions must often be corrected. To do so requires that the logic of perception be able to represent the logical structure of judgment events, that is, to include the formulas of the logic as objects to be reasoned about. However, there is a limit to how finely humans can examine their own represen- tations. Terms representing primary and secondary qualities seemed to be locked, so that the numbers (or levels of neural activation) that are their essence are not directly accessible. Humans feel a need to invoke “intrinsic,” “nonrelational” prop- erties of many secondary qualities — their qualia — to “explicate” how we compare and discriminate among them, although this is not actually how the comparisons are accomplished. This model of qualia explains several things: It accounts for the difference between “normal” and “introspective” access to a perceptual module in terms of quotation. It dissolves Jackson’s knowledge argument by explaining what Mary learns as a fictional but undoubtable belief structure. It makes spectrum in- version logically impossible by providing a degree of freedom between the physical structure of the brain and the representations it contains that redescribes putative cases of spectrum inversion as alternative but equivalent ways of mapping physical states to representational states.