LEADER 02522oam 2200553I 450 001 9910154883603321 005 20230809233556.0 010 $a1-317-14940-8 010 $a1-315-57764-X 010 $a1-317-14941-6 024 7 $a10.1201/9781315577647 035 $a(CKB)4340000000018638 035 $a(MiAaPQ)EBC4751226 035 $a(OCoLC)964699077 035 $a(EXLCZ)994340000000018638 100 $a20180331h20172017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aDistributed cognition and reality $ehow pilots and crews make decisions /$fKatherine L. Plant, Neville A. Stanton 210 1$aBoca Raton :$cCRC Press,$d[2017] 210 4$dİ2017 215 $a1 online resource (277 pages) $cillustrations 225 0 $aHuman factors and socio-technical systems 311 $a0-367-88207-8 311 $a1-4724-8298-0 320 $aIncludes bibliographical references and index. 327 $achapter 1. Introduction -- chapter 2. Schema theory : past, present and future -- chapter 3. Case study of the Kegworth plane crash : understanding local rationality with the perceptual cycle model -- chapter 4. A pilot study : using the perceptual cycle model and critical decision method to understand decision-making processes in the cockpit -- chapter 5. Examining the validity of Neisser's perceptual cycle model with accounts from critical decision-making in the cockpit -- chapter 6. Development of a perceptual cycle classification scheme -- chapter 7. Schema world action research method for understanding perceptual cycle processes -- chapter 8. Team perceptual cycle processes -- chapter 9. Exploring distributed cognition in search and rescue teams -- chapter 10. Conclusions. 606 $aAeronautics$xHuman factors 606 $aDistributed cognition 606 $aAirplanes$xPiloting$xDecision making 606 $aFlight crews 606 $aGroup decision making 615 0$aAeronautics$xHuman factors. 615 0$aDistributed cognition. 615 0$aAirplanes$xPiloting$xDecision making. 615 0$aFlight crews. 615 0$aGroup decision making. 676 $a629.132/52019 700 $aPlant$b Katherine L.$0929896 702 $aStanton$b Neville A$g(Neville Anthony),$f1960- 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910154883603321 996 $aDistributed cognition and reality$92091093 997 $aUNINA LEADER 06287oam 2200553Mu 450 001 9910793767203321 005 20190820011821.0 010 $a0-429-67119-9 010 $a0-429-67268-3 010 $a0-429-00112-6 024 7 $a10.1201/9780429001123 035 $a(CKB)4100000008701622 035 $a(MiAaPQ)EBC5824983 035 $a(OCoLC)1109833607 035 $a(OCoLC-P)1109833607 035 $a(FlBoTFG)9780429001123 035 $a(EXLCZ)994100000008701622 100 $a20190720d2019 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAI and Human Thought and Emotion 210 $aMilton $cAuerbach Publications$d2019 215 $a1 online resource (267 pages) 300 $a4.3.1 The Scientific Clean Sweep 311 $a0-367-02929-4 320 $aIncludes bibliographical references. 327 $aCover; Half Title; Title Page; Copyright Page; Contents; Author; 0 Introduction; 0.1 Frustrations and Opportunities in AI Research; 0.2 Central Questions; 0.3 Structure of This Volume; 0.4 How to Read This Book; PART I: INTELLIGENCE IN COMPUTERS, HUMANS AND SOCIETIES; 1 Artificial Intelligence as It Stands; 1.1 About AI; 1.1.1 AI's Relation to Psychology, Cognitive Science, etc.; 1.1.2 What Are Intelligence, Consciousness, and Introspection; 1.1.3 Defining and Viewing AI; 1.2 First Approach: Logic and Mathematics; 1.3 Second Approach: Biological Inspiration 327 $a1.4 A Half-Approach, and a Point or Two1.5 Watson; 1.5.1 Explicit Motivations; 1.5.2 Arguments against Introspection; 1.5.3 Interesting Points; 1.5.4 Watson -- Summary; 1.6 Simon; 1.6.1 Economics; 1.6.2 Hostile to Subjectivity -- Rationalistic; 1.6.3 Artificial Intelligence; 1.6.4 Against His Critics; 1.6.5 Flirting with Subjectivity; 1.7 AI as It Stands -- Summary; 2 Current Critiques of Artificial Intelligence; 2.1 Background: Phenomenology and Heidegger; 2.1.1 Phenomenology; 2.1.2 Heidegger; 2.2 The Cognition vs Phenomenology Debate; 2.3 Dreyfus 327 $a2.3.1 Part I -- Ten Years of Research in Artificial Intelligence (1957-1967)2.3.2 Part II -- Assumptions Underlying Persistent Optimism; 2.3.3 Part III -- Alternatives to the Traditional Assumptions; 2.3.4 Dreyfus's Updated Position; 2.4 Winograd and Flores; 2.4.1 Cognition as a Biological Phenomenon; 2.4.2 Understanding and Being; 2.4.3 Language as Listening and Commitment; 2.5 Hermeneutics and Gadamer; 2.5.1 Hermeneutics; 2.5.2 The Hermeneutics of Heidegger and Gadamer; 2.6 AI's Inadequate Response to Dreyfus and Other Critiques; 2.7 Locating This Project amongst Existing Thinkers 327 $a2.8 Current Critiques of AI: Summary3 Human Thinking: Anxiety and Pretence; 3.1 Individual Thinking; 3.1.1 Our Thinking Processes Are Embarrassing; 3.1.2 Anxiety, Pretence, Stories, and Comfort; 3.1.3 Can We Even Tell the Truth?; 3.1.4 Motivations; 3.2 Society's Thinking; 3.2.1 Politics; 3.2.2 Social Perceptions of Science; 3.2.3 Interrelation of Politics and Science; 3.2.4 Distinct Disciplines and Education; 3.2.5 Education as Indoctrination; 3.3 Adapting to Social Norms; 3.3.1 Social Pressure -- the Game of Life; 3.3.2 Conforming; 3.3.3 Escape to a Role, Arrogance; 3.3.4 Needs Must 327 $a3.4 Relevance to AI3.4.1 Anxiety and Pretence Are Immediately Relevant to Thinking; 3.4.2 Implications for AI, a Rudimentary Human-Like Mind; 3.4.3 Meaning-for-Me vs Big Data; 3.4.4 Relevance to AI -- the Future; 3.5 Human Thinking: Anxiety and Pretence: Summary; 4 Prevailing Prejudices Pertaining to Artificial Intelligence; 4.1 A History of an Idea: Positivism; 4.2 Knowledge; 4.2.1 Truth Exists, Is Knowable, and Can Be Expressed in Language; 4.2.2 There Is Only One Truth System; 4.2.3 Kinds of Illumination; 4.2.4 Polarisation of Knowledge and Doubt; 4.3 Science 330 $aThe field of artificial intelligence (AI) has grown dramatically in recent decades from niche expert systems to the current myriad of deep machine learning applications that include personal assistants, natural-language interfaces, and medical, financial, and traffic management systems. This boom in AI engineering masks the fact that all current AI systems are based on two fundamental ideas: mathematics (logic and statistics, from the 19th century), and a grossly simplified understanding of biology (mainly neurons, as understood in 1943). This book explores other fundamental ideas that have the potential to make AI more anthropomorphic. Most books on AI are technical and do not consider the humanities. Most books in the humanities treat technology in a similar manner. AI and Human Thought and Emotion, however is about AI, how academics, researchers, scientists, and practitioners came to think about AI the way they do, and how they can think about it afresh with a humanities-based perspective. The book walks a middle line to share insights between the humanities and technology. It starts with philosophy and the history of ideas and goes all the way to usable algorithms. Central to this work are the concepts of introspection, which is how consciousness is viewed, and consciousness, which is accessible to humans as they reflect on their own experience. The main argument of this book is that AI based on introspection and emotion can produce more human-like AI. To discover the connections among emotion, introspection, and AI, the book travels far from technology into the humanities and then returns with concrete examples of new algorithms. At times philosophical, historical, and technical, this exploration of human emotion and thinking poses questions and provides answers about the future of AI. 606 $aArtificial intelligence$xPsychological aspects 606 $aAffect (Psychology)$xComputer simulation 606 $aThought and thinking 615 0$aArtificial intelligence$xPsychological aspects. 615 0$aAffect (Psychology)$xComputer simulation. 615 0$aThought and thinking. 676 $a153.42028563 700 $aFreed$b Sam$c(Philosophy professor),$01493857 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910793767203321 996 $aAI and Human Thought and Emotion$93717087 997 $aUNINA