What is Artificial Intelligence‪?‬

This book engages with the title question: what is artificial intelligence (AI)? Instead of reiterating received definitions or surveying the field from a disciplinary perspective, the question is engaged here by putting two standpoints into conversation. The standpoints are different in their disciplinary groundings — i.e. technology and the humanities — and also in their approaches — i.e. applied and conceptual. Peter is an AI engineer: his approach is in terms of how to make AI work. Suman is a humanities researcher: his approach is in terms of what people and academics mean when they say 'AI'.A coherent argument, if not a consensus, develops by putting the two standpoints into conversation. The conversation is presented in 32 short chapters, in turn by Suman and Peter. There are two parts: Part 1, Questioning AI, and Part 2, AI and Government Policy. The first part covers issues such as the meaning of intelligence, automation, evolution, artificial and language. It outlines some of the processes through which these concepts may be technologically grounded as AI. The second part addresses policy considerations that underpin the development of AI and responds to the consequences. Themes taken up here include: rights and responsibilities; data usage and state-level strategies in the USA, UK and China; unemployment and policy futures.Contents: Part 1: Questioning AI: Setting Terms More Terms Questioning Terms, and a Provisional Concept of Intelligence Elaborating Terms Methods and Approaches Methods and Field Discerning the Intelligent Agent Realising the Intelligent Agent Recognising the Intelligent Agent The Intelligent Agent in the Prospect Devolving Evolution Evolution as a Creativity Engine Evolution and Articles of Faith On Evolution: Ungrounded Hardwired Knowledge Short Circuits Intelligence On Evolution: Intelligence Short Circuits Ungrounded Hardwired Knowledge Reflections on the Artificial in AI Parameters of the Artificial in AI Limits of the Artificial in AI Restrictions on AI Research Expectations of AI Research Part 2: AI and Government Policy: Policy and Legal Autonomy Autonomy and Grounding Responsibility Legal Autonomy: Rights and Responsibilities Autonomy: Limiting and Conferring Rights Note on Rights and Data Matters Note on Qualia and Using Data Doubting Qualia and Social Data Data Users and Data Doubters Data Distinctions and Data Nations Data Doubters and Data Owners Populism, Jobs and Policy Futures Jobs, Futures and AI Engineers Readership: General informed readers. Readers with knowledge of AI and its underpinning principles will be interested. In particular, those with a disciplinary background in computing and technological development, policy studies, current affairs, philosophy and discourse analysis. Appropriate for undergraduate students and upwards, or those whose interest is more conceptual than the general user of technology. Intention;Final Purpose;Grounding;Consciousness;Recognition;Classification;Detection;Perception;Evolution;Creativity;Search;Optimization;Convolution Neural Networks;Face Recognition;Ethics;Data Scientists;Reinforcement Learning;Generative Methods;Discriminative Methods;Qualia;Statistics;automaton;natural language;Third Wave AI;Emergent Language;Agency;Artifice;Personhood;Responsibility;Awareness;Populism;Social Statistics;Climate0Key Features: Engages with the field of AI research and policy as a conversation between two distinct standpoints: science/technology and humanities/social studies; instrumental (applied) and conceptual (clarificatory); inductive and deductive reasoning. Genuinely interdisciplinary The focus throughout is on contested concepts and unresolved questions in the field. The book therefore offers a front-line sense of the field Attention is given both to the content of the field and to the manner in which (preconceptions with which) it is expressed. This is extremely rare in existing publications on AI The presentation of the book as a conversation...