Rational Machines and Artificial Intelligence
- 1st Edition - March 31, 2021
- Imprint: Academic Press
- Author: Tshilidzi Marwala
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 0 6 7 6 - 8
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 0 9 4 4 - 8
Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning.… Read more
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Request a sales quoteIntelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts.
- Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective?
- Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions
- Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets
- Discusses the application of Moore’s Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality
Researchers and developers in Computer Science, Biomedical Engineering, Artificial Intelligence, Applied Informatics, Bioinformatics, Neural Engineering, Applied Mathematics, and Computational Intelligence
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface
- Chapter 1: Introduction to machine and human rationality
- Abstract
- 1.1: Introduction
- 1.2: Machine rationality
- 1.3: Fourth industrial revolution
- 1.4: Artificial intelligence
- 1.5: Summary of the book
- Chapter 2: What is machine vs human rationality?
- Abstract
- 2.1: Introduction
- 2.2: What is utility?
- 2.3: What is rationality?
- 2.4: Utility of actions
- 2.5: State and action utility measurement
- 2.6: Bounded rationality
- 2.7: Seeking a bounded rational model
- 2.8: Human rationality: Clay pots
- 2.9: Machine rationality: Condition monitoring
- 2.10: Conclusions
- Chapter 3: Rational machine
- Abstract
- 3.1: Introduction
- 3.2: What is a rational machine?
- 3.3: Artificial intelligence
- 3.4: Knowledge representation
- 3.5: Rational machines
- 3.6: Conclusions
- Chapter 4: Flexibly bounded rationality
- Abstract
- 4.1: Introduction
- 4.2: Rational decision-making
- 4.3: Bounded rational decision-making
- 4.4: Flexibly bounded rational decision-making of humans
- 4.5: Flexibly bounded rational decision-making of machines
- 4.6: Flexibly bounded rationality humans vs machines
- 4.7: Humans vs machines: Case of radiology
- 4.8: Conclusions
- Chapter 5: Rational expectation
- Abstract
- 5.1: Introduction
- 5.2: Adaptive expectations
- 5.3: Knowledge representation of man vs machines
- 5.4: Machines vs human decision-making
- 5.5: Rational expectation and interstate conflict
- 5.6: Rational expectation of HIV infection
- 5.7: Conclusions
- Chapter 6: Rational choice
- Abstract
- 6.1: Introduction
- 6.2: What is rational choice?
- 6.3: Information
- 6.4: Choices
- 6.5: Optimization
- 6.6: Rational choice
- 6.7: Human vs artificial intelligence rational choice
- 6.8: Interstate conflict and human vs machine rational choice
- 6.9: Conclusions
- Chapter 7: Bounded rational counterfactuals
- Abstract
- 7.1: Introduction
- 7.2: Counterfactuals
- 7.3: Counterfactuals and causality
- 7.4: Rational counterfactuals
- 7.5: Bounded rational counterfactuals in politics
- 7.6: Bounded rational counterfactuals in history
- 7.7: Bounded counterfactuals in engineering
- 7.8: Bounded rational counterfactuals in interstate conflict
- 7.9: Counterfactuals and artificial intelligence
- 7.10: Conclusions
- Chapter 8: Rational opportunity cost
- Abstract
- 8.1: Introduction
- 8.2: Counterfactuals
- 8.3: Opportunity cost
- 8.4: Game theory and opportunity cost
- 8.5: Rational opportunity cost
- 8.6: Artificial intelligence and rational opportunity cost
- 8.7: Handling rational opportunity cost
- 8.8: Conclusions
- Chapter 9: Can machines be rational?
- Abstract
- 9.1: Introduction
- 9.2: What is rationality?
- 9.3: What did Herbert Simon say?
- 9.4: Data information and rationality
- 9.5: What happens when replacing humans with machines?
- 9.6: Digital and quantum computing
- 9.7: All models are wrong
- 9.8: Can machines be rational?
- 9.9: St. Petersburg Paradox and rationality
- 9.10: Conclusion
- Chapter 10: Can rationality be measured?
- Abstract
- 10.1: Introduction
- 10.2: Information
- 10.3: Model: Biological and artificial brain
- 10.4: What about the uncertainty principle?
- 10.5: Optimization
- 10.6: Classification of rationality
- 10.7: Rational decision-making
- 10.8: What is irrationality?
- 10.9: Marginalization of irrationality theory
- 10.10: Marginalization of irrationality in decision-making
- 10.11: Rationality quantification
- 10.12: Rationality and condition monitoring
- 10.13: Conclusion
- Chapter 11: Is machine rationality subjective?
- Abstract
- 11.1: Introduction
- 11.2: Optimization
- 11.3: Choosing optimization method
- 11.4: Local optimization
- 11.5: Global optimization
- 11.6: Is a single goal optimization subjective?
- 11.7: Does multicriteria optimization make rationality subjective?
- 11.8: The curse of dimensionality and model complexity
- 11.9: Is machine rationality subjective?
- 11.10: Conclusion
- Chapter 12: Group vs individual rationality
- Abstract
- 12.1: Introduction
- 12.2: Democracy
- 12.3: Authoritarianism
- 12.4: Democracy vs authoritarianism
- 12.5: Committee of rational machines
- 12.6: Theory of committee of networks
- 12.7: Application to condition monitoring
- 12.8: Conclusions
- Chapter 13: Human vs machine rationality
- Abstract
- 13.1: Introduction
- 13.2: Human vs machine chess player
- 13.3: Human vs machine go player
- 13.4: Human-driven vs autonomous vehicles (AVs)
- 13.5: Human vs autonomous aircraft pilot
- 13.6: Human vs machine language translator
- 13.7: Human vs machine rational expectations
- 13.8: Human vs machine: Optimal stopping problem
- 13.9: Human vs machine rational choice
- 13.10: Human vs machine game theory and mechanism design
- 13.11: Human vs machine rational counterfactuals
- 13.12: Human vs machine rational opportunity cost
- 13.13: Human vs machine rationality subjectivity
- 13.14: Human vs machine group and individual rationality
- 13.15: Machine vs human rationality vs prospect theory
- 13.16: Conclusion
- Chapter 14: Rational markets
- Abstract
- 14.1: Introduction
- 14.2: Efficient market hypothesis
- 14.3: Historical prices and market rationality
- 14.4: Causality and market rationality
- 14.5: Historical prices, internet, and market rationality
- 14.6: Historical prices, internet, private information, and market rationality
- 14.7: Rational expectations and market rationality
- 14.8: Bounded rationality and market rationality
- 14.9: Rational choice and market rationality
- 14.10: Information asymmetry and market rationality
- 14.11: Biases, heuristics, and market rationality
- 14.12: Prospect theory and market rationality
- 14.13: Irrational exuberance and market efficiency
- 14.14: Evolution of market efficiency
- 14.15: Conclusion
- Chapter 15: Human vs machine ethics
- Abstract
- 15.1: Introduction
- 15.2: Normative vs scientific laws
- 15.3: Governance and ethics
- 15.4: Machine ethics
- 15.5: Data
- 15.6: Model: Algorithms and testing
- 15.7: Decisions and actuators
- 15.8: Contemporary ethical issues
- 15.9: Conclusion
- Chapter 16: Conclusion
- Abstract
- 16.1: Introduction
- 16.2: Rationality
- 16.3: Bounded rationality, rational expectations, and rational choice
- 16.4: Rational counterfactual and opportunity cost
- 16.5: Rationality quantification and subjectivity
- 16.6: Rationality, groups, markets, and ethics
- 16.7: Conclusion
- Nomenclature
- Appendix A: Data
- Abstract
- A.1: Suspended beam
- A.2: Cylindrical shells
- A.3: Interstate conflict
- A.4: HIV database
- Appendix B: Subjectivity vs relativity
- Abstract
- B.1: Introduction
- B.2: Newtonian mechanics
- B.3: Maxwell’s equations
- B.4: Michaelson-Morley experiment
- B.5: FitzGerald-Lorentz transformation
- B.6: Relative mass
- B.7: Einstein’s theory of relativity
- B.8: Subjectivity vs objectivity vs relativity
- Appendix C: Algorithms
- Abstract
- C.1: Fuzzy system
- C.2: Genetic algorithm
- Index
- Edition: 1
- Published: March 31, 2021
- No. of pages (Paperback): 270
- No. of pages (eBook): 270
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780128206768
- eBook ISBN: 9780128209448
TM
Tshilidzi Marwala
Dr. Tshilidzi Marwala is the Rector of the United Nations (UN) University and the UN Under-Secretary-General from 1 March 2023. He was previously the Vice-Chancellor and Principal of the University of Johannesburg, Deputy Vice-Chancellor for Research and Executive Dean of the Faculty of Engineering at the University of Johannesburg. He was Associate Professor, Full Professor, the Carl and Emily Fuchs Chair of Systems and Control Engineering at the University of the Witwatersrand. He holds a Bachelor of Science in Mechanical Engineering (magna cum laude) from Case Western Reserve University, a Master of Mechanical Engineering from the University of Pretoria, PhD in Artificial Intelligence from the University of Cambridge and a Post-Doc at Imperial College (London). He is a registered professional engineer, a Fellow of TWAS (The World Academy of Sciences), the Academy of Science of South Africa, the African Academy of Sciences and the South African Academy of Engineering. He is a Senior Member of the IEEE and a distinguished member of the ACM. His research interests are multi-disciplinary and they include the theory and application of artificial intelligence to
engineering, computer science, finance, social science and medicine. He has supervised 28 Doctoral students published 15 books in artificial intelligence (one translated into Chinese), over 300 papers in journals, proceedings, book chapters and magazines and holds five patents. He is an associate editor of the International Journal of Systems Science (Taylor and Francis Publishers). He has been a visiting scholar at Harvard University, University of California at Berkeley, Wolfson College of the University of Cambridge, Nanjing Tech University and Silesian University of Technology in Poland. His opinions have appeared in the New Scientist, The Economist, Time Magazine, BBC, CNN and the Oxford Union. Dr. Marwala is the author of Rational Machines and Artificial Intelligence from Elsevier Academic Press.
Affiliations and expertise
Rector of the United Nations (UN) University and the UN Under-Secretary-General in Tokyo, Japan, from 1 March 2023Read Rational Machines and Artificial Intelligence on ScienceDirect