Why the world wants controls over Artificial Intelligence

Abstract This article reviews the nature, the current state and possible future of Artificial Intelligence (AI). AI is described both in the abstract and in four forms that are currently evident not only in laboratories but also in real-world applications. Clarity about the public's concerns is sought by articulating the threats that are inherent within AI. It is proposed that AI needs to be re-conceived as `complementary artefact intelligence', and that the robotics notion of `machines that think' needs to give way to the idea of `intellectics', with the focus on `computers that do'. This article lays a foundation for two further articles on how organisations can adopt a responsible approach to AI, and how an appropriate regulatory scheme for AI can be structured.

[1]  Hubert L. Dreyfus,et al.  What computers still can't do - a critique of artificial reason , 1992 .

[2]  Thomas B. Sheridan,et al.  Human and Computer Control of Undersea Teleoperators , 1978 .

[3]  Roger Clarke,et al.  What drones inherit from their ancestors , 2014, Comput. Law Secur. Rev..

[4]  Roger Clarke,et al.  Understanding the drone epidemic , 2014, Comput. Law Secur. Rev..

[5]  Gary Marcus,et al.  Deep Learning: A Critical Appraisal , 2018, ArXiv.

[6]  Roger A. Clarke,et al.  A contingency approach to the application software generations , 1991, DATB.

[7]  Steve Mann,et al.  Cyborg: Digital Destiny and Human Possibility in the Age of the Wearable Computer , 2001 .

[8]  Sandra Wachter,et al.  A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI , 2018 .

[9]  Roger Clarke,et al.  Big data, big risks , 2016, Inf. Syst. J..

[10]  Steve Mann.  Wearable Computing: Toward Humanistic Intelligence , 2001 .

[11]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[12]  Wolfgang Bibel.  The technological change of reality: Opportunities and dangers , 2005, AI & SOCIETY.

[13]  Benjamin Kuipers,et al.  Computer power and human reason , 1976, SGAR.

[14]  Roger Clarke,et al.  Surfing the third wave of computing: A framework for research into eObjects , 2015, Comput. Law Secur. Rev..

[15]  Emilio Frazzoli,et al.  A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles , 2016, IEEE Transactions on Intelligent Vehicles.

[16]  Raymond C. Kurzweil,et al.  The Singularity Is Near , 2018, The Infinite Desire for Growth.

[17]  Heiko Mueller,et al.  Problems , Methods , and Challenges in Comprehensive Data Cleansing , 2005 .

[18]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[19]  D. Boyd,et al.  CRITICAL QUESTIONS FOR BIG DATA , 2012 .

[20]  James S. Albus,et al.  Outline for a theory of intelligence , 1991, IEEE Trans. Syst. Man Cybern..

[21]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[22]  Roger Clarke,et al.  Cyborg Rights , 2010, IEEE Technology and Society Magazine.

[23]  Roger Clarke.  Quality Assurance for Security Applications of Big Data , 2016, 2016 European Intelligence and Security Informatics Conference (EISIC).

[24]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[25]  A. J. Armstrong.  DEVELOPMENT OF A METHODOLOGY FOR DERIVING SAFETY METRICS FOR UAV OPERATIONAL SAFETY PERFORMANCE MEASUREMENT , 2010 .

[26]  John McCarthy,et al.  A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955 , 2006, AI Mag..

[27]  Agustí Verde Parera,et al.  General data protection regulation , 2018 .

[28]  D. C. Englebart,et al.  Augmenting human intellect: a conceptual framework , 1962 .

[29]  Viktor Mayer-Schnberger,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2013 .

[30]  Jenna Burrell,et al.  How the machine ‘thinks’: Understanding opacity in machine learning algorithms , 2016 .

[31]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[32]  Steve Mann.  Guest Editor's Introduction: Wearable Computing-Toward Humanistic Intelligence , 2001, IEEE Intell. Syst..

[33]  Jennifer Widom,et al.  Research problems in data warehousing , 1995, CIKM '95.

[34]  Margaret A. Boden,et al.  AI: Its Nature and Future , 2016 .

[35]  John Durkin,et al.  Expert Systems , 1994 .

[36]  Roman V. Yampolskiy,et al.  Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures , 2016, ArXiv.

[37]  Julia Powles,et al.  "Meaningful Information" and the Right to Explanation , 2017, FAT.

[38]  Kevin Warwick,et al.  The Cyborg Revolution , 2014, NanoEthics.

[39]  Charles Anderson,et al.  The end of theory: The data deluge makes the scientific method obsolete , 2008 .

[40]  Eric Gossett,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2015 .

[41]  Chris Hables Gray,et al.  The cyborg handbook , 1995 .

[42]  Katina Michael,et al.  Engineering-Based Design Methodology for Embedding Ethics in Autonomous Robots , 2019, Proceedings of the IEEE.

[43]  Matthew U. Scherer.  Regulating Artificial Intelligence Systems: Risks, Challenges, Competencies, and Strategies , 2015 .

[44]  R. Bharath,et al.  Risks of artificial Intelligence , 2016 .

[45]  Zhaohui Wu,et al.  Cyborg Intelligence: Recent Progress and Future Directions , 2016, IEEE Intelligent Systems.

[46]  Titu-Marius I. Băjenescu.  The risks of artificial intelligence , 2018 .