GenEth: a general ethical dilemma analyzer

Abstract We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which intelligent autonomous systems are apt to be deployed and for the actions they are liable to undertake, as we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles needed for ethical guidance of the behavior of autonomous systems. Such principles help ensure the ethical behavior of complex and dynamic systems and further serve as a basis for justification of this behavior. To provide assistance in discovering ethical principles, we have developed GenEth, a general ethical dilemma analyzer that, through a dialog with ethicists, uses inductive logic programming to codify ethical principles in any given domain. GenEth has been used to codify principles in a number of domains pertinent to the behavior of autonomous systems and these principles have been verified using an Ethical Turing Test, a test devised to compare the judgments of codified principles with that of ethicists.

[1]  Michael Anderson,et al.  MedEthEx: A Prototype Medical Ethics Advisor , 2006, AAAI.

[2]  Alan Bundy,et al.  Representation as a Fluent: An AI Challenge for the Next Half Century , 2006, IEEE Intelligent Systems.

[3]  H. Lee Swanson,et al.  Working Memory, Short-term Memory, Speech Rate, Word Recognition and Reading Comprehension in Learning Disabled Readers: Does the Executive System Have a Role?. , 2000 .

[4]  Luc De Raedt,et al.  Probabilistic Inductive Logic Programming , 2004, ALT.

[5]  Antonija Mitrovic,et al.  Intelligent Tutors for All: The Constraint-Based Approach , 2007, IEEE Intelligent Systems.

[6]  M. Mitchell Waldrop,et al.  Man-Made Minds: The Promise of Artificial Intelligence, Mitchell M. Waldrop. 1988. Walker and Company, New York. 280 pages. Index. ISBN: 0-8027-0899-4. $22.95 , 1988 .

[7]  Marcello Guarini,et al.  Particularism and the Classification and Reclassification of Moral Cases , 2006, IEEE Intelligent Systems.

[8]  Michael Anderson,et al.  Machine Ethics: Creating an Ethical Intelligent Agent , 2007, AI Mag..

[9]  Colin Allen,et al.  Prolegomena to any future artificial moral agent , 2000, J. Exp. Theor. Artif. Intell..

[10]  Joachim Diederich,et al.  Rule Extraction from Support Vector Machines , 2008, Studies in Computational Intelligence.

[11]  Thomas M. Powers Prospects for a Kantian Machine , 2006, IEEE Intelligent Systems.

[12]  Susan Leigh Anderson,et al.  Robot be good. , 2010, Scientific American.

[13]  Selmer Bringsjord,et al.  Toward a General Logicist Methodology for Engineering Ethically Correct Robots , 2006, IEEE Intelligent Systems.

[14]  Christopher Grau,et al.  There Is No "I" in "Robot": Robots and Utilitarianism , 2006, IEEE Intelligent Systems.

[15]  M. Mitchell Waldrop,et al.  A Question of Responsibility , 1987, AI Mag..

[16]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[17]  Saso Dzeroski,et al.  Inductive Logic Programming: Techniques and Applications , 1993 .

[18]  Luís Moniz Pereira,et al.  Machine Ethics: Modeling Morality with Prospective Logic , 2011 .

[19]  Joachim Diederich,et al.  Rule Extraction from Support Vector Machines: An Introduction , 2008, Rule Extraction from Support Vector Machines.

[20]  Bruce M. McLaren,et al.  Extensionally defining principles and cases in ethics: An AI model , 2003, Artif. Intell..

[21]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[22]  J. Gips Towards the ethical robot , 1995 .

[23]  Kenji Araki,et al.  What Statistics Could Do for Ethics? : The Idea of Common Sense Processing Based Safety Valve , 2005, AAAI 2005.

[24]  Bart Baesens,et al.  Rule Extraction from Support Vector Machines: An Overview of Issues and Application in Credit Scoring , 2008, Rule Extraction from Support Vector Machines.

[25]  A. F. Umar Khan,et al.  The ethics of autonomous learning systems , 1995 .

[26]  John D. Rawls,et al.  Outline of a Decision Procedure for Ethics , 1951 .

[27]  Luc De Raedt,et al.  Probabilistic inductive logic programming , 2004 .