Approaches to Forming ETHICAL AI as an Artificial Moral Agent: Suggesting Virtue Education Method Through Comparison of Top-Down and Bottom-Up Approaches
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Purpose: The purpose of this study is to propose that the virtue education method can be utilized in the pro-cess of learning to have ethics as an Artificial Moral Agent(AMA). Recent various discussions about AI presuppose the coexistence of humans and AI. Meanwhile, in order for coexistence to be achieved, it is fundamentally neces-sary for humans as individual beings to form relationships with others in an appropriate way. This study focused on the use of the virtue education method among the methods for AI to learn the order of relationships as an AMA that becomes the counterpart of human ethical behavior in the interaction between humans and AI. Method: This study presented basic data using the method of literature research. And based on this, a virtue education method that can be applied to AMA was developed and presented using the method of development research. With this, This research tried to argue about the necessity and validity of the virtue education method. Results: This study examines that the current discussion on ethical learning in AMA is mainly based on a Top-down approach based on traditional ethical theory. And as an alternative to this, it is suggested that machine learning and deep learning methods can be used as a method for AMA to learn ethics. Based on this, the charac-teristics and validity of virtue ethics applicable to AMA were presented. And as a method to learn it, a teaching and learning method applicable to the learning of AMA was proposed. Conclusion: Currently, the approach to preparing ethics for AMA tends to mainly choose a Top-down ap-proach in which a specific ethical theory is selected and the design of a computational algorithm and system that can implement the theory is derived. However, just as children develop moral reasoning through appropriate de-velopmental stages, AMA also needs to actively introduce a bottom-up approach to forming ethical judgment principles. As a specific method, we propose to use the method of grafting the virtue education method of analyz-ing the characteristics of a virtuous person and repeating it by imitating it to the deep learning method of AI.
Abstract
Purpose: The purpose of this study is to propose that the virtue education method can be utilized in the pro-cess of learning to have ethics as an Artificial Moral Agent(AMA). Recent various discussions about AI presuppose the coexistence of humans and AI. Meanwhile, in order for coexistence to be achieved, it is fundamentally neces-sary for humans as individual beings to form relationships with others in an appropriate way. This study focused on the use of the virtue education method among the methods for AI to learn the order of relationships as an AMA that becomes the counterpart of human ethical behavior in the interaction between humans and AI. Method: This study presented basic data using the method of literature research. And based on this, a virtue education method that can be applied to AMA was developed and presented using the method of development research. With this, This research tried to argue about the necessity and validity of the virtue education method. Results: This study examines that the current discussion on ethical learning in AMA is mainly based on a Top-down approach based on traditional ethical theory. And as an alternative to this, it is suggested that machine learning and deep learning methods can be used as a method for AMA to learn ethics. Based on this, the charac-teristics and validity of virtue ethics applicable to AMA were presented. And as a method to learn it, a teaching and learning method applicable to the learning of AMA was proposed. Conclusion: Currently, the approach to preparing ethics for AMA tends to mainly choose a Top-down ap-proach in which a specific ethical theory is selected and the design of a computational algorithm and system that can implement the theory is derived. However, just as children develop moral reasoning through appropriate de-velopmental stages, AMA also needs to actively introduce a bottom-up approach to forming ethical judgment principles. As a specific method, we propose to use the method of grafting the virtue education method of analyz-ing the characteristics of a virtuous person and repeating it by imitating it to the deep learning method of AI.
참고문헌 (20)
- Allen C, "Artificial Morality: Top-down, Bottom-up, and Hybrid Approaches", Ethics and Information Technology, 7, pp.149~155 (2005)
- Dennett D, "Cognitive Science as Reverse Engineering Several Meanings of “Top-down” and “Bottom-up”", Studies in Logic and the Foundations of Mathematics, 134, pp.679~689 (1995)
- Blockeel H., "Top-down Induction of First Order Logical Decision Trees", AI Communications, 12(1-2), pp.119~120 (1999)
- Rokach L, "Top-down Induction of Decision Trees Classifiers -A Survey", IEEE Transactions on Systems, Man, and Cybernetics, 35(4), pp.476~487 (2005)
- Yi Li, "AI Ethics and Privacy Right", Robotics & AI Ethics, 5(2), pp.27~33 (2020), J-INSTITUTE
- 김윤경, "Rubrics and Schoolwide Approach to the Character Education and Some Implications to AI-Based Character Education", Robotics & AI Ethics, 5(2), pp.19~26 (2020), J-INSTITUTE
- Kim Tae-woong, "IR4.0 and Ethical Tasks of AI", Robotics & AI Ethics, 4(2), pp.6~13 (2019), J-INSTITUTE
- 김현수, "Ethical Issues on AI Equipped Combat ROBOTS", Robotics & AI Ethics, 5(2), pp.1~7 (2020), J-INSTITUTE
- Nussbaum MC, "Virtue Ethics: A Misleading Category?", The Journal of Ethics, 3, pp.163~201 (1999)
- McAleer S, "An Aristotelian Account of Virtue Ethics: An Essay in Moral Taxonomy", Pacific Philosophical Quarterly, 88, pp.208~225 (2007)
- Wallach W, "Consciousness and Ethics: Artificially Conscious Moral Agents", International Journal of Machine Consciousness, 3(1), pp.177~192 (2011)
- Hew PC, "Artificial Moral Agents are Infeasible with Foreseeable Technologies", Ethics and Information Technology, 16, pp.197~206 (2014)
- Allen C, "Prolegomena to Any Future Artificial Moral Agent", Journal of Experimental & Theoretical Artificial Intelligence, 12(3), pp.251~261 (2010)
- Muller VC, "Risks of General Artificial Intelligence", Journal of Experimental & Theoretical Artificial Intelligence, 26(3), pp.297~301 (2014)
- Torres P, "The Possibility and Risks of Artificial General Intelligence", Bulletin of the Atomic Scientist, 75(3), pp.105~108 (2019)
- Omohundro S, "Autonomous Technology and the Greater Human Good", Journal of Experimental & Theoretical Artificial Intelligence, 26(3), pp.303~315 (2014)
- Cervantes JA, "Artificial Moral Agents: A Survey of the Current Status", Science and Engineering Ethics, 26, pp.501~532 (2020)
- 김태웅, "Future Oriented SMART SOCIETY and Ethical Issues", Robotics & AI Ethics, 6(1), pp.35~44 (2021), J-INSTITUTE
- 김현수, "Suggestion of Building the AI Code of ETHICS through Deep Learning and Big Data Based AI", Robotics & AI Ethics, 6(1), pp.29~34 (2021), J-INSTITUTE
- 이상수, "AI-Based CYBERSECURITY: Benefits and Limitations", Robotics & AI Ethics, 6(1), pp.18~28 (2021), J-INSTITUTE