ABSTRACT
The rapid development of autonomous systems and their presence in human life force them to make quick decisions based on Big Data. Many of these decisions involve moral judgments that are then transformed into specific actions. Side effects of the choices made by the decision systems can be dangerous, so we have to be very careful when increasing the capacity of these systems. The decisions the autonomous systems make should be as ethical as possible.
This paper adapts the observe-orient-decide-act (OODA) loop to the decision-making process in the moral area. It combines the parameterization of cognitive aspects of autonomous systems with ethical standards and moral inference. Problems related to the implementation of moral inference to autonomous systems, including artificial intelligence (AI) systems, are presented. Thanks to the adaptation of the OODA loop, it is possible to make morally correct decisions and actions based on a set of ethical principles adjusted to a specific situation.
The presented proposal allows for moral inference, which extends the possibilities of autonomous systems that use the inference loop, especially those processing Big Data. The decision-making system still has the possibility of a choice aimed at doing more good or less evil.
- [1] British Standards Institute. 2016. BS 8611:2016. Ethical design and application of robots.Google Scholar
- [2] Ian T. Brown. 2018. A new conception of war: John Boyd, the US marines, and maneuver warfare. Marine Corps University Press, Marine Corps Base Quantico, VA, USA.Google Scholar
- [3] Karni A. Chagal-Feferkorn. 2019. Am I an algorithm or a product: when products liability should apply to algorithmic decision-makers. Stanford Law & Policy Review 30, 61-114.Google Scholar
- [4] Nicola Fabiano. 2019. Ethics and the protection of personal data. Journal on Systemics, Cybernetics and Informatics 17, 2 (2019), 58-64.Google Scholar
- [5] Federal Ministry of Transport and Digital Infrastructure of the Federal Republic of Germany. 2017. Report by the Ethics Commission on Automated and Connected Driving. June.Google Scholar
- [6] Horward E. Gardner. 2000. Intelligence reframed: multiple intelligences for the 21st century. Hachette, UK.Google Scholar
- [7] Bryan Harris. 2014. Closing the OODA Loop: Using Big Data and Analytics to Improve Decision Making. SAS Global Conclusions Paper, 2 (2014).Google Scholar
- [8] Gry Hasselbalch. 2021. A framework for a data interest analysis of artificial intelligence. First Monday 26, 7 (2021), https://doi.org/10.5210/fm.v26i7.11091Google Scholar
- [9] Patrick Henz. 2021. Ethical and legal responsibility for artificial intelligence. Discover Artificial Intelligence 1, 2 (2021), https://doi.org/10.1007/s44163-021-00002-4Google Scholar
- [10] IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. 2019. Ethically aligned design.Google Scholar
- [11] Müge Karabağ. 2021. A theoretical overview of artificial intelligence ethics within the context of coding moral values. TRT Akademi 6, 13 (2021), 748-767, https://doi.org/10.37679/trta.954641Google Scholar
- [12] Korea’s Ministry of Commerce, Industry and Energy. 2012. South Korean robot ethics charter.Google Scholar
- [13] Utku Kose, Ibrahim Adra Cankaya, and Tuncay Yigit. 2018. Ethics and safety in the future of artificial intelligence: remarkable issues. International journal of engineering science and application 2, 2 (2018), 65-70.Google Scholar
- [14] Eduardo Magrani. 2019. New perspectives on ethics and the laws of artificial intelligence. Internet Policy Review 8, 3 (2019), 1-19, http://dx.doi.org/10.14763/2019.3.1420Google ScholarCross Ref
- [15] Eduardo Magrani, Priscilla Silva, and Rafael Viola. 2019. New perspectives on ethics and responsibility of artificial intelligence. In (Eds.) Caitlin Mulholland, and Ana Frazao. Artificial intelligence and law: ethics, regulation and responsibility. Thomson Reuters, Revista dos Tribunais, São Paulo, 117.Google Scholar
- [16] John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude E. Shannon. 1959. Artificial intelligence. Research Laboratory of Electronics Progress Report 53.Google Scholar
- [17] Zorica Mijartovic, and Orhan Jašić. 2021. Ethics for ”intelligent” beings created by man: scenarios of the future. Epistēmēs Metron Logos 6, 6 (2021), 22–29, https://doi.org/10.12681/eml.27743Google Scholar
- [18] Ellen Pearlman. 2021. Building a ‘Sicko’ AI: AIBO: An emotionally intelligent artificial intelligent GPT-2 AI Brainwave Opera. In ACM International Conference on Interactive Media Experiences (IMX ‘21), New York, NY, USA, 205–207, https://doi.org/10.1145/3452918.3467814Google ScholarDigital Library
- [19] (Eds.) Stuart Russel, and Peter Norvig. 2003. Artificial intelligence: a modern approach. Prentice Hall, Haboken, NJ, USA.Google Scholar
- [20] Jan Strelau. 1997. Human intelligence. ŻAK, Warsaw, Poland.Google Scholar
- [21] Robert Szeligowski. 2018. Cognifying the OODA Loop: Improved Maritime Decision Making. Gravely Naval Research Group, Naval War College.Google Scholar
- [22] Grzegorz Szulczewski. 2019. Artificial intelligence and moral intelligence. An introduction to cybernetic ethics. Annales. Etyka W Życiu Gospodarczym 22, 3 (2019), 19–31, https://doi.org/10.18778/1899-2226.22.3.02Google Scholar
- [23] Hui Yie Teh, Andreas W. Kempa-Liehr, and Kevin I-Kai Wang. 2020. Sensor data quality: a systematic review. Journal of Big Data 7, 11 (2020), https://doi.org/10.1186/s40537-020-0285-1Google ScholarCross Ref
- [24] United Nations Commission on International Trade Law. 2005. United Nations Convention on the Use of Electronic Communications in International Contracts. 23 November. Vienna, Austria.Google Scholar
- [25] Gianmarco Veruggio. 2006. The EURON Roboethics Roadmap. In 6th IEEE-RAS International Conference on Humanoid Robots, 612-617, https://doi.org/10.1109/ICHR.2006.321337Google Scholar
- [26] Aku Olavi Visala. 2018. On the theology of artificial intelligence. Teologinen Aikakauskirja 123, 5 (2018), 402-417.Google Scholar
- [27] Damian Węgrzyn. 2021. Towards improving the decision-making process of artificial intelligence devices in situations of moral dilemmas. In (Eds.) Jorge P. Borondo, Mario A. Oliva, Kiyoshi Murata, and Ana M. L. Palma. Moving technology ethics at the forefront of society, organisations and governments. Universidad de La Rioja, Spain, 168-179.Google Scholar
- [28] Alan Winfield. 2017. ELS issues in robotics and steps to consider them. Part 3: ethics.Google Scholar
- [29] World Commission on the Ethics of Scientific Knowledge and Technology. 2017. Report of COMEST on robotics ethics. 14 September. Paris, France.Google Scholar
Index Terms
- The adaptation of the OODA loop to the decision-making systems processing Big Data in the area of morality
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