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abstract

Towards a code of ethics for autonomous and self-adaptive systems

Published:18 September 2020Publication History

ABSTRACT

Software systems are playing an increasingly important role in many domains of our society. To ensure that software will support the public good, software engineers, who create and maintain the software, shall adhere to ethical principles. A joint task force of IEEE and ACM has brought such a set of principles together in a Code of Ethics. These principles describe responsibilities for software engineers and guidelines to assist them when making decisions in the benefit of public good. With the emergence of computing systems that take autonomous decisions, there is growing consensus that new ethical principles will be required. Since self-adaptive systems are characterized by autonomy, the need for new principles applies to these systems. Based on the Code of Ethics and leveraging on ongoing initiatives, we suggest an initial set of new ethical principles for autonomous and self-adaptive systems as an inspiration for an extended Code of Ethics for this important class of systems.

References

  1. J. Andersson et al. 2009. Modelling Dimensions of Self-adaptive Software Systems. In Software Engineering for Self-Adaptive Systems. LNCS, Vol. 5525. Springer.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. A. Bennaceur et al. 2016. Feed Me, Feed Me: An Exemplar for Engineering Adaptive Software. In Software Engineering for Adaptive and Self-Managing Systems.Google ScholarGoogle Scholar
  3. R. Calinescu et al. 2018. Engineering Trustworthy Self-Adaptive Software with Dynamic Assurance Cases. Transactions on Software Engineering 44, 11 (2018).Google ScholarGoogle ScholarCross RefCross Ref
  4. World Economic Forum. 1/2020. https://www.weforum.org/whitepapers/how-to-prevent-discriminatory-outcomes-in-machine-learning/Google ScholarGoogle Scholar
  5. D. Gotterbarn et al. 2001. Software Engineering Code of Ethics and Professional Practice. Science and Engineering Ethics 7 (2001).Google ScholarGoogle Scholar
  6. J. Kephart and D. Chess. 2003. The Vision of Autonomic Computing. Computer 36, 1 (2003).Google ScholarGoogle Scholar
  7. J. Leikas et al. 2019. Ethical Framework for Designing Autonomous Intelligent Systems. Journal of Open Innovation: Technology, Market, & Complexity 5, 1 (2019).Google ScholarGoogle ScholarCross RefCross Ref
  8. IEEE/ACM Joint Task Force on Software Engineering Ethics and Professional Practices. 1/2020. Code of Ethics. www.computer.org/education/code-of-ethicsGoogle ScholarGoogle Scholar
  9. D. Weyns. 2019. Software Engineering of Self-adaptive Systems. In Handbook of Software Engineering. Springer, 399--443.Google ScholarGoogle Scholar
  10. D. Weyns and U. Iftikhar. 2019. ActivFORMS: A Model-Based Approach to Engineer Self-Adaptive Systems. arXiv:cs.SE/1908.11179Google ScholarGoogle Scholar

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            cover image ACM Conferences
            SEAMS '20: Proceedings of the IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
            June 2020
            211 pages
            ISBN:9781450379625
            DOI:10.1145/3387939

            Copyright © 2020 Owner/Author

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 18 September 2020

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