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The Ethics of AI Ethics an Evaluation of Guidelines

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The Ethics of AI Ethics an Evaluation of Guidelines The Ethics of AI Ethics An Evaluation of Guidelines Dr. Thilo Hagendorff University of Tuebingen International Center for Ethics in the Sciences and Humanities [email protected] Abstract - Current advances in research, development AI ethics – or ethics in general – lacks mechanisms to and application of artificial intelligence (AI) systems reinforce its own normative claims. Of course, the have yielded a far-reaching discourse on AI ethics. In enforcement of ethical principles may involve consequence, a number of ethics guidelines have been reputational losses in the case of misconduct, or released in recent years. These guidelines comprise restrictions on memberships in certain professional normative principles and recommendations aimed to bodies. Yet altogether, these mechanisms are rather harness the “disruptive” potentials of new AI weak and pose no eminent threat. Researchers, technologies. Designed as a comprehensive evaluation, politicians, consultants, managers and activists have to this paper analyzes and compares these guidelines deal with this essential weakness of ethics. However, it highlighting overlaps but also omissions. As a result, I is also a reason why ethics is so appealing to many AI give a detailed overview of the field of AI ethics. Finally, companies and institutions. When companies or I also examine to what extent the respective ethical research institutes formulate their own ethical principles and values are implemented in the practice guidelines, regularly incorporate ethical of research, development and application of AI systems considerations into their public relations work, or – and how the effectiveness in the demands of AI ethics adopt ethically motivated “self-commitments”, efforts can be improved. to create a truly binding legal framework are continuously discouraged. Ethics guidelines of the AI Keywords - artificial intelligence, machine learning, industry serve to suggest to legislators that internal ethics, guidelines, implementation self-governance in science and industry is sufficient, and that no specific laws are necessary to mitigate possible technological risks and to eliminate scenarios 1 Introduction of abuse (Calo 2017). And even when more concrete laws concerning AI systems are demanded, as recently The current AI boom is accompanied by constant calls done by Google (Google 2019), these demands remain for applied ethics, which are meant to harness the relatively vague and superficial. “disruptive” potentials of new AI technologies. As a result, a whole body of ethical guidelines has been Science- or industry-led ethics guidelines, as well as developed in recent years collecting principles, which other concepts of self-governance, may serve to technology developers should adhere to as far as pretend that accountability can be devolved from state possible. However, the critical question arises: Do authorities and democratic institutions upon the those ethical guidelines have an actual impact on respective sectors of science or industry. Moreover, human decision-making in the field of AI and machine ethics can also simply serve the purpose of calming learning? The short answer is: No, most often not. This critical voices from the public, while simultaneously paper analyzes 21 of the major AI ethics guidelines and the criticized practices are maintained within the issues recommendations on how to overcome the organization. The association “Partnership on AI” relative ineffectiveness of these guidelines. (2018) which brings together companies such as 1 Amazon, Apple, Baidu, Facebook, Google, IBM and Intel and development of AI systems. In particular, I is exemplary in this context. Companies can highlight critically examine to what extent the principles have an their membership in such associations whenever the effect. In a third and final step, I will work out ideas on notion of serious commitment to legal regulation of how AI ethics can be transformed from a merely business activities needs to be stifled. discursive phenomenon into concrete directions for action. This prompts the question as to what extent ethical objectives are actually implemented and embedded in 2 Guidelines in AI ethics the development and application of AI, or whether merely good intentions are deployed. So far, some 2.1 Method papers have been published on the subject of teaching Research in the field of AI ethics ranges from ethics to data scientists (Garzcarek and Steuer 2019; reflections on how ethical principles can be Burton et al. 2017; Goldsmith and Burton 2017) but by implemented in decision routines of autonomous and large very little to nothing has been written about machines (Anderson, M. and Anderson, S. Leigh 2015; the tangible implementation of ethical goals and Etzioni, A. and Etzioni, O. 2017; Yu, H. et al. 2018) over values. In this paper, I address this question from a meta-studies about AI ethics (Vakkuri and theoretical perspective. In a first step, 21 of the major Abrahamsson 2018; Prates, Avelar, and Lamb, Luis, C. guidelines of AI ethics will be analyzed and compared. 2018; Boddington 2017; Greene, Hoffman, and Stark I will also describe which issues they omit to mention. 2019; Goldsmith and Burton 2017) or the empirical In a second step, I compare the principles formulated analysis on how trolley problems are solved (Awad et in the guidelines with the concrete practice of research al. 2018) to reflections on specific problems (Eckersley The European Commission's High-Level Expert Group Group Expert High-Level Commission's European The Human Well-being with Autonomous and Intelligent and Intelligent Autonomous with HumanWell-being and Intelligent Autonomous with HumanWell-being Montréal Declaration for Responsible Development Declaration Responsible Development Montréal for OECD Recommendation of the Council Artificialon of the OECDRecommendation Principles for Accountable Algorithms and aAccountable Principlesfor SocialAlgorithms Ethically Prioritizing Vision A for Design: Aligned Ethically Prioritizing Vision A for Design: Aligned Report on the Future of Artificial Intelligence Future the on Report The Malicious The of Artificial IntelligenceUse EverydayEthics Artificial for Intelligence Systems (Version for Public for Discussion) (Version Systems DeepMind Ethics DeepMind & PrinciplesSociety Impact Statement for Algorithms for ImpactStatement ArtificialGoogle at Intelligence The AsilomarAI The Principles on Artificialon Intelligence ofArtificial Intelligence Systems (First Edition) (First Systems MicrosoftAI principles ITIAI Policy Principles AI Now 2016 Report 2016 AINow Report 2017 AINow Report 2018 AINow number of mentions of number BeijingAI Principles Partnership on AI on Partnership OpenAI Charter OpenAI Intelligence AI4People (The IEEE (The IEEE (Organisatio Global Global (Beijing n for Initiative on Initiative on (Information Academy of Economic Co- (Future of Ethics of Ethics of Technology (Microsoft (Pekka et al. (Holdren et (Brundage et (Floridi et (Crawford et (Campolo et (Whittaker (Diakopoulo (Abrassart (OpenAI (Google (Cutler et al. (Partnership authors Artificial operation Life Institute Autonomus Autonomus Industry Corporation (DeepMind) 2018) al. 2016) al. 2018) al. 2018) al. 2016) al. 2017) et al. 2018) s et al.) et al. 2018) 2018) 2018) 2018) on AI 2018) Intelligence and 2017) and and Council 2019) 2019) Developmen Intelligent Intelligent 2017) t 2019) Systems Systems 2016) 2019) meta- principles of code of several detailed detailed several several IBM’s short analysis brief short list of an analysis of large statements statements statements ethics short description description short short list of about principles of guideline keywords association AI principles AI principles AI prinicples AI principles abuse collection of on social on social on social released by principles of ethical of ethical principles principles keywords key issue principles the FAT ML about basic for the between of the EU of the US of China of the OECD scenarios of different implications implications implications the for the aspects in aspects in for the for the for the for the community ethical ethical use several AI principles of AI of AI of AI Université ethical use the context the context ethical use ethical use ethical use beneficial principles of AI industry de Montréal of AI of AI of AI of AI of AI of AI use of AI leaders privacy protection x x x x x x x x x x x x x x x x x 17 accountability x x x x x x x x x x x x x x x x x 17 fairness, non-discrimination, justice x x x x x x x x x x x x x x x x x 17 transparency, openness x x x x x x x x x x x x x x x 15 safety, cybersecurity x x x x x x x x x x x x x x x 15 common good, sustainability, well-being x x x x x x x x x x x x x x x 15 human oversight, control, auditing x x x x x x x x x x x x 12 explainability, interpretabiliy x x x x x x x x x x 10 solidarity, inclusion, social cohesion x x x x x x x x x x 10 science-policy link x x x x x x x x x x 10 legislative framework, legal status of AI systems x x x x x x x x x 9 responsible/intensified research funding x x x x x x x x 8 public awareness, education about AI and its risks x x x x x x x x 8 future of employment x x x x x x x x 8 dual-use problem, military, AI arms race x x x x x x x 7 field-specific deliberations (health, military, mobility etc.) x x x x x x x 7 human autonomy x x x x x x x 7 diversity in the field of AI x x x x x x 6 certification for AI products x x x x 4 cultural differences in the ethically aligned design of AI x x 2 systems protection
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