This is a repository copy of Toward an understanding of responsible artificial intelligence practices. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/162719/ Version: Published Version Proceedings Paper: Wang, Y. orcid.org/0000-0003-1575-0245, Xiong, M. and Olya, H. orcid.org/0000-0002-0360-0744 (2020) Toward an understanding of responsible artificial intelligence practices. In: Bui, T.X., (ed.) Proceedings of the 53rd Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences (HICSS 2020), 20202-01-07 - 2020-01-10, Maui, Hawaii, USA. Hawaii International Conference on System Sciences (HICSS) , pp. 4962-4971. ISBN 9780998133133 10.24251/hicss.2020.610 © 2020 The Authors. Article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license https://creativecommons.org/licenses/by-nc-nd/4.0/. Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can’t change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020 Toward an Understanding of Responsible Artificial Intelligence Practices Yichuan Wang Mengran Xiong Hossein G. T. Olya University of Sheffield University of Sheffield University of Sheffield [email protected] [email protected] [email protected] Abstract efficiency and effectiveness by using data generated from an explosion of digital touchpoints [5], [6]. At Artificial Intelligence (AI) is influencing all the same time, it comes with its own concerns aspects of human and business activities nowadays. relating to privacy concerns, user distrust, data Although potential benefits emerged from AI leakages, information transparency, and ethical technologies have been widely discussed in many concerns. Such ethical dilemma and concerns, if they current literature, there is an urgently need to are not well addressed when developing AI understand how AI can be designed to operate initiatives, would lead to the potential loss of responsibly and act in a manner meeting credibility for products and brands and hamper the stakeholders’ expectations and applicable company reputation in the marketplaces. Ethical and regulations. We seek to fill the gap by exploring the societal concerns aroused from AI systems need to be practices of responsible AI and identifying the addressed in priority to ensure effective, ethical, and potential benefits when implementing responsible AI responsible use of AI [7]. However, relatively little practices. In this study, 10 responsible AI cases were attention has been given to understand responsible selected from different industries to better understand approaches to the development, implementation, the use of responsible AI in practices. Four management, and governance of AI. responsible AI practices are identified, including Indeed, corporate social responsibility (CSR) has governance, ethically design solutions, risk control become the main preoccupations of organizations in and training and education and five strategies for the global marketplaces [8], used in broad domains firms who are considering to adopt responsible AI including areas of policies, programs and actions practices are recommended. while interacting with stakeholders [9][10]. For instance, customer retention rate could be enhanced 1. Introduction as consumers prefer to purchase from and engage in, Artificial Intelligence (AI), a set of algorithm- socially responsible companies [8]. Likewise, based machine, is programmed to self-learn from company reputation could be built along with CSR data and display predictions and intelligent behaviors activities [11]. From the CSR perspective, through artificial neural networks, automated organizations need to embrace the goal of being machine learning, robotic process automation, and socially responsible while bringing AI into the text mining [1]. AI is capable of responding to real- business mainstream. However, according to the world problems and arriving decisions in real-time or Cognizant’s report, only about 50% of surveyed 975 near real-time manner on behalf of human being [2], executives across industries in U.S. and Europe had [3], [4]. For instance, Chatbots, an AI-enabled service policies and procedures in place to address ethical robot, developed by Bookings.com provides real-time concerns while designing AI applications [12]. 24/7 customer service with the support of 43 Although potential benefits emerged from AI languages to answer travel related queries to its technologies have been widely discussed in many customers. With such highly evolved language current literatures, the sustainable outcomes from processing capabilities, Chatbots can interact with business to the society that AI presents is remained customers and provide them with personalized unexplored [6]. Specifically, there is an urgently need recommendations. It also enables Booking.com to to understand how AI solutions can be designed to deliver marketing automation thereby simplify operate responsibly and act in a manner meeting routine works accordingly. stakeholder expectations and applicable regulations AI, as a major shift in the global economy, is [7], [13], [14]. influencing all aspects of human and business We seek to fill the gap by exploring the practices activities nowadays. It holds the promise to create of responsible AI and identifying the potential URI: https://hdl.handle.net/10125/64352 978-0-9981331-3-3 Page 4962 (CC BY-NC-ND 4.0) benefits when implementing responsible AI As digital has become a megatrend in the global initiatives. Therefore, this study set out to answer the economy, new technology gains great popularity following research questions. among different industries, offering new possibilities and bringing benefits in many aspects of human lives RQ1: What are the practices of responsible AI? [22]. For example, labor force may be replaced by the intelligent machines [23]. However, concept of the RQ2: What benefits and challenges have been sustainability has changed as it is confronted with the brought by implementing responsible AI practices? digital transformation, also known as a technological leap [24], leading to the increase in the restraints, To answer the above research questions, we hope from the national laws and international rules, on to provide business practitioners a more current companies’ responsibilities towards society and comprehensive understanding of responsible AI and environment (Bernal-Conesa et al., 2017). Thus, both theoretical and practical reference values for the challenges could be posted to organizations for use of AI in a more socially responsible way. In this creating sustainability and responsibility in the long paper, we begin by providing the historical context of run. Inability to communicate the CSR programmers technology use of CSR, and then move on to and integrate them into strategies may lead to the understanding ethical challenges in AI and the failure from achieving full potentials. Moreover, development of AI in responsible practices. We criticisms of CSR vary between companies and conducted a multiple case study of responsible AI, industries [20]. Data, algorithms and bots are main which leads to the identification of responsible AI areas to be explored during the process of sustainable practices and the recommendation of responsible AI digitalization [22]. Specifically, although having strategies. access to consumer data helps predict their potential moves and create personalized experiences for them, 2. Literature Review privacy invasions and algorithmic bias derived from 2.1. Technology Use in CSR the sophisticated use of consumer data cannot be underestimated [25]. Hence, the performance of Corporate social responsibility (CSR) can be technologies is required to be aligned with CSR defined as commitments from organizations to the principle and enhance its implementations [26]. In society in improving societal, environmental and practice, technology could identify the integration economic well-being through different business points of CSR initiatives, offering corporate strategy practices [8], [15]. The relationship between the to increase the overall integrated level. In addition, it company’s social responsibilities and its financial could reduce human bias through the multi- performance has been documented extensively in the dimensional measurement on the programme literature [16], [17]. The study from Bernal Conesa et performance. Therefore, it is arguable that technical al. [18] has indicated that the contribution of CSR- resources can be integrated with human resources, oriented strategies is significant to the overall within or across companies, helping develop performance of the organizations. From the empirical capabilities to address sustainable concerns and perspectives, this principle has been incorporated in delivering responsible values to stakeholders