Business and the Ethical Implications of Technology: Introduction to the Symposium

Abstract

While the ethics of technology is analyzed across disciplines from science and technology studies (STS), engineering, computer science, critical management studies, and law, less attention is paid to the role that firms and managers play in the design, development, and dissemination of technology across communities and within their firm. Although firms play an important role in the development of technology, and make associated value judgments around its use, it remains open how we should understand the contours of what firms owe society as the rate of technological development accelerates. We focus here on digital technologies: devices that rely on rapidly accelerating digital sensing, storage, and transmission capabilities to intervene in human processes. This symposium focuses on how firms should engage ethical choices in developing and deploying these technologies. In this introduction, we, first, identify themes the symposium articles share and discuss how the set of articles illuminate diverse facets of the intersection of technology and business ethics. Second, we use these themes to explore what business ethics offers to the study of technology and, third, what technology studies offers to the field of business ethics. Each field brings expertise that, together, improves our understanding of the ethical implications of technology. Finally we introduce each of the five papers, suggest future research directions, and interpret their implications for business ethics.

Community-in-the-loop: towards pluralistic value creation in AI, or—why AI needs business ethics

“…In fact, even if an AI system is completely ethically designed on a technical level-if this is possible at all and whatever that may mean with regard to say fairness, privacy or safety in particular [13,44,68]-major ethical questions may arise. Think, for example, of the risks of dual use or the cases in which employees from Google or Microsoft have voiced public protest against the potential use of some of their companies' products for immigration and law enforcement agencies, military purposes or foreign governments [64,69,70]. Or take the already widespread and various use of AI systems in recruiting, which raise questions about whether decisions about the future of people based on (psychological) profiling are legitimate and desirable.…”

“…Business ethics deals with the question of the possibility of ethical behaviour in a market economy which is driven by the principle of competition [92]. Despite early contributions on AI from a business ethics perspective [93] and the fact that the impact of AI on business ethics has been recognised [94,95] and conceptualised by several authors [69,88,96,97], business ethics approaches are hardly found in the current AI ethics debate [69,98], but in no case from a contractualist perspective.…”

An Exploration of Ethical Decision Making with Intelligence Augmentation

“…in order to reject the AI tool's recommendation and provide a significant amount of mandatory justification (vis-à-vis accepting the recommendation), then the design of the tool or process is likely to influence their judgement. This concept has been acknowledged in "Values in Design" (ViD), which describes the field of research that investigates how "individually and organizationally held values become translated into design features" (Martin et al 2019).…”

“…] an important part of a larger decision and influence the delegation of roles within an ethical decision". Martin et al (2019) argue that "ethical biases in technology might take the form of [ . .…”

No business as usual: a case for data ethics and data governance in the age of coronavirus

“…Information and communication technology (ICT) has been rapidly and innovatively employed by organisations to maintain "business as usual" and to counteract the negative economic impacts on their business. Most organisations have seen an increased adoption of new technologies aimed at maintaining good communication with stakeholders, new forms of machine learning and various autonomous digital systems which drive an increasing amount of decisions made in both business and government (Martin et al, 2019).…”