Recent attempts to develop and apply digital ethics principles to address the challenges of the digital transformation leave organisations with an operationalisation gap. To successfully implement such guidance, they must find ways to translate high-level ethics frameworks into practical methods and tools that match their specific workflows and needs. Here, we describe the development of a standardised risk assessment tool, the Principle-at-Risk Analysis (PaRA), as a means to close this operationalisation gap for a key level of the ethics infrastructure at (...) many organisations – the work of an interdisciplinary ethics panel. The PaRA tool serves to guide and harmonise the work of the Digital Ethics Advisory Panel at the multinational science and technology company Merck KGaA in alignment with the principles outlined in the company’s Code of Digital Ethics. We examine how such a tool can be used as part of a multifaceted approach to operationalise high-level principles at an organisational level and provide general requirements for its implementation. We showcase its application in an example case dealing with the comprehensibility of consent forms in a data-sharing context at Syntropy, a collaborative technology platform for clinical research. (shrink)

The rapid and dynamic nature of digital transformation challenges companies that wish to develop and deploy novel digital technologies. Like other actors faced with this transformation, companies need to find robust ways to ethically guide their innovations and business decisions. Digital ethics has recently featured in a plethora of both practical corporate guidelines and compilations of high-level principles, but there remains a gap concerning the development of sound ethical guidance in specific business contexts. As a multinational science and technology company (...) faced with a broad range of digital ventures and associated ethical challenges, Merck KGaA has laid the foundations for bridging this gap by developing a Code of Digital Ethics (CoDE) tailored for this context. Following a comprehensive analysis of existing digital ethics guidelines, we used a reconstructive social research approach to identify 20 relevant principles and derive a code designed as a multi-purpose tool. Versatility was prioritised by defining non-prescriptive guidelines that are open to different perspectives and thus well-suited for operationalisation for varied business purposes. We also chose a clear nested structure that highlights the relationships between five core and fifteen subsidiary principles as well as the different levels of reference—data and algorithmic systems—to which they apply. The CoDE will serve Merck KGaA and its new Digital Ethics Advisory Panel to guide ethical reflection, evaluation and decision-making across the full spectrum of digital developments encountered and undertaken by the company whilst also offering an opportunity to increase transparency for external partners, and thus trust. (shrink)

Responsibility has become a central concept in AI ethics; however, little research has been conducted into practitioners’ personal understandings of responsibility in the context of AI, including how responsibility should be defined and who is responsible when something goes wrong. In this article, we present findings from a 2020–2021 data set of interviews with AI practitioners and tech workers at a single multinational technology company and interpret them through the lens of feminist political thought. We reimagine responsibility in the context (...) of AI development and deployment as the product of work cultures that enable tech workers to be responsive and answerable for their products over the long and short term. From our interviews, we identify three key pain points in understanding the distribution of responsibility between actors and developing responsible design and deployment practices: (1) unstable business ecosystems and AI lifecycles, which require an approach to responsibility that accounts for the dynamic nature of these systems; (2) the issue of incentivizing engineers to take responsibility for the mundane maintenance practices essential to the functioning of AI systems and (3) the need to overcome individual and structural barriers to taking ownership over AI products and their effects. From these findings, we make three recommendations based on feminist theory: (1) organisations should move from a static model of responsibility to a dynamic and ethically motivated response-ability; (2) companies need to revalue care and maintenance practices; and (3) firms must move away from individualistic ideas of responsibility towards fostering wider cultures of responsibility. (shrink)

By mid-2019 there were more than 80 AI ethics guides available in the public domain. Despite this, 2020 saw numerous news stories break related to ethically questionable uses of AI. In part, this is because AI ethics theory remains highly abstract, and of limited practical applicability to those actually responsible for designing algorithms and AI systems. Our previous research sought to start closing this gap between the ‘what’ and the ‘how’ of AI ethics through the creation of a searchable typology (...) of tools and methods designed to translate between the five most common AI ethics principles and implementable design practices. Whilst a useful starting point, that research rested on the assumption that _all_ AI practitioners are aware of the ethical implications of AI, understand their importance, and are actively seeking to respond to them. In reality, it is unclear whether this is the case. It is this limitation that we seek to overcome here by conducting a mixed-methods qualitative analysis to answer the following four questions: what do AI practitioners understand about the need to translate ethical principles into practice? What motivates AI practitioners to embed ethical principles into design practices? What barriers do AI practitioners face when attempting to translate ethical principles into practice? And finally, what assistance do AI practitioners want and need when translating ethical principles into practice? (shrink)