Expert responsibility in AI development

Abstract

The purpose of this paper is to discuss the responsibility of AI experts for guiding the development of AI in a desirable direction. More specifically, the aim is to answer the following research question: To what extent are AI experts responsible in a forward-looking way for effects of AI technology that go beyond the immediate concerns of the programmer or designer? AI experts, in this paper conceptualised as experts regarding the technological aspects of AI, have knowledge and control of AI technology that non-experts do not have. Drawing on responsibility theory, theories of the policy process, and critical algorithm studies, we discuss to what extent this capacity, and the positions that these experts have to influence the AI development, make AI experts responsible in a forward-looking sense for consequences of the use of AI technology. We conclude that, as a professional collective, AI experts, to some extent, are responsible in a forward-looking sense for consequences of use of AI technology that they could foresee, but with the risk of increased influence of AI experts at the expense of other actors. It is crucial that a diversity of actors is included in democratic processes on the future development of AI, but for this to be meaningful, AI experts need to take responsibility for how the AI technology they develop affects public deliberation.

Artificial Intelligence Teaching as Part of Medical Education: Qualitative Analysis of Expert Interviews

“…The need for standardization in the definition of AI as a foundation for related teaching content is further emphasized by the potential ethical challenges and issues that may arise from the use of different types of AI in a clinical context. For example, in the context of bias, clinical decision support systems can be subject to bias arising from the unintended transfer of existing bias on the part of the developers [ 31 , 32 ]. Focusing on applications based on ML as part of statistical AI per definition, there is an imminent risk for bias originating from unrepresentative data sets used in the training process of the applications [ 33 ].…”

Epigenetics and Responsibility

“…In the context of epigenetic responsibility, the principle of position has been put forward: those who are in a position to make a difference -because they have relevant resources or because they are at the right place at the right time -have a moral obligation to do so. Position, so understood, may, but need not, overlap with capacity (Hedlund and Persson, 2022). This argument may point to a societal responsibility to mitigate adverse effects of epigenetic mechanisms .…”

“…Aspects such as the number of data points (Kwon, 2020) and the representativeness of datasets (Cirillo and Rementeria, 2022) are very important for the accuracy of data analysis, which is also important for the discussion on responsibility ascription. AI technology is a technically complicated field that is difficult to understand for those who are not themselves experts on the technology (Hedlund and Persson, 2022). In combination with epigenetics, another technically complicated field, this makes responsibility attribution even more intricate.…”

Role of Ethics in Developing AI-Based Applications in Medicine: Insights From Expert Interviews and Discussion of Implications

“…In light of these ethical principles, the role of developers in creating AI-based applications in medicine has become critically important. Developers bear a particular responsibility to ensure that the design and implementation of these technologies adhere to the ethical standards outlined by autonomy, nonmaleficence, beneficence, and justice [ 28 ]. A deep understanding and awareness of the ethical implications during the development process are essential, as the principles and guidelines frequently discussed in the current literature should be integrated from the early stages of AI application development [ 29 , 30 ].…”