Artificial Intelligence: Ethical Challenges For Research

AI research faces ethical challenges, requiring careful consideration of principles like respect, good consequences, justice, and integrity.

Recent and ongoing developments in artificial intelligence cause worries and uncertainty. At the moment, large language models (LLMs) get the most attention, as they are widely distributed and able to do what is traditionally considered intellectual work.

This raises important questions about responsibilities, training and awareness, both when it comes to those developing the technology and when it comes to those utilising it – be they researchers, research institutions, research funders, national or multi-national fora, or private individuals. In this situation, there is an obvious need for renewed research ethics reflection.

Research ethics broadly construed is about ensuring the ethical quality of research processes and products through constructive reflection and good practices. Ethically relevant is not only what happens in a given project between the researchers, or between researchers and research participants, but also possible or likely societal and environmental impacts.

New questions, established principles

Research ethics understood in this way is principle-based. That is to say, research ethics is not about the application of some esoteric normative theory, or limited to purely juridical issues; it is concerned with asking about the values we deem central, and hopefully finding wise and practicable answers.

When it comes to the relations between researchers and the rest of the world, core values can be articulated in terms of three basic principles: respect for persons, good consequences, and justice. (The ‘rest of the world’ includes anything from research participants to ecosystems, depending on the case at hand.) When it comes to relations among researchers, integrity is such a basic principle.

AI has not created a situation where we need new principles. The established principles remain the crucial ones. But we do need to think through the changing situations anew, in order to figure out how to respond well to a rapidly changing landscape.[…]

AI research faces ethical challenges, requiring careful consideration of principles like respect, good consequences, justice, and integrity.

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