Artificial intelligence is becoming increasingly prevalent in scientific research – from automating simple tasks, through to handling experimental data, ideation and generating novel hypotheses. It is, therefore, of great importance that users pause to consider the ethical implications of implementing these technologies.
The ethics of using AI should not be treated as peripheral to research, industry-based and commercial applications, but as central, keystone components of shaping how AI is developed, used and understood in scientific environments. For example, in the fields of biology, medicine and the life sciences, the use of AI in experiments involves handling sensitive human data, biological samples and potential clinical outcomes, raising important moral questions that must be addressed, responsibly.
This resource will build on what we are calling the ethical research pyramid (below), the summit of which is only achieved by building solid foundations to support it. As we move through this course, we will aim to explain the importance of each segment of the pyramid.