A few quick thoughts on this.
The world we live in is becoming more and more data-driven. This is causing companies to make more and more use of AI techniques such as machine learning and deep learning. It seems to be the only “efficient” way to get control over the data and generate value for the company relatively quickly. Of course, future competitiveness also plays a significant role.
The task of the Chief AI Ethics Officer (CAIEO) should not be technical. Instead, it should sensitize data scientists, machine learning engineers, and developers to ethical issues. The whole process of sensitization should be part of every data-driven project. By this, I mean that the ethical workflow should be firmly integrated into the respective process models and phases.
In the following graphic, I have tried to show how a responsible machine learning workflow (including the ethical workflow) could look like.
It is primarily about understanding ethical risks and training managers & employees on how to do the same.
Chief AI-Ethics Officer: The job of the future
Discussions about AI Ethics are still mostly conducted in academic circles. But one can already see that many companies are seriously dealing with it. One thing that seems clear to me: Graduates of philosophy and ethics will be in high demand in the future to investigate AI-related processes through a human lens.