A blindspot of AI ethics: anti-fragility in statistical prediction
It highlights a potential societal risk from AI decision-making, but is incremental as it critiques existing discourse without proposing new solutions.
The paper argues that current AI ethics discussions overlook the threat of AI systems optimized for short-term error avoidance, which may reduce societal diversity and flexibility needed for progress, framing this concern using the concept of anti-fragility.
With this paper, we aim to put an issue on the agenda of AI ethics that in our view is overlooked in the current discourse. The current discussions are dominated by topics suchas trustworthiness and bias, whereas the issue we like to focuson is counter to the debate on trustworthiness. We fear that the overuse of currently dominant AI systems that are driven by short-term objectives and optimized for avoiding error leads to a society that loses its diversity and flexibility needed for true progress. We couch our concerns in the discourse around the term anti-fragility and show with some examples what threats current methods used for decision making pose for society.