A blindspot of AI ethics: anti-fragility in statistical prediction
Artificial Intelligence
2020-06-25 v1
Abstract
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.
Keywords
Cite
@article{arxiv.2006.11814,
title = {A blindspot of AI ethics: anti-fragility in statistical prediction},
author = {Michele Loi and Lonneke van der Plas},
journal= {arXiv preprint arXiv:2006.11814},
year = {2020}
}
Comments
7th Swiss Conference on Data Science (accepted as Poster)