A blindspot of AI ethics: anti-fragility in statistical prediction

by   Michele Loi, et al.
Universität Zürich
University of Malta

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.


page 1

page 2

page 3


Online anti-Semitism across platforms

We created a fine-grained AI system for the detection of anti-Semitism. ...

Trustworthy AI

The promise of AI is huge. AI systems have already achieved good enough ...

The societal and ethical relevance of computational creativity

In this paper, we provide a philosophical account of the value of creati...

Combating Anti-Blackness in the AI Community

In response to a national and international awakening on the issues of a...

AI Design, Design AI, Human-Centred AI and the Theatre of the Absurd the language, life and times of a UX designer

This article connects the concepts and phenomena of Design AI, AI in cre...

Why we need an AI-resilient society

Artificial intelligence is considered as a key technology. It has a huge...

No Keyword is an Island: In search of covert associations

This paper describes how corpus-assisted discourse analysis based on key...

Please sign up or login with your details

Forgot password? Click here to reset