# Classification Schemas for Artificial Intelligence Failures

## TL;DR

This paper analyzes historical AI failures, proposes a classification scheme to categorize future failures, and aims to improve responses and reduce failures through systematic risk assessments.

## Contribution

It introduces a novel classification scheme for AI failures to enhance response strategies and guide risk assessments in development processes.

## Key findings

- A systematic classification aids in response planning.
- Targeted risk assessments can reduce AI failures.
- Historical failure analysis informs future prevention strategies.

## Abstract

In this paper we examine historical failures of artificial intelligence (AI) and propose a classification scheme for categorizing future failures. By doing so we hope that (a) the responses to future failures can be improved through applying a systematic classification that can be used to simplify the choice of response and (b) future failures can be reduced through augmenting development lifecycles with targeted risk assessments.

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Source: https://tomesphere.com/paper/1907.07771