AI Incident Database Spotlights Worst Machine Translation Fails

In the ongoing popular (albeit shallow) debate pitting human translators against machine translation (MT), one constant is the question of quality -- how to define it, how to measure it, and how to improve it. Now, a new website, the AI Incident Database (AIID), aims to quantify the risks presented, and actual harm caused, by AI. Sean McGregor, ML architect at Syntiant and developer of the AIID, described the "collective memory of [AI systems'] failings" in a November 2020 paper. As McGregor explained, the AIID is a project of the Partnership on AI (PAI), an organization funded by tech companies and governed by a board comprising corporate partners and non-profits. The AIID is modeled on incident databases in other industries, namely aviation and cybersecurity, which promote transparency.