6 Matching Annotations
  1. Last 7 days
    1. An AI model taught to view racist language as normal is obviously bad. The researchers, though, point out a couple of more subtle problems. One is that shifts in language play an important role in social change; the MeToo and Black Lives Matter movements, for example, have tried to establish a new anti-sexist and anti-racist vocabulary. An AI model trained on vast swaths of the internet won’t be attuned to the nuances of this vocabulary and won’t produce or interpret language in line with these new cultural norms. It will also fail to capture the language and the norms of countries and peoples that have less access to the internet and thus a smaller linguistic footprint online. The result is that AI-generated language will be homogenized, reflecting the practices of the richest countries and communities.

      [21] AI Nuances

  2. Apr 2023
  3. Dec 2022
    1. Many HRMS providers point to AI approaches for processing unstructured data as the bestcurrently available approach to dealing with validation. Currently these approaches suffer frominsufficient accuracy. Improving them requires development of large and high-quality referencedatasets to better train the models.

      Historical labor data will be full of bias. AI approaches must correct for bias in training sets, lest we build very sophisticated and intelligent systems that excel at perpetuating the bias they were taught.

  4. Mar 2021
  5. Jan 2021