With any emergent technology, there are always challenges to overcome as adoption and awareness grow. Those hurdles can seem mountainous when two things happen simultaneously: millions of people start using and discussing the technology immediately and when that tech has the potential to transform our productivity levels and how we interact with our devices.
Generative AI is in this nuanced position right now. One of the seemingly immense and complex issues it faces is the idea of bias showing up in both the powerful language learning models training these tools and in the outcomes they produce. But addressing bias in AI is much more difficult than telling a tool like Jasper Chat or ChatGPT, “Don’t be biased in your generations” or “Give me objective results.”
For this series on ethics and responsible AI use, I asked experts for their opinion around the idea of bias in model training and outcomes. Where does it come from? How does it show up? How can we stop it from…