If you have gone through our training, you would know that modern AI tools are built using Large Language Models. The name Large Language relates to the fact that these models are mathematically driven models that have been fed lots of language. They have been trained on videos, on audio, on books—let’s just say, a lot of language.
As a side note, did you know that there are approximately 600,000 words in the English language?
In all the languages that the models have been trained on, there is an inherent bias depending on the knowledge and the content that the Large Language Model was trained on. Large Language Models are therefore prone to sometimes suggest solutions or create content that may not be in line with societal expectations.
To an extent, the inherent randomness in what the models and tools create can be influenced by the user and the questions they ask.
The good news is that, like with any other software, when building Assistive Intelligence tools, we can create controls both during the development process and once the tools are in production. This ensures that bias is something we are aware of and can manage effectively. We don’t want to understate the importance of bias and its management; it introduces one of the biggest risks when Assistive Intelligence is exposed to your customers in public. But you can be assured that there are ways to manage it, and that many organizations are already using AI tools with this risk at hand, and managing it well.
If you haven’t already, come to our training. We highly encourage you and your executives to join us and learn about the main risks, how to manage them, and most importantly, see the opportunity ahead.
