At over 200 pages, there’s a lot of content covered in the Report. For the purposes of this project, I focused on just a few paragraphs that discussed the concept of Explainable AI.
Machine learning algorithms (a type of AI) are used all over the internet, from tailored recommendations to content moderation. Recent years have seen ML algorithms used to make increasingly impactful decisions, such as
whether or not your mortgage will be approved.
"Explainable AI" seeks to create algorithms that not only output decisions, but explanations for their decisions. While it sounds great in theory, this may be a more difficult task than it seems. The Policy Primer dives into the complexities of trying to explain a machine learning algorithm, with plenty of background information for the less knowledgeable.