Looking at Explainable AI (XAI)

How can we increase ethical design practices in the field of AI? Kigumi Group's Shubhi Upadhyay offers insight into one method, Explainable AI (XAI), and some specific technical ways to practice XAI, in our Medium publication.

The emerging field of XAI is focused on explaining how AI algorithms arrive at solutions, which is valuable because it can increase transparency (and thus, trust) in these algorithms.

In this manner, XAI can prove useful and applicable in various fields. For example, in the criminal justice system, using an XAI model to determine the risk of recidivism can enable stakeholders to look at which specific factors informed the model’s decision and the ethicality of these models. In the field of healthcare, an XAI model could help doctors understand how the model decides whether to diagnose a patient with a disease. With this knowledge, developers can alter machine learning models to address the areas where bias seeps in rather than scrapping the implementation of AI altogether.

Read the full article here.