The award-winning Compliance into the Weeds is the only weekly podcast that takes a deep dive into a compliance-related topic, literally going into the weeds to more fully explore a subject. Looking for some hard-hitting insights on sanctions compliance? Look no further than Compliance into the Weeds! In this episode, Tom and Matt take a deep dive into the recent FTC enforcement action involving Rite-Aid and its inappropriate use of AI-generated facial recognition.

The adoption of AI technologies, as See more +

The award-winning Compliance into the Weeds is the only weekly podcast that takes a deep dive into a compliance-related topic, literally going into the weeds to more fully explore a subject. Looking for some hard-hitting insights on sanctions compliance? Look no further than Compliance into the Weeds! In this episode, Tom and Matt take a deep dive into the recent FTC enforcement action involving Rite-Aid and its inappropriate use of AI-generated facial recognition.

The adoption of AI technologies, as demonstrated by the Rite Aid case, underscores the critical need for robust compliance oversight. This case, involving the use of AI-driven facial recognition technology, resulted in compliance risks and a high rate of false positives, highlighting the potential pitfalls of AI technologies when not properly managed. Tom emphasized the importance of a comprehensive process to assess, manage, and monitor the risks associated with new technologies. He believes that collaboration among different stakeholders is key to understanding and mitigating potential risks. Matt stressed the need for careful consideration of how new technologies will impact business processes and the importance of correct governance from both a technical and human perspective. Join Tom Fox and Matt Kelly in this episode of the Compliance into the Weeds podcast as they delve deeper into the importance of robust governance in adopting AI technologies.

Key Highlights:

• The Impact of AI Facial Recognition Technology

• Concerns of AI Facial Recognition and Racial Profiling

• Issues with AI Facial Recognition Training

• Collaborative Risk Management for AI Implementation See less -