Event Description
Overview
UHY Advisors, Inc. (UHY), in partnership with the Detroit Chapter of the Tax Executives Institute, Inc. (TEI), is proud to sponsor this webinar on professional ethics, specifically focused on navigating cognitive dissonance and understanding the ethical impacts of artificial intelligence (AI) in professional environments. Attendees will earn 2 CPE credits in Behavioral Ethics upon attending the program.
One lucky attendee will be randomly selected to win 4 tickets and a parking pass to the Detroit Tigers game on Sunday, June 28, against the Houston Astros in Section 122, Row 8.
Program Information
Navigating Cognitive Dissonance in Internal and Client Relationships
Cognitive dissonance—mental discomfort arising from holding contradictory beliefs, values, or behaviors—appears daily in leadership decisions, team dynamics, and client interactions. When left unexamined, it fuels rationalization, weak feedback cultures, ethical blind spots, and strained relationships.
This session equips professionals to recognize cognitive dissonance in themselves and others, understand the neuroscience that drives rationalization, and apply practical strategies to navigate high-stakes internal and client conversations more effectively. Participants leave with tools to promote psychological safety, improve feedback quality, and reduce ethical and decision-making risks.
Ethics & AI: How Artificial Intelligence Intersects with Ethics in Professional Environments
As AI becomes embedded in everyday workflows such as drafting, research, analysis, and client communication, the pace of adoption is often outpacing reflection. This session explores how artificial intelligence intersects with ethical responsibility in professional services environments, with a practical—not technical—focus.
This session reinforces a central message: while AI can enhance efficiency and insight, accountability for accuracy, judgment, and impact remains firmly in human hands. Participants will examine common AI use cases alongside the ethical risks they introduce, including inaccurate or fabricated outputs, confidentiality and data privacy concerns, bias, and overreliance on automated tools.