Leesburg, Va. – Mosaic Data Science, a leader in AI and machine learning consulting, will participate in the upcoming American Health Law Association (AHLA) conference on “The Complexities of AI in Health Care.” Scheduled for Thursday, May 16, 2024, this one-day in-person event aims to dissect the intricate relationship between AI technology and healthcare, focusing on the critical issue of algorithmic bias and fairness.
Michael Shumpert, VP of Data Science, will contribute his expertise to a panel discussion alongside our partners at Epstein Becker Green and EBG Advisors, represented by Brad M. Thompson, moderator. The talk, titled “Managing Algorithmic Bias and Fairness,” will explore the nuanced challenges and risks posed by unintentional biases in algorithms, which can lead to legal, regulatory, and reputational repercussions for businesses.
The implications of AI bias in healthcare are significant and multifaceted, affecting patients, healthcare providers, and the broader healthcare system in various ways. It can lead to misdiagnosis, inappropriate treatment recommendations, and exacerbate health disparities, particularly affecting underrepresented groups. Legal, ethical, and safety implications necessitate rigorous bias auditing, diverse data inclusion, and interdisciplinary collaboration. Addressing these biases is crucial for ensuring equitable, effective, and safe healthcare delivery.
“Our participation in the AHLA conference is a testament to its leadership in addressing the ethical challenges posed by AI and machine learning technologies,” said Shumpert. “By providing critical insights into the AI lifecycle, auditing for bias, and ensuring compliance with ethical standards, Mosaic is helping to pave the way for responsible AI development and deployment across industries like healthcare.”
Mosaic adheres to a strict algorithm bias auditing protocol in line with the AI Risk Management Framework developed by the National Institute of Standards and Technology (NIST). This approach ensures not only the accuracy of AI systems but also their fairness and transparency, addressing potential biases that can arise from various sources, including data selection, algorithm design, and the broader implications of deployment in diverse environments.
Through our partnership with Epstein Becker Green and EBG Advisors, Mosaic is at the forefront of efforts to audit and manage algorithmic bias, contributing to a broader initiative to enhance the ethical deployment of AI in healthcare and beyond. This collaboration highlights Mosaic’s commitment to blending our state-of-the-art AI capabilities with the specialized legal and risk management insights of our partners at EBG, offering customers holistic solutions to complex problems at the intersection of AI technology and healthcare.
Mosaic is shaping the regulatory future of AI in the United States through participation in the U.S. AI Safety Institute Consortium (AISIC). We bring our extensive expertise in data science to support the development of standards and methods aimed at managing the risks associated with AI utilization. In addition to its AISIC participation, Mosaic Data Science continues to offer algorithmic bias auditing and risk management engagements. Mosaic recommends Explainable AI services and MLOps for any production deployment.
