JMP Securities Conference - Evaluating Data Science Companies

In this panel discussion at the JMP Securities Conference on Artificial Intelligence, Dr. Michael Housman, Chief Science Officer and Co-Founder of RapportBoost.AI, examines how organizations should evaluate the value and usefulness of data science sources when building effective AI-driven solutions.

Housman argues that not all data is equally valuable, and that the success of any data science initiative depends less on the volume of data and more on its relevance, quality, and connection to real-world outcomes. He cautions against the common tendency to treat data as inherently valuable without first understanding what decisions it can meaningfully inform.

Drawing on his experience in applied machine learning, he outlines key criteria for assessing data sources, including how closely they map to the behavior being studied, whether they can support causal insight rather than just correlation, and how reliably they can be integrated into existing workflows.

The discussion reinforces a central principle of Housman’s approach to AI: better solutions come from better questions. By starting with clear business objectives and working backward to identify the most informative data, organizations can avoid wasted effort and focus their analytics on generating actionable, human-centered insights.