Skip to content
  1. Programs

The HACLab

HAC Lab logo

CHIBE-affiliated faculty member Dr. Ravi Parikh leads the Human Algorithm Collaboration Laboratory (HACLab), which implements and scales artificial intelligence (AI) and machine learning. The Lab’s mission is to train, validate, implement, and evaluate interventions based on AI, machine learning, and predictive algorithms to improve patient health and reduce health inequities. The team works with clinicians, data scientists, behavioral economists, human factors scientists, biostatisticians, and policymakers to answer key questions in patient care through targeted clinical trials and observational studies.

The HACLab designs practical AI and machine learning models that respond to discrete needs from clinicians, patients, and end-users. That involves sitting down with end-users to get a sense of what should and should not go into an algorithm, how should algorithm outputs be presented, and how sensitive or specific would the end-user want the algorithm to be. Then, they partner with organizations to implement these models in practice.

The team also runs trials that investigate how AI can augment clinicians and patients, rather than replacing them. They have a robust program producing policy-focused work on how AI should be regulated, reimbursed, and subject to liability. None of these models are fully baked, which means that the team has a chance to frequently interact with government and industry to shape the next generation of AI policy in health care.

Learn more about the HAC Lab

Interested in collaborating with the Human Algorithm Collaboration Lab on AI, machine learning, or predictive analytics? Get in touch to learn more about how we can work together.