Being Responsible with Artificial Intelligence Solutions

When vendors are evaluating which artificial intelligence (AI) solutions are best for them, what should they be keeping top of mind?

Kondru: It's a great question. There's a lot of companies that are popping up in the AI space with LLMs (large language models). The factors that one needs to think about is performance and reliability. The second one is, do they have built-in guardrails to ensure data integrity and patient safety within the life sciences sector? AI has a different meaning for our participants and folks across the globe, and having this keen eye on the guardrails for data integrity and patient safety is a must. Some of the considerations that I would include when I'm looking at a vendor race, are there business goals aligned? For us, I think in the end, we serve the participants and the patients, and our hope is to impact human health, so is there a business alignment there? How is the data infrastructure? Are there any safeguards or guardrails around patient data privacy? We also want to make sure that there are ethical considerations. We talked about patient recruitment and site selection—are there inherent biases? Is there fairness, transparency, and accountability? These are some of the things that I would look at when I'm picking out a vendor in the AI space or LLM space.