Responsible AI in Life Sciences: Frameworks, Applications and Considerations

Go back to programme

Responsible AI in Life Sciences: Frameworks, Applications and Considerations

  • Watch

    * Register (or log in) to the AI4G Neural Network to add this session to your agenda or watch the replay

  • Healthcare data continues to be produced at an incredible rate. In the life sciences sector, data produced in clinical trials and in the “real world” (patient care outside of a clinical trial and in the broader healthcare environment) are creating massive volumes of information on an individual patient and their response to novel treatments in development today.  

    With the advancements in data science and generative AI within the last year, we find ourselves at an inflection point: while this data liquidity could very well be the foundation and training ground necessary to develop more precise therapeutics and significantly reduce lengthy clinical trials, it also presents a high stakes challenge for the healthcare data industry.  How do we ensure that models developed by AI to diagnose or treat patients are fair, ethical, transparent and accountable? What does it mean to be a health data steward, re-purposer or provider and what are the guardrails for the utilization of data?   

    This AI for Good talk will lay out the major challenges and opportunities in drug development, an overview of the health data ecosystem, what the promise of AI holds in tackling these problems and provide some frameworks and perspectives for how the industry should consider governance in a rapidly evolving space. 

    This live event includes a 30-minute networking event hosted on the AI for Good Neural Network. This is your opportunity to ask questions, interact with the panelists and participants and build connections with the AI for Good community.

    Share this session

    Are you sure you want to remove this speaker?