Vinyas Harish & Nuwan Perera, Machine Learning for Health at the Public-Private Boundary: Questions to Consider (Ethics of AI in Context: Emerging Scholars)

Ethics of AI in Context: Emerging Scholars

Machine Learning for Health at the Public-Private Boundary: Questions to Consider

Recent advances in artificial intelligence (AI) have spurred much interest and investment in the ‘disruption’ of healthcare.  Major breakthroughs in numerous areas of machine learning (ML) are leading to the creation of ‘decision support systems’ which promise to aid physicians throughout the trajectory of a patient’s care. Numerous major technology companies (e.g. Microsoft, Apple, Google) have identified healthcare as an untapped opportunity and key vertical for their business. As seen with recent headlines in the media (e.g. Google’s Project Nightingale), we propose that ML for health at the public-private boundary brings forward unique ethical considerations not seen with other technologies.  There is limited academic literature to inform decision-making by non-technical stakeholders and a lack of clarity around the practical discussion around what should be done when considering a [public-private?] partnership in this space. We provide a series of questions to guide the framework around making responsible decisions when partnering with private sector to design and deploy AI/ML solutions for health.

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Vinyas HarishVinyas Harish
University of Toronto
Medicine and Public Health

 

 

Nuwan PereraNuwan Perera
Software Engineer
integrate.ai

Wed, Jan 29, 2020
04:00 PM - 05:30 PM
Centre for Ethics, University of Toronto
200 Larkin