Multiple Events

  • Wed, Jan 29, 2020
    Ethics at Noon
    Josée Johnston & Shyon Baumann, What is “Good” Food? How Foodies Negotiate Status and Ethics in Food Choices (Ethics@Noon)

    What Is “Good” Food? How Foodies Negotiate Status and Ethics in Food Choices

    How do foodies decide what is “good” food — food worthy of eating, discussing, researching and photographing? This talk will draw from research on foodies to discuss the ways that foods become venerated as high status choices. Our research charts the rise of an omnivorous food culture that values high-class cuisine alongside street-stand tacos and diner meals. Besides identifying key markers of foodie status, we will discuss how food choices relate to ethical consumption deals like democratic openness, multiculturalism, and sustainability. Drawing from a survey with Toronto-based food shoppers, we explore the intersection of foodie culture and ethical consumption. This data suggests the emergence of a high-status foodie who appreciates the finest, most delicious foods, while also seeking to feel ethically virtuous at the dining table.

    ☛ please register here

    Shyon BaumannShyon Baumann
    University of Toronto
    Sociology 

     

     

    Josée JohnstonJosée Johnston
    University of Toronto
    Sociology

    12:30 PM - 02:00 PM
    Centre for Ethics, University of Toronto
    200 Larkin

  • Wed, Jan 29, 2020
    Ethics of AI in Context: Emerging Scholars
    Vinyas Harish & Nuwan Perera, Machine Learning for Health at the Public-Private Boundary: Questions to Consider (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.

    ☛ please register here

    Vinyas HarishVinyas Harish
    University of Toronto
    Medicine and Public Health

     

     

    Nuwan PereraNuwan Perera
    Software Engineer
    integrate.ai

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