Our Focus
Advances in AI will inevitably transform how healthcare is delivered and experienced worldwide. Dr. Laura Sikstrom and Dr. Marta Maslej combine their expertise in computational, experimental, and ethnographic methods to study impacts of AI development and implementation in mental health. Their team’s past and ongoing projects have focused on topics in one or more of the following areas: Data, Prediction, and Care.
Data
We examine the social and technical processes that shape how data are collected and transformed into meaningful insights. Although data science focuses on “cleaning” or validating data after collection, far less attention has been paid to what kinds of data are collected, and how data is collected, interpreted, and instrumentalized by clinicians and patients in everyday encounters. We also delve into the social and political factors that bias data and AI models, with the aim of mitigation and preventing discriminatory harms.
Prediction
AI has potential to support mental health care via prediction of symptoms, behaviours, and outcomes. We explore this potential by training AI models on heterogenous datasets, to advance our understanding of mental health and support assessment, prognostication, and treatment personalization. Rather than focusing on optimizing model performance, we prioritize developments that center patient and provider values, promote equity in outcomes, and aim to meaningfully impact the health of individuals and communities.
Care
We explore the intersection of care and technology, striving to uncover how AI impacts the experience, quality, and delivery of mental health care. Our team considers human factors of AI implementation, or how patients and providers will team up with AI systems. We additionally prioritize the development of tools that are optimized for the care settings in which they are meant to be embedded, recognizing that successful human-AI teaming will require changes to workflows, care pathways, training, and education.
