Counterfactual reasoning in AI is a method where artificial intelligence analyzes “what-if” scenarios to predict how changing one variable could affect an outcome. By exploring alternative possibilities based on historical data, it helps AI make decisions, explain predictions, detect biases, and improve transparency, personalization, and safety in applications ranging from finance to self-driving cars.
Emilie currently works in Marketing & Communications for a non-profit organization based in Toronto, Ontario. She completed her Masters of English Literature at UBC in 2021, where she focused on Indigenous and Canadian Literature. Emilie has a passion for writing and behavioural psychology and is always looking for opportunities to make knowledge more accessible.
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I was blown away with their application and translation of behavioral science into practice. They took a very complex ecosystem and created a series of interventions using an innovative mix of the latest research and creative client co-creation. I was so impressed at the final product they created, which was hugely comprehensive despite the large scope of the client being of the world's most far-reaching and best known consumer brands. I'm excited to see what we can create together in the future.
Heather McKee
BEHAVIORAL SCIENTIST
GLOBAL COFFEEHOUSE CHAIN PROJECT
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By launching a behavioral science practice at the core of the organization, we helped one of the largest insurers in North America realize $30M increase in annual revenue.
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By redesigning North America's first national digital platform for mental health, we achieved a 52% lift in monthly users and an 83% improvement on clinical assessment.
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By designing a new process and getting buy-in from the C-Suite team, we helped one of the largest smartphone manufacturers in the world reduce software design time by 75%.
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By implementing targeted nudges based on proactive interventions, we reduced drop-off rates for 450,000 clients belonging to USA's oldest debt consolidation organizations by 46%
