After developing an innovative algorithm for his doctorate that predicts the personality of web users, Golnoosh Farnadi quickly found success: Many companies wanted to use his algorithm in their hiring process. Alarmed, she decided on the spot that her career would take a different turn.
Posted at 2:00 p.m
Simon Lord Special Collaboration
“My PhD aimed to develop a model to predict the personality of internet users based on the traces they leave behind: the texts they write, the photos they post,” explains Golnoosh Farnadi, assistant professor at HEC Montréal.
But over time, various companies have reached out to her and expressed interest in using these models to help them recruit.
“I was interested in the theoretical aspect, but when I realized what we can do with these models in terms of recruitment, I got scared,” laughs the 37-year-old researcher.
Here his career plans changed.
Focus on the risk
Prior to his PhD, Golnoosh Farnadi wrote an additional dissertation chapter. In it, she explained why such a model that she is developing should not be used as part of a hiring process – the opposite of what a graduate student would reflexively do.
“This is worrying because this type of tool is rarely 100% reliable,” she says. These models make mistakes, and those mistakes could result in one person being chosen over another. So I decided to change my research direction. »
During her postdoc, she therefore decided to focus more on the risks of artificial intelligence (AI). An area of research she continues to explore today as she focuses on issues of discrimination and bias in AI models.
Better health equity
Golnoosh Farnadi, Principal Fellow of Mila, the Quebec Institute of Artificial Intelligence, and holder of a Canada-CIFAR AI Chair, is currently working on a project related to kidney transplants.
She explains that there are software programs around the world that use AI to match patients with kidney donors. However, this software is not yet perfect because not all patients – although they are also medically compatible – have the same probability of being selected by the algorithm.
“We’re trying to come up with a different model, a different approach that guarantees all potential patients the same chance of a kidney,” explains the researcher, who admits that the rapid advance of knowledge in her field is a constant challenge.
“The models advance so fast, think ChatGPT, that we always lag behind: the algorithms are launched, and only after that we, the researchers, try to make them fair and equitable. It would be better to do it beforehand, but there are few regulations about it. »
strong support
Golnoosh Farnadi was founded in Montreal five years ago and grew up in Iran. There she developed her interest in everything to do with computers and technology at a young age.
Computers have always fascinated me. As a kid I loved playing with the Commodore 128 my dad brought home.
Golnoosh Farnadi, Assistant Professor at HEC Montreal
After completing a research trip that took her from Tehran to Belgium via the Netherlands, she now believes she has found a springboard for her research here in Montreal.
“I love Canada and Canada has treated me very well,” she says. My research chair is tremendously supportive, Mila is amazing and I’m surrounded by people who believe in our research. I take pride in working with people with whom I share beliefs. »