Mona Khalil

Mona Khalil is a Senior Data Scientist at Greenhouse, where she works on enhancing talent management software using data science and machine learning (ML). She emphasizes that their approach to ML differs from others in the field by focusing on augmenting human decision-making rather than automating it. The company has developed benchmark departments, recommendation engines, and Bayesian features to provide intelligent information about hiring processes without making decisions about people. Greenhouse is closely monitoring legislation related to ML and automated systems in the hiring process, such as a bill in the New York City Council that requires reporting on their use. They are also working on improving data quality within their system and exploring the possibility of creating more intelligent datasets to mitigate bias. Khalil led an effort to establish a Data Ethics and Product Committee at Greenhouse, which includes members from various departments such as product, security, sales, customer success, and marketing. The committee has developed guidelines for risky candidate outcomes, information sharing, and privacy protection. They have also educated teams on how to handle customer inquiries about AI features and shared their perspective through blog posts and conference talks. Khalil believes that creating more effective curated training sets could help generate predictions that make better decisions than people, by focusing on desired outcomes for different subgroups within a population. She sees opportunities to leverage the domain expertise of social sciences in data collection methods. Greenhouse is excited about expanding their resources and conducting research to publish their own findings as an external resource.