A/Prof Lisa Williams (UNSW)

Driving EDI with data: How data-driven approaches can advance equity in the STEM sector

Abstract

Advancing equity, diversity, and inclusion is a moral and operational imperative in today’s society, especially in the STEM sector. Establishing what to do to shift the dial in this space, and evaluating if it’s working, is essential yet often overlooked. This talk will cover several projects that leverage data to design, garner support for, and advance initiatives for equity, diversity, and inclusion at the university, sector, and national levels. These projects include data-driven design and evaluation of initiatives within the UNSW Faculty of Science, including the UNSW Women in Maths and Science Champions Program. Other examples include those conducted in A/Prof Williams’ capacity as Chief Investigator on the grants that fund Australia’s Women in STEM Ambassador initiative: (1) an analysis of 20 years of ARC and NHMRC grant outcomes data by gender of the lead investigator, (2) a trial of anonymising peer review for grant applications for access to scientific equipment, and (3) a series of systematic reviews on the efficacy of workplace initiatives to support gender equity, disability inclusion, and inclusion of sexual and gender minority populations. How such approaches can be effectively leveraged to advise on policy and practice at governmental and organisational levels will be discussed.

Bio

Associate Professor Lisa A. Williams is a social psychologist whose research explores the mechanisms of social and emotional wellbeing. Her current research projects address emotional experience in the context of close relationships, prosocial behaviour, and blood donation. She is an advocate for gender equity—particularly in STEM—and currently serves as Associate Dean Equity Diversity and Inclusion in the UNSW Faculty of Science. She is Chief Investigator on the grants that fund the Australian Government’s Women in STEM Ambassador initiative. To her advocacy for equity she brings her knowledge of the science of stereotypes, discrimination, and prejudice and is a staunch supporter of deploying best-practice initiatives using an empirically-backed approach.