We are the Women in Risk Advisory. We solve complex problems and foresee risks. We innovate and analyse. We incubate and referee. We help our clients build resilient, sustainable organisations. We imagine new possibilities, connecting trust, resilience, and security to make an impact that matters. We need more like us. We need more like you.
Meet Michelle. As a senior manager in Risk Analytics: AI and Data Science at Deloitte UK, Michelle serves as the AI (Artificial Intelligence) Ethics lead, advising clients on the risks and ethical issues posed by AI technology. She also leads the development of a suite of offerings and technical accelerators that help teams create trustworthy AI systems.
Michelle’s work exists at the intersection of risk and AI, an area that is constantly changing. She loves how this pushes her toward continuous innovation.
Michelle is a firm believer in the power of a personal brand. She attributes part of her success to the strong reputation she has built as an AI expert, both within Deloitte Risk Advisory and amongst clients. Because of Michelle’s pioneering work, organisations can better govern their AI and avoid unintended harm.
Michelle believes more women should pursue Risk Advisory and AI careers because people tend to design solutions according to what they know, making it important for teams to include individuals with a diversity of experiences. As she puts it, “diverse teams build better and more inclusive technologies.”
One of Michelle’s proudest accomplishments is a pro bono Deloitte project in which she and her team built a geospatial analytics and machine learning model. The model predicts which UK local authorities are at highest risk of bed shortages in youth homeless shelters, and it won a top five spot in the 2018 DatSci Awards for “best use of data to achieve social impact.”
At present, Michelle is taking advantage of Deloitte’s flexible work options to pursue a PhD in computer science and technology at the University of Cambridge. Her research explores ethics and machine learning systems and algorithmic fairness.
We need more like Michelle. We need more like you.