Sam Deverett
I focus on helping clarify our understanding of the risks and opportunities from AI.
As a Research Engineer at the UK AI Safety Institute, I evaluate the capabilities of advanced AI systems. The goal is to equip policymakers, industry leaders, and the wider research community with an empirical understanding of the risks from AI so that we can develop it responsibly and regulate it appropriately.
I am also interested in the use of AI for promoting democracy. I believe language models have potential to scale deliberation and enable more representative, transparent, and accountable processes for collective decision-making. Projects in this vein include democratizing the governance of AI as well as automatically mapping the opinion landscape on a given topic.
Links to my relevant pages are in the icons above and below. I’m always happy to connect.
timeline
| 2024 | - | Technical Staff, Research Engineer @ UK AI Safety Institute Evaluating the capabilities of frontier AI systems. | |
|---|---|---|---|
| 2024 | - | 2024 | Research Fellow @ AI Futures Fellowship Prototyped LLMs’ potential to scale deliberative democracy, with a focus on finding the best questions to ask people in order to surface points of consensus or cruxes of disagreements. I was supervision by Jonathan Stray and collaborated with the AI Objectives Institute. |
| 2023 | - | 2023 | Researcher @ MIT, Fraenkel Lab Built an LLM for metabolomics research using retrieval-augmented generation. |
| 2023 | - | 2023 | Researcher @ AI Safety Hub Produced workshop paper on defining and preventing collusion in multi-agent reinforcement learning settings. I served as the team lead, and we were supervised by Lewis Hammond. |
| 2022 | - | 2023 | Data Science Engineer @ DraftKings A “Data Science Engineer” is a Data Scientist + Machine Learning Engineer. I worked on the Risk & Fraud team. The job was full-stack: formulating business cases, creating data pipelines, developing machine learning models, deploying them to production, setting up monitors, and responding to errors. The two projects I worked most on were quantifying the skill of a bettor and catching identity fraud during a registration attempt. |
| 2021 | - | 2022 | Product Analyst, Data Science @ DraftKings I worked as an analyst for the data science team. This invovled tasks like designing KPIs, running experiments to quantify the impact of new models, conducting deep dives to understand customers’ behavior, building dashboards, and presenting insights to stakeholders from around the business. |
| 2017 | - | 2020 | Student @ UC Berkeley Bachelor’s in Data Science Regents’ and Chancellor’s Scholar Certificate in Entrepreneurship & Technology |