Who we are

https://www.linkedin.com/in/milestidmarsh/

Miles is a data scientist and economist who applies statistical techniques to improve the value-alignment of artificial intelligence. 

Miles been active in the Effective Altruism field for 10 years. Aside from co-founding Compassion in Machine Learning (CaML), Miles has also co-founded Modeling Cooperation, which researches AI competition dynamics; the Centre for AI Responsibility and Education (CAIRE), an AI safety education startup; and helped organize Effective Altruism’s EAGxAustralia 2023 conference. Miles’ presentations and papers include ‘Making AIs Actually Care About Animals’, Sentient Futures (2025) and ‘Modelling Cooperation’ (2021).

Miles has a Masters in Economics from the University of Melbourne, Australia, and was accepted into the PhD program. Since then, he has further developed his AI and MML skills, completing ‘Practical Deep Learning for Coders’ at FastAI and ‘Machine Learning’ by Stanford University’s Andrew Ng. Previously Miles was a research economist in the Productivity Commission which provides independent advice to the Australian Government on economic, social and environmental issues.

Miles is skilled in statistics, leadership, research and in forming collaborative relationships and teams across disciplines, organisations and countries. 

https://www.linkedin.com/in/joyeechen/    

Joyee graduated UC Berkeley with a BS in EECS. Under Berkeley’s Supervised Program for Alignment Research (SPAR), he assembled literature for scaffolding for the feasibility of automated alignment researchers with Dr. Bogdan-Ionut Cirstea, and honed his simulation and experimental skills studying cumulative risk metrics for causal generative world models. His strengths are not only in his detail orientedness but in asking the “so what?” to every part of a hard question to distill its important parts. In the style of Hamming’s “You and Your Research”, he takes an iterative approach with diverse tools and approaches, and seeing what sticks, in problem-solving and the alignment cause.

https://www.linkedin.com/in/jasmine-brazilek-70b0a4149/ 

Jasmine has over 6 years of experience in the technology industry, focusing on cybersecurity and data science. At Anthropic, she designed security systems for unique use cases, bridging gaps in existing tools. 

Highly productive and detail-oriented, Jasmine has also been involved in effective altruism for 7 years, primarily focusing on earning to give. She completed the ‘Practical Deep Learning for Coders’ course from FastAI and has gained significant skills in ML, primarily during in her time at CAML. She has now trained dozens of models, generated dozens of datasets of thousands of rows and learnt iteratively through experience and reading papers.