Rebekah Tweed is the Executive Director of All Tech Is Human and a leader in Responsible Technology. Rebekah was named one of the 100 Brilliant Women in AI Ethics in 2023 and frequently speaks on responsible AI, generative AI, AI policy, and responsible technology careers, talent, and hiring trends. She is the guest editor of Springer AI and Ethics Journal topical collection on the social impacts of AI on youth and children and is the Co-Chair of the IEEE Global AI Ethics Initiative Editing Committee and a member of the Arts Committee.

Previously, Rebekah worked as the Assistant Producer of A BETTER TECH, 2021 Public Interest Technology (PIT) Convention & Career Fair, hosted by New York University and funded by New America's PIT-University Network. Prior to that, Rebekah worked as the Project Manager for NYC law firm Eisenberg & Baum, LLP's AI Fairness and Data Privacy Practice Group, where she examined technology's impact on society, organizing and promoting virtual events to build public awareness around algorithmic discrimination and data privacy issues in New York City and beyond.

Dr. Savannah Thais is an Associate Research Scientist and adjunct professor in the Data Science Institute where she focuses on the intersection of machine learning (ML), artificial intelligence (AI), science, and society with the goal of learning how to build more trustworthy models. She is interested in complex system modeling and in understanding what types of information is measurable or modelable and what impacts designing and performing measurements have on systems and societies. This work is informed by her background in high energy particle physics and incorporates traditional scientific experiment design components and scientific methodologies. At Columbia, she designed and teaches a new course on AI Ethics, and leads the interdisciplinary Science, Society, and AI Lab.

Dr. Thais is the founder and Research Director of Community Insight and Impact, an non-profit organization focused on data-driven community needs assessments for vulnerable populations and effective resource allocation. She is passionate about the impacts of science and technology on society and is a strong advocate for improving access to scientific education and literacy, community centered technology development, and equitable data practices. She was the ML Knowledge Convener for the CMS Experiment from 2020-2022, currently serves on the Executive Board of Women in Machine Learning and the Executive Committee of the APS Group on Data Science, and is a Founding Editor of the Springer AI Ethics journal. She is also heavily involved in mutual aid groups and local politics in Brooklyn.

Teresa is a researcher at Arthur interested in transparency and social impact of algorithmic systems from a human-centered lens. She is interested in use-case evaluations of tools for AI transparency and context-based mechanisms for accountability. Previously, she worked on XAI and HCI projects while completing her M.S. in Data Science at Harvard University. She was also a recent recipient of the "Young AI Role Model of the Year" award by Women in AI.

Tanya is an experienced reporter, editor and editorial manager with a decade of tech and business coverage under her belt.

She currently leads tech coverage for LinkedIn News, reaching LinkedIn's 1 billion+ members with relevant and timely news, analysis, insights, and trends focusing on AI, enterprise tech and big tech.

Before this, she was the founding reporter on Business Insider's advertising and media team, where she wrote regular news and feature stories, and led and built flagship editorial products like the 'Most Innovative Chief Marketing Officers' and the 'CMOs to Watch' lists.