✍️ Original article by Abhinav Raghunathan, the creator of EAIDB who publishes content related to ethical ML / AI from both theoretical and practical perspectives. This article is a part of our Ethical AI … [Read more...] about The Ethical AI Startup Ecosystem 05: Governance, Risk, and Compliance (GRC)
Looking before we leap: Expanding ethical review processes for AI and data science research
🔬 Research Summary by Ismael Kherroubi Garcia, trained in business management, and philosophy of the social sciences. He is the founder and CEO of Kairoi, the AI Ethics and Research Governance Consultancy. … [Read more...] about Looking before we leap: Expanding ethical review processes for AI and data science research
Humans are not Boltzmann Distributions: Challenges and Opportunities for Modelling Human Feedback and Interaction in Reinforcement Learning
🔬 Research Summary by David Lindner, a doctoral student at ETH Zurich working on reinforcement learning from human feedback. [Original paper by David Lindner, Mennatallah El-Assady] Overview: Current work … [Read more...] about Humans are not Boltzmann Distributions: Challenges and Opportunities for Modelling Human Feedback and Interaction in Reinforcement Learning
Beyond Bias and Compliance: Towards Individual Agency and Plurality of Ethics in AI
🔬 Research Summary by Megan Welle Brozek and Thomas Krendl Gilbert Megan is the CEO and co-founder of daios, a deep tech AI ethics startup, and a background in the philosophy and methodology of science. Tom is a … [Read more...] about Beyond Bias and Compliance: Towards Individual Agency and Plurality of Ethics in AI
Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model based AI Systems
🔬 Research Summary by Dr Qinghua Lu, the team leader of the responsible AI science team at CSIRO's Data61. [Original paper by Qinghua Lu, Liming Zhu, Xiwei Xu, Zhenchang Xing, Jon Whittle] Overview: … [Read more...] about Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model based AI Systems