Yuriel Ryan

🧑🏻⚖️🤖 AI is rapidly embedding itself into how we learn 👨‍🎓, work 👨‍💼, create 👨‍🎨, and choose🤳, but we lack a clear research framework for preserving meaningful human agency in the process. Our paper (papers.ssrn.com/sol3/papers.cf…) draws on how existing debates about #AI are often too abstract and insufficiently operational. We propose a rights-based lens grounded in everyday capacities: the Right to Learn, Work, Own, and Choose. This work is an inter-disciplinary and inter-institutional collaboration 🤝 between @AISingapore PhD Fellows, AI Accelerated Masters Program awardees (Ryan Yuriel Wang @YurielRyan @sutdsg, Nicole Heng Yim Oo @sgSMU, Hui En Pang @Pangyyyyy55 @NTUsg, Davin Choo @Harvard) our directors (Simon Chesterman @ProfChesterman, Jungpil Hahn @jungpil) and research fellows (Eric J. W. Orlowski, Hakim Norhashim), and my researchers in GLOW.AI @NUSingapore (Khoo Zi-Yu @ziyuuu____, Ruth Wan Theng Chew @ruthchewing, Rachael Hwee Ling Sim @RachaelSim2). Instead of asking only what AI systems can do, we ask what they should be designed to enable humans to continue doing well. ⭐️Our paper’s main contributions: • Reframing AI governance as a socio-technical challenge linking core technical properties (opacity, homogenisation, persuasive fluency, etc.) to lived societal impacts. • Translating high-level principles into concrete, researchable questions across learning, labour, ownership/attribution, and preference formation. • Identifying operational gaps where current AI development risks quietly eroding human agency. • Proposing a forward-looking research agenda that shifts the conversation from panic ("What should we do?") to coordinated problem-solving ("Here are the levers we can work on."). 💫As AI assistance becomes prolific and effective, the central question is no longer whether we use AI. Instead, we should look at how we design systems that amplify, rather than displace, human capacity.