To achieve human-AI hybrid intelligence systems, we need AI models that interact fluidly with us, understand our interests dynamically, and change accordingly. Current progress with Open AI GPT for Omni model is a step in the right direction, yet current AI systems still lack the ability to update their models based on real-time interaction data. Rather than pushing their predictions to us, human-AI hybrid intelligence systems would require interactions where AI encourages us to reach our own conclusions by enabling us with relevant information for the task at hand. I hope to see more of these in our community in the future.
Although we have significant technical progress in AI in recent years, real-world pedagogical adoption by practitioners and impact of AI in education are dependent on many other factors including technical infrastructure, school governance, pedagogical culture, teacher training, and assessment structures to count a few. AI solutions in education are not only closed engineering systems but part of a large socio-technical ecosystem. Therefore, based on decades of research in AI in education, I assert that AI tools alone are unlikely to democratize or revolutionize education. Change in education systems is likely to happen gradually, and it is our responsibility as key stakeholders to steer it towards an intentional, evidence-informed and human-centered direction.