The widespread availability of general-purpose AI that can perform complex cognitive tasks threatens to undermine education at scale. This effortless bypass dilemma sharpens a challenge AIED has long engaged with but must now confront directly: ensuring learners choose effortful engagement when easier alternatives are available to complete learning tasks. In this paper, I argue that AIED's longstanding agenda of building more effective intelligent educational tools should continue, but with a renewed emphasis on the urgency of ensuring learners choose to engage authentically. Drawing on established motivational and learning theories, I outline five directions in which AIED can build on its existing strengths: supporting autonomy and agency, building learner resilience to metacognitive threats, designing for interest and relevance, amplifying process-based assessment, and empowering teachers. I then share four envisioned technologies that embody key features of this future and conclude by outlining how AIED must now evolve.
Most existing EEG-based emotion recognition studies formulate affective decoding as static category prediction, although emotions elicited by continuous stimulation evolve over time, accumulate, reach peak intensity, and then recover. This motivates EEG-based dynamic affective tr…
AI-driven algorithms and automated tools are increasingly embedded in the correctional landscape, shaping parole eligibility,release decisions, and surveillance. These tools are also often framed as objective, inevitable solutions to inefficiency andbias. Yet, these computational…
Large language models (LLMs) are increasingly used for a range of software, hardware and human-centered security tasks. Consequently, LLM performance on security tasks is an active area of measurement and research, often with a focus on identifying areas in which LLM security ``k…
Claims that language models homogenise are usually measured against human judgements collected for the study, which makes the human side an artifact of the design: a crowdworker given the model's instruction is running the model's prompt. We measure convergence against a human re…
Visualization style guides play a crucial role in shaping how data is interpreted and trusted, yet they often receive little scrutiny in their creation and use. Understanding their impact requires looking beyond the specific rules that style guides prescribe and examining how the…
Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as foreign propaganda, with consequences for democratic discourse and information sovereignty. Yet, whether an AI's perceived national…