HCI Seminar: Qianou (Christina) Ma, "Future-Proof Developers: Optimizing and Training for Human-AI Collaboration in Programming."

Title: Future-Proof Developers: Optimizing and Training for Human-AI Collaboration in Programming Abstract: Large language models (LLMs) are redefining what it means to program and broadening who can develop software apps or analyze complicated data, from CS experts to non-programmers, without writing much code.

However, there is a gap between this vision and reality: people benefit unequally from LLMs, and AI’s impact depends not only on algorithmic power but on how humans collaborate with it. How can we enable everyone, even the non-experts, to program productively with AI and solve complex tasks?

What skills should we teach humans to effectively program with AI, and how should we best prepare humans for the AI era? Qianou (Christina) Ma from CMU will share her work that explores these questions for the future of programming with AI.

Bio: Qianou (Christina) Ma is a PhD student at Carnegie Mellon University Human-Computer Interaction Institute, specializing in Human-AI interaction, GenAI, and Learning Sciences, and co-advised by Sherry Wu and Ken Koedinger.

She focuses on designing, building, and evaluating LLM applications to help humans adapt and thrive in AI-infused development environments and optimize human‑AI collaboration. For example, she develops AI-based interactive learning that significantly improves end users' skills to write prompt programs. Her work has been published across top research venues such as AIED, CHI, and ACL, and has been recognized by industry and media such as The New York Times.

Her research has earned distinctions such as Best Paper at AIED and has been supported by NSF, Gates Foundation, and Google Academic Research Award.