Generative AI fundamentally shifts the dynamic between human and machine. It is not just about making machines easier to use anymore; it is about making them creative partners. Think about AI-generated content in art, writing, software development—AI is learning how to adapt and respond to human needs on the fly, creating new opportunities for HCI researchers to explore intuitive interfaces, creative problem-solving, and personalized interactions.
Our Noteworthy works:
- The Great AI Witch Hunt: Reviewers Perception and (Mis) Conception of Generative AI in Research Writing (Journal of Computers in Human Behavior: Artificial Humans)
In this research, we advocate for updated reviewer guidelines to ensure impartial assessments of AI-assisted manuscripts, focusing solely on research quality rather than preconceived biases toward AI tools. Importantly, we emphasize that researchers must retain full authorship and control over their work, using AI as an aid rather than a replacement for the intellectual rigor central to academic writing.
- ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions (Journal of Computers in Human Behavior: Artificial Humans)
This research advocates for AI development that prioritizes human needs, ensuring these tools enhance rather than compromise educational quality. Through an analysis of social media conversations, we found that users frequently discuss generative AI in terms of productivity, efficiency, and ethics. While many view GPTs as a valuable tools for enhancing learning, concerns have been raised about its potential to foster superficial learning and weaken students' critical thinking and social skills.
- Augmenting the Author: Exploring the Potential of AI Collaboration in Academic Writing (ACM CHI 2024, Workshop Paper)
This work critically examines the integration of generative AI in academic writing, focusing on its role as a collaborative tool. We compare the performance of two AI models, Gemini and ChatGPT, through a collaborative inquiry process where researchers designed prompts to generate research outlines. Our study underscores the significance of prompt design in shaping output quality and highlights the distinct strengths and limitations of each model.
Our vision for future:
In our team, we are not just experimenting with AI—we are fundamentally reshaping the theory and practice of how humans and machines collaborate. AI’s role is not to replace human creativity; it is to enhance it.
Our next steps focus on building AI tools, developing theoretical frameworks, and advancing models that adapt intelligently, whether in education, research, UX, or gaming. We are crafting theories that guide AI’s responsible integration, ensuring it strengthens critical thinking and deepens engagement, while designing practical systems that improve real-world outcomes.