Citation
2026. Graeff, E. “AI’s Humility Problem: Threats to the Practice of Design.” Presented at the 2026 Forum on Philosophy, Engineering, and Technology (fPET 2026), University of Maryland, College Park, MD, Jun 11.
Presentation Slides
Abstract
This paper will examine the relationship between artificial intelligence and humility, arguing that humility—especially epistemic humility—is a crucial civic virtue that contemporary AI systems place at risk. Generative AI technologies allow us to use knowledge that is beyond us without helping us appreciate the boundaries of our understanding. While AI could help reveal our limitations in ways that augment humility, more common uses threaten to erode humility, the social practices that sustain it, and our civil society that relies on it.
I am approaching this concern through exploratory engagement with multidisciplinary scholarship on humility, ethics, computing, and AI, alongside reflection on my formative experiences in computing and my current work in engineering education. Drawing on my graduate education within the innovation culture of the MIT Media Lab, I will consider, from this situated vantage point, how many computing environments have rewarded anti-humble performances of speed, certainty, and mastery. Generative AI intensifies these tendencies by giving users the illusion that they need not be limited by their own experiences and education—that one can access collective knowledge on demand, even though this is far from the totality of human knowledge. I will use these experiences to ask how everyday encounters with AI may reshape dispositions toward doubt, listening, and deference to others.
A guiding premise is that humility is not merely a private moral trait but a foundation for democratic and collaborative life via openness to plural forms of knowledge and deliberative capacity. Humility ensures that we value the creation of new knowledge, that we are awed when others do things we cannot or did not think to do, and that we embrace curiosity and deep listening. Awareness of our limitations enables us to be more open and tolerant, to collaborate with people from different backgrounds, and to become well-rounded humans. If generative AI obscures our lack of knowledge and ability, I fear we will diminish a key part of our humanity and civic capacity.
I am exploring these questions through a review of literature on intellectual humility, AI and engineering ethics, engineering and computer science education, and critical approaches to human-computer interaction, with strong influence from Shannon Vallor’s account of “technomoral humility” and her arguments in The AI Mirror. Rather than claiming a settled literature, the paper will map concerns about how AI mediates experiences of competence and ignorance. It will also consider the responsibility of developers and educators to account for what happens when humility is undermined and these effects operate at scale.
Ultimately, I contend that AI strengthens the need to cultivate technomoral humility. Particular attention will be given to implications for undergraduate engineering and computer science programs. We need engineers and technologists who see humility as a virtue in their work. The paper will argue for an AI ethics more centrally concerned with humility and for pedagogical directions that normalize admitting uncertainty, foreground the social origins of knowledge, reward engagement with unfamiliar perspectives, and connect humility to civic-mindedness and democracy.
