I had the privilege of attending a webinar delivered by Dr. Chris Dede on “Lifelong Learning in the Age of GenAI”, organized by the Office of Digital Learning and Online Education at Qatar University. In this session, Dr. Dede offered a transformative perspective on the evolving relationship between humans and intelligent technologies. His central argument—that the future of work will be defined not by artificial intelligence replacing human capabilities, but by intelligence augmentation, where humans and machines collaborate to enhance performance—challenged conventional assumptions about the role of technology in education and society. This framing positions AI not merely as a tool for efficiency, but as a catalyst for rethinking how humans learn, decide, and act.

One of the most compelling insights from the webinar was Dr. Dede’s distinction between “doing things better” and “doing better things.” AI-driven automation primarily serves the former: it increases speed, accuracy, and efficiency in routine tasks. Automation refines existing processes, enabling us to perform what we already do—only faster, with fewer errors, and at greater scale. While this is undeniably valuable, it remains incremental improvement. In contrast, doing the right things requires distinctly human capacities such as ethical judgment, contextual understanding, applied wisdom, and the ability to frame problems rather than simply solve them. Dr. Dede emphasized that these qualities remain uniquely human and will become even more essential in an AI-rich world.

This distinction mirrors the deeper contrast between automation and augmentation. Automation delegates tasks to machines; augmentation, however, elevates human capability by enabling deeper insight, more sophisticated decision-making, and richer forms of learning. Through augmentation, AI does not replace human thinking—it expands the space in which thinking occurs. Dr. Dede argued that this paradigm shift necessitates new educational models that cultivate advanced cognitive and metacognitive skills, preparing learners to work with AI as a partner rather than a substitute.

The discussion of how AI can “engineer” learning was particularly illuminating. Machine learning has the potential to redesign performance-based simulations that immerse learners in realistic decision environments, requiring them to navigate complexity, ambiguity, and ethical trade-offs. Such experiences foster applied wisdom, which Dr. Dede described as a cornerstone of future leadership. In addition, AI-enabled diagnostic and formative assessments provide continuous feedback that supports ongoing skill development rather than episodic evaluation. These innovations illustrate the true potential of augmentation: AI becomes a mentor, guide, and reflective partner in the learning process.

Reflecting on the webinar, I realized that the true promise of AI in education lies not in making learning more efficient, but in making learners more capable—more capable of exercising judgment, discernment, creativity, and responsible action. The challenge for universities is to design learning environments that embody this distinction. We must resist the temptation to use AI simply to optimize existing practices; instead, we should leverage its power to reimagine what learning can become and what humanity needs to thrive amid rapidly evolving technologies and societal expectations.

Ultimately, Dr. Dede’s message is a call to shift our mindset from efficiency to purpose. AI can indeed help us do things better, but, more importantly, it can help us identify, and pursue, what the better things are.