Speaker
Description
The rapid development and application of artificial intelligence (AI) has radically transformed our conception of planning and what the planning profession can achieve. AI has enabled new, and in many cases more accurate, ways to make predictions, more efficient design modeling, and streamlined data gathering. When used appropriately, AI can contribute to more robust decision-making, revealing its vast potential as a tool capable of achieving outcomes that were previously unattainable or too resource-intensive to accomplish. For planning education, this presents a clear imperative: to teach students how to use AI to solve problems, emphasizing AI’s role as a tool.
However, the mission of planning educators goes beyond simply teaching students technical know-how. As John Dewey argued, education should be about helping students realize their potential—developing their capacity for situational problem-solving that aligns with their personal goals. To clarify the type of capacity we are referring to, it is helpful to invoke Aristotle’s typology from Nicomachean Ethics. Aristotle differentiated between two types of wisdom: technical wisdom (techne), which focuses on using tools to achieve a specific end, and practical wisdom (phronesis), which is about determining the right ends and choosing the appropriate tools to use in a given situation.
Teaching students how to use AI to achieve specific goals clearly falls within the realm of technical wisdom (techne). Yet, the rise of AI also provides educators with the opportunity to foster the development of students’ practical wisdom (phronesis). The development of practical wisdom—making sound judgments about what is right in a given situation—has long been advocated as something best achieved through case-based pedagogy, as demonstrated in programs like those at Harvard Business School. In this context, AI creates new possibilities for more efficient, tailored case-based simulations that can meet the specific needs of planning curricula.
A central question, however, is whether AI-generated case studies can effectively simulate real-life situations. Drawing on Herbert Simon’s pragmatist ideas on simulation, this presentation argues that even if AI-generated cases are not perfectly realistic, they can still serve valuable pedagogical purposes if properly supervised by experienced educators and tailored to meet specific learning objectives. The emphasis on AI’s capacity to generate case studies is not intended to replace teaching students how to use AI but to complement it.
To strengthen planning as a professional discipline, it is essential to provide students with both the general professional knowledge required to use AI and the practical wisdom to make informed decisions in their professional and personal lives—whether or not AI is involved. This balanced approach will ensure that future planning graduate are not only skilled in using advanced tools like AI but are also capable of exercising judgment and making wise decisions in the increasingly complex real-world situations they will face.
| Best Congress Paper Award | No |
|---|
