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Ignoring context creates a systematic bias in how we measure AI impact. The more context-free a task, the more AI can help. The more embedded a task is in specific knowledge and relationships, the more AI assistance can actually get in the way.
A lecture by Jamer Hunt, professor at the Parsons School of Design and author of Not to Scale, at the Artificiality Summit 2024.
What are the cause and effect of my actions? How do I know the effect of the small acts in my life? How can I identify opportunities to have impact that is much larger than myself? How can we make problems that seem overwhelmingly complex feel more manageable and knowable? How might we use the scaling tools of designers to tackle some of the world’s largest and most complex problems?
To answer these questions, we talked with Jamer Hunt about his book Not to Scale: How the Small Becomes Large, the Large Becomes Unthinkable, and the Unthinkable Becomes Possible. The book repositions scale as a practice-based framework for navigating soci al change in complex systems. Jamer is Professor of Transdisciplinary Design and Program Director for University Curriculum at the New School’s Parsons School for Design. Jamer was the founding director of the Transdisciplinary Design graduate program at Parsons that was created to emphasize collaborative design-led research and a systems-oriented approach to social change.
We’re big fans of Jamer’s book and have incorporated his concept of scalar framing into our work. We encourage you to check his book out as well and see how zooming in and out can help you frame complex problems in a way that makes them more addressable.
Learn more about Jamer Hunt
Learn more about Jamer’s book Not to Scale
Learn more about the Transdisciplinary Design program at Parsons
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