WSDG September Technical Presentation

The Software Engineer Reborn: A Vision of Human-AI Collaboration
by John Lee

Abstract:
AI can generate software faster than we can understand, evaluate, and maintain it. If implementation becomes cheaper, what might the software engineer become?

Drawing on my personal journey through neuroscience, scientific software, full-stack development, and AI-assisted product building, I will examine how AI expands what one person can create—and the accompanying risks of cognitive overload, uncontrolled scope, weakened mastery, and work that no one fully owns.

Software engineers may be well prepared for this transition, not merely because we code, but because we decompose ambiguous problems, construct feedback loops, expose failures, and turn unreliable components into dependable systems. Through a hands-on exploration of how coding has already changed, I will consider what the engineer's role might become—and the unresolved challenge of directing machine capability without surrendering human judgment, responsibility, or purpose.

Human–AI collaboration also changes how humans collaborate with one another. As individuals gain greater autonomy and organizational boundaries begin to shift, how might we preserve trust, share understanding, coordinate expertise, and build communities around work whose production is increasingly automated?

Bio:
John Lee began his career studying learning and memory in fruit flies, earning a PhD in neurophysiology from Trinity College Dublin. His path from experimental neuroscience led through neuroimaging data and research software in the NIH Intramural Research Program, open-source scientific Python and infrastructure at Quansight, and independent consulting and product development. He now works as a Research Software Engineer at Dartmouth's Center for Open Neuroscience, building/applying tools for reproducibility and provenance tracking to scientific and healthcare image data. His interests include using semantic technologies to constrain and audit AI output, and understanding how AI may transform healthcare. He recently moved to Williamsburg, Virginia.
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This hybrid meeting will be available both in-person and remotely. For those attending in person, we will be at the Williamsburg Regional Library, Conference Room B.
For online access, the Zoom info is:
https://us06web.zoom.us/j/2562166096?omn=81998225947
Meeting ID: 256 216 6096
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Upcoming schedule:

October 14, 6:00 PM - Social Event

November 18, 6:30 PM - Williamsburg Library, Conference Room C.
*** Note changed date and room ***
Glover Barker will present "Detection and Notification Case Studies"

December 9, 6:00 PM - Social Event