Generative Glitter is a weekly newsletter focused on how to use generative AI to work better—from theory to techniques.
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Reorganizing work around technology
Louis Hyman, a labor and technology historian, writes in the New York Times that
productivity gains of the industrial age didn’t happen just because someone invented a new technology; they happened because people also figured out how best to reorganize work around that technology.
He argues for everyday automation—a personal assembly line with benefits for workers and organizations—as a tool to improve productivity. For workers, generative AI could provide freedom from mundane tasks, which could open up space to do more creative and human work (and hello, 30 hour work week).
Some evidence
Earlier this year, researchers at MIT found that ChatGPT shortened basic writing tasks, decreased productivity inequality, and increased job satisfaction in an experiment with 444 marketers, grant writers, consultants, data analysts, human resource professionals, and managers.
Take my job
My dad emailed me and asked “could I ask ChatGPT to access GIS data and prepare a map?” Kind of. GPT is a language model, so it doesn’t directly access and prepare, but it could:
Speed up the search by suggesting places to go look for GIS data.
Figure out the analysis by outlining the steps to import the data into a GIS (or even writing the code).
Refine the map production by recommending best practices for map layout and design.
As a personal assembly-line worker, you would still be shepherding each of these tasks to the next, but the technology could make it faster and more efficient.
For something more autonomous, you could wire the output up to workflow automation tools like Zapier to complete specific tasks based on responses. That might require some coding today. But with so many people hacking on a concept called Auto-GPT I think we’ll see more of this in the future.