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AI that takes missions, not tasks
What a mission looks like
Hand an agent a mission and the work changes. Someone who cares about a societal problem could send it to spread awareness and work out how people should coordinate. Someone who loves a video game could ask it to combine ideas from two favorite games into a new one. Someone curious about materials science could send it to explore a different way of constructing materials, running its own experiments for months.
Time on execution
Compare that with a bulk email that refuses to unindent, where a person still fights an editor for something that takes less effort to explain than to do. That execution should be handled, leaving the person to think about what to build and what they want to see in the world that isn't there yet.
Work seen from the past
Picture an ancestor from a thousand years ago watching someone sit in a room, talk with other people, and call it a meeting. Farming and making clothes by hand were work; this looks like nothing. Work a few decades from now may look just as strange to us: people pursuing curiosities, causes, and art, sending their agents off on missions, and calling that their job.
How could an agent run experiments for months?
It would need a way to plan, act, record what it learned, and revise the plan, repeated over a very long stretch. In practice that means keeping notes and results in files, which it rereads as it goes. For lab work it would also need connections to simulations or instruments that run the experiments. Autonomous systems that propose and test hypotheses in chemistry and biology already exist in research labs.
How much of work has vanished into machines before?
In 1900, about 40 percent of the American workforce was employed in agriculture, according to US Census data. Today the share is under 2 percent. Mechanization raised farm output while it cut the labor needed, and workers moved to jobs that did not exist before. The majority of jobs people hold today have no counterpart in 1900.
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