Co-Intelligence: Living and Working with AI

by Ethan Mollick

Only 36 job categories out of 1,016 had no overlap with AI. Those few jobs included dancers and athletes, as well as pile driver operators, roofers, and motorcycle mechanics (though I spoke to a roofer, and they were planning on using AI to help with marketing and customer service, so maybe 35 jobs). You will notice that these are highly physical jobs, ones in which the ability to move in space is critical. It highlights the fact that AI, for now at least, is disembodied.

At the level of tasks, we need to think about what AI does well and what it does badly. But we also need to consider what we do well and what tasks we need to remain human. Those we can call Just Me Tasks. They are tasks in which the AI is not useful and only gets in the way, at least for now. They might also be tasks that you strongly believe should remain human, with no AI help.

The next category of tasks is Delegated Tasks. These are tasks that you assign the AI and may carefully check (remember, the AI makes stuff up all the time), but ultimately do not want to spend a lot of time on. This is usually stuff you really don’t want to do and is of low importance, or time-consuming. The perfect Delegated Task is tedious, repetitive, or boring for humans but easy and efficient for AI.

Then there are Automated Tasks, ones you leave completely to the AI and don’t even check on.

Centaur work has a clear line between person and machine, like the clear line between the human torso and horse body of the mythical centaur. It depends on a strategic division of labor, switching between AI and human tasks, allocating responsibilities based on the strengths and capabilities of each entity.

On the other hand, Cyborgs blend machine and person, integrating the two deeply. Cyborgs don’t just delegate tasks; they intertwine their efforts with AI, moving back and forth over the Jagged Frontier. Bits of tasks get handed to the AI, such as initiating a sentence for the AI to complete, so that Cyborgs find themselves working in tandem with the AI.

First, they need to recognize that the employees who are figuring out how best to use AI might be at any level of the organization, with any sort of history or past performance record.

Second, leaders need to figure out a way to decrease the fear associated with revealing AI use. Assuming early studies are true and we see productivity improvements of 20 to 80 percent on various high-value professional tasks, I fear the natural instinct among many managers is “fire people, save money.” But it does not need to be that way. There are many reasons for companies to not turn efficiency gains into head-count reduction or cost reduction. Companies that figure out how to use their newly productive workforce should be able to dominate any company that tries to keep their post-AI output the same as their pre-AI output, just with fewer people. And companies that commit to maintaining their workforce will likely have employees as partners who are happy to teach others about the uses of AI at work, rather than scared workers who hide their AI for fear of being replaced.

Third, organizations should highly incentivize AI users to come forward, and expand the number of people using AI overall. That means not just permitting AI use but also offering substantial rewards to people finding substantial opportunities for AI to help.

When we start to take into account the systems in which jobs operate, we see other reasons to suspect slower, rather than faster, change in the nature of jobs. Humans are built deep into the fabric of every aspect of our organizations. You cannot easily replace a human with a machine without tearing that fabric.

So students will cheat with AI. But as we saw with user innovation earlier, they also will begin to integrate AI into everything they do, raising new questions for educators. Students will want to understand why they are doing assignments that seem obsolete thanks to AI. They will want to use AI as a learning companion, a coauthor, or a teammate. They will want to accomplish more than they did before, and will also want answers about what AI means for their future learning paths. Schools will need to decide how to respond to this flood of questions.

We stand on the cusp of an era when AI changes how we educate—empowering teachers and students and reshaping the learning experience—and, hopefully, achieve that two sigma improvement for all. The only question is whether we steer this shift in a way that lives up to the ideals of expanding opportunity for everyone and nurturing human potential.