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We are going to need to reconstruct meaning, in art and in the rituals of creative work. This is not an easy process, but we have done it before, many times. Where musicians once made money from records, they now depend on being excellent live performers. When photography made realistic oil paintings obsolete, artists started pushing the bounds of photography as art. When the spreadsheet made adding data by hand unneeded, clerks shifted their responsibilities to bigger-picture issues.
almost all of our jobs will overlap with the capabilities of AI.
the job with the highest overlap is actually telemarketer. Robocalls are going to be a lot more convincing, and a lot less robotic, soon.
Getting rid of some tasks doesn’t mean the job disappears. In the same way, power tools didn’t eliminate carpenters but made them more efficient, and spreadsheets let accountants work faster but did not eliminate accountants.
AI has the potential to automate mundane tasks, freeing us for work that requires uniquely human traits such as creativity and critical thinking—or, possibly, managing and curating the AI’s creative output,
When the AI is very good, humans have no reason to work hard and pay attention. They let the AI take over instead of using it as a tool, which can hurt human learning, skill development, and productivity. He called this “falling asleep at the wheel.”
we need to be conscious about the tasks we are giving AI, so as to take advantage of its strengths and our weaknesses. We want to be more efficient while doing less boring work, and to remain the human in the loop while also addressing the value of AI.
AI is great at summarizing and simplifying,
Using AI as a co-intelligence, as I did while writing, is where AI is the most valuable.
The innovation groups and strategy councils inside organizations can dictate policy, but there is no reason to believe that the corporate leaders of any organization are going to be wizards at understanding how AI might help a particular employee with a particular task. In fact, they are likely pretty bad at figuring out the best-use cases for AI. Individual workers, who are keenly aware of their problems and can experiment a lot with alternate ways of solving them, are far more likely to find powerful and targeted uses.
the best way for an organization to benefit from AI is to get the help of their most advanced users while encouraging more workers to use AI.
No company hired employees based on their AI skills, so AI skills might be anywhere.
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.
organizations can offer guarantees that no employees will be laid off as a result of AI use, or promise that workers can use the time they free up using AI to work on more interesting projects, or even end work early.
Workers, while worried about AI, tend to like using it because it removes the most tedious and annoying parts of their job, leaving them with the most interesting tasks. So, even as AI removes some previously valuable tasks from a job, the work that is left can be more meaningful and more high-value. This
You need to ask: What is your vision about how AI makes work better rather than worse? And this is where organizations with high degrees of trust and good cultures will have an advantage. If your employees don’t believe you care about them, they will keep their AI use hidden.
organizations should highly incentivize AI users to come forward, and expand the number of people using AI overall.
Think cash prizes that cover a year’s salary. Promotions. Corner offices.
Human attention remains finite, our emotions are still important, and workers still need bathroom breaks. The technology changes, but workers and managers are just people. This is what AI may alter.
We could imagine how LLMs might supercharge this process, creating an even more comprehensive panopticon: in this system, every aspect of work is monitored and controlled by AI. AI tracks the activities, behaviors, outputs, and outcomes of workers and managers. AI sets goals and targets for them, assigns tasks and roles to them, evaluates their performance, and rewards them accordingly.
LLMs might also provide feedback and coaching to help workers improve their skills and productivity. AI’s ability to act as a friendly adviser could sand down the edges of algorithmic control, covering the Skinner box in bright wrapping paper. But it would still be the algorithm in charge. If history is a precedent, this is a likely path for many companies.
We don’t need to subject vast numbers of humans to machine overlords. Rather, LLMs could help us flourish by making it impossible to ignore the truth any longer: a lot of work is really boring and not particularly meaningful. If we acknowledge that, w...
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maybe we should start the way every other automation wave has started: with the tedious, (mentally) dangerous, and repetitive.
how to make boring processes “AI friendly,” allowing machines (with human supervision) to fill our required forms.
“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”
The main idea behind flipped classrooms is to maximize classroom time for active learning and critical thinking, while using at-home learning for content delivery.
The way to be useful in the world of AI is to have high levels of expertise as a human.
a human working with an AI co-intelligence outperforms all but the best humans working without an AI.
