How to Help People Thrive with AI

**Nathaniel Whittemore** (0:00)
Today on The AI Daily Brief, how to help people thrive with AI.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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The big theme of this week has been models, models, models and more models. And yet, all the models in the world aren't going to help people learn how to get value out of AI.
Yes, model improvements can deal with fail cases from previous models and open up new opportunities. But if people aren't supported in learning how to use them, it's kind of all for not. And that certainly seems to be what today's sponsor section found with their most recent AI Proficiency Report. The story the report tells is one that will be very familiar for many of you guys who work inside big companies. Their first key finding they summed up, agents are here, agentic readiness is not. While 69% of workers they surveyed reported that their organization had taken some action on AI agents, only 16% actually use an agentic tool at work, and less than 10% can define an AI agent in their own words. This isn't surprising when you find out that only 30% of employees at organizations with AI agents have actually received agentic training.
Now, this study is the latest to show this sort of detail, but is far from the only one out there telling this story. Where we're going to end today is some ideas and examples of how to help people thrive more with AI. But before we do that, since this is a weekend, big think slash long reads type of episode, I actually want to read some excerpts of this recent long-form piece in the Atlantic by David Brooks called The People Who Will Thrive in the AI Age. Brooks argues that what will differentiate people is not how smart they are, but instead their relationship to mental effort. Brooks writes, Remember when AI was going to take away our jobs and leave humans with nothing to do? So far, that doesn't seem to be happening. Researchers from ActiveTrack analyzed the digital activity of more than 10,000 workers and found that when people adopted AI, their work life became more intense, not less. The time that these early adapters spent on email, messaging and chat apps more than doubled. Their use of business software rose by 94%.
Researchers from UC Berkeley's Haas School of Business found that when using AI, workers started taking on tasks that they had previously outsourced, because activities such as coding and engineering became easier to do. They squeezed in work bursts in the evening, on weekends, in waiting rooms and wherever else they had a spare moment and AI was handy. They also did a lot more multitasking, supervising a bunch of bots doing things simultaneously. The general pattern that the research points to is that many people don't use the time they save using AI to do less, they use the time to take on new tasks. AI also seems to shift workers' expectations and their bosses' expectations about how much they should accomplish in a day.
Every hour feels more crowded but also more frazzled. The ActiveTrack researchers found that the time people spent on focused, uninterrupted work fell by 9%.
There's even a name for this mental state. AI brain fry.
Now, taking a pause from Brooks' piece for a minute, there is a lot of this feeling going around. Midjourney founder David Hulls recently tweeted, My friends are all feeling extremely productive and also extremely drained with the latest coding models. This makes me feel like something is wrong and also that there might be a big opportunity. Does anyone have any strategies they use to make it feel better day-to-day?
This is also something I've talked about a lot. A couple of months ago in an episode, I introduced the idea of the infinite backlog. Basically, this never-ending list of work that ensures that there is always a next thing to do. Now in the pre-AI world, while the list was never-ending, there were reasonable stopping points on that list. What changed with AI and agents specifically is that now that you can effectively duplicate yourself through agents, it feels as though there should never be any downtime in work. Agents don't need weekends, they don't need sleep, so can't they be taking on that infinite backlog constantly? Of course, in reality, the limits have just shifted from how much we can do to how much planning and oversight we can support. In any case, back to Brooks, he writes, A guiding principle of the emerging AI age is this. When intelligence is plentiful, volition is valuable. The people who are going to make a difference are not the ones who seek relaxation and passively use AI to work less. They are the ones who will seek improvement and actively wrestle with AI to develop their own mental capabilities and accomplish more. In other words, what will differentiate people is not how smart they are but their relationship to mental effort. Right now, some people have what psychologists call a high need for cognition. They enjoy thinking hard. These are the people who enjoy playing difficult games and reading dense books. On the other end of the spectrum, there are the cognitive misers, the people who find it unpleasant to think hard and take any opportunity not to do it. In the middle are the people who have a medium need for cognition. They will put in the effort when they really care about something but they don't intrinsically enjoy it. Need for cognition correlates with intelligence but is not the same thing. We all know a lot of really smart people who don't like to work hard. This leads Brooks to start to identify a number of different archetypes for people who will have different experiences with AI.