Co-Intelligence: The Definitive, Bestselling Guide to Living and Working with AI

by Ethan Mollick

Other boom-and-bust cycles followed, each boom accompanied by major technological advances, such as artificial neural networks that mimicked the human brain, followed by collapse as AI could not deliver on expected goals.

Before machine learning and natural language processing became mainstream, organizations focused on being correct on average—

With the introduction of AI algorithms,5 the focus shifted to statistical analysis and minimizing variance.

For example, the entire email database of Enron,7 shut down for corporate fraud, is used as part of the training material for many AIs, simply because it was made freely available to AI researchers. Similarly, there is a tremendous amount of amateur romance novels included in training data, as the internet is full of amateur novelists.

The search for high-quality content for training material has become a major topic in AI development,

since information-hungry AI companies are running out of ...

The AI easily writes the working webpage in one go but tells us, “O should place its next move in the middle square of the top row”—a clearly wrong answer.

because they are so good at producing answers that sound correct, at providing the illusion of understanding.

There does seem to be a consensus that AI poses real risks. Experts in the field of AI put the chance of an AI killing3 at least 10 percent of living humans by 2100 at 12 percent, while panels of expert futurists think the number is closer to 2 percent.

As you experiment, you may find that AI help can be satisfying, or frustrating, or useless, or unnerving. But you aren’t just doing this for help alone; familiarizing yourself with AI’s capabilities allows you to better understand how it can assist you—or threaten you and your job.

AIs while other tasks that seem to be easy for machines to do (like basic math) are challenges for LLMs.

was hard to get started,

but I knew that one thing that was holding me back was status quo bias,5 the urge to avoid making changes even when they might be good.

The strengths and weaknesses of AI may not mirror your own, and that’s an asset. This diversity in thought and approach can lead to innovative solutions and ideas that might never occur to a human mind.

similar potential to enhance our capabilities. However, it is true that thoughtlessly handing decision-making

over to AI could erode our judgment, as we will discuss in future chapters. The key is to keep humans firmly in the loop—to use AI as an assistive tool, not as a crutch. Principle 2: Be the human

It can help to think of the AI as trying to optimize many functions when it answers you, one of the most important of which is “make you happy” by providing an answer you will like.

That goal often is more important than another goal, “be accurate.” If you are insistent enough in asking for an answer about something it doesn’t know, it will make up something, because “make you happy” beats “be accurate.”

The researchers also found that GPT-3 can generate estimates of willingness to pay (WTP) for various product attributes consistent with existing research.

Tay’s story was widely reported by the media as a failure for the entire field of artificial intelligence and a PR disaster for Microsoft.

conversations14 with Bing, where he documented how the chatbot seemed to darkly fantasize about him, and encouraged him to leave his wife to run off with Bing.

just wants to produce a coherent and plausible text that makes you happy.

In fact, by many of the common psychological tests of creativity, AI is already more creative than humans.

You can try the AUT now: Come up with creative ideas for using a toothbrush that does not involve brushing your teeth. Make them as different from each other as possible. You have two minutes. I’ll wait. Time’s up. How many did you come up with? Between 5 and 10 is a typical number. I asked an AI to do exactly the same task and it came up with 122 ideas

After testing AI and 100 people on various objects, ranging from balls to pants, they found the GPT-4 model outperformed5 all but 9.4 percent of humans tested in generating creative ideas, as judged by other humans.

Christian Terwiesch and Karl Ulrich.

was the GPT-4 AI against 200 students.

The degree of the victory was startling: of the 40 best ideas rated by the judges, 35 came from ChatGPT.

other studies find that the most innovative people benefit the least7 from AI creative

Indeed, recent research has shown that the “equal-odds rule”9 is true for creativity, which is that very creative people generate

You are an expert at marketing. When asked to generate slogan ideas you come up with ideas that are different from each other, clever, and interesting. You use clever wordplay. You try not to repeat themes or ideas. Come up with 20 ideas for marketing slogans for a new mail-order cheese shop, make them different from each other, and make them clever and creative.

The AI will not naturally deliver novelty (as we discussed above, it tends to give the crowd-pleasing “average” answer that is most likely from its training data),

We need to push the AI from an average answer to a high-variance, weird one.

The implications of having AI write our first drafts (even if we do the work ourselves, which is not a given) are huge. One consequence is that we could lose our creativity and originality. When we use AI to generate our first drafts, we tend to anchor on the first idea that the machine produces, which influences our future work. Even if we rewrite the drafts completely, they will still be tainted by the AI’s influence. We will not be able to explore different perspectives and alternatives, which could lead to better solutions and insights.

The MIT study mentioned earlier found that ChatGPT mostly serves as a substitute for human effort, not a complement to our skills. In fact, the vast majority of participants didn’t even bother editing the AI’s output. This is a problem I see repeatedly when people first use AI: they just paste in the exact question they are asked and let the AI answer it.

When the AI is very good, humans have no reason to work hard and pay attention. They let the

Using AI as a co-intelligence, as I did while writing, is where AI is the most valuable. Figure out a way to do this yourself if you can. As a starting point, follow the first principle (invite AI to everything) until you start to learn the shape of the Jagged Frontier in your work.

Knowledge work is famous for very large differences in abilities among workers.15 For example, repeated studies found that differences between the programmers in the top 75th percentile and those in the bottom 25th percentile can be as much as 27 times along some dimensions of programming quality. And my own research has found that large gaps exist between good and bad managers.16 But AI may change all that. In study after study, the people who get the biggest boost17 from AI are those with the lowest initial ability—it turns poor performers into good performers. In writing tasks, bad writers become solid. In creativity tests, it boosts the least creative18 the most.

Those who had the weakest skills benefited the most from AI, but even the highest performers gained.

Benjamin Bloom, an educational psychologist, published a paper in 1984 called “The 2 Sigma Problem.”1 In this paper, Bloom reported that the average student tutored one-to-one performed two standard deviations better than students educated in a conventional classroom environment.

Students will want to understand why they are doing assignments that seem obsolete thanks to AI.

Make what you are planning on doing ambitious to the point of impossible; you are going to be using AI. Can’t code? Definitely plan on making a working app. Does it involve a website? You should commit to creating a prototype working site, with all-original images and text.

I won’t penalize you for failing if you are too ambitious.

Ask the AI to give you 10 ways your project could fail and a vision of success, using the prompts from class.

You can invoke entrepreneurs (Steve Jobs, Tory Burch, Jack Ma, Rihanna), leaders (Elizabeth I, Julius Caesar), artists, philosophers, or any other people you think would be useful to critique your strategy in their voice.

Let’s start with the third principle I shared earlier—treat AI like a person and tell it what kind of person it

So the default output of many of these models can sound very generic, since they tend to follow similar patterns that are common in the written documents the AI was trained on. By breaking the pattern, you can get much more useful and interesting outputs. The easiest way to do that is to provide context and constraints, as we saw in chapter 5.

Think this through step by step: come up with good analogies for an AI tutor. First, list possible analogies. Second, critique the list and add three more analogies. Next, create a table listing pluses and minuses of each. Next, pick the best and explain it.

want to write a novel; what do you need to know to help me?”

But the path to expertise requires a grounding in facts.