Confluence Book Note: Co-Intelligence by Ethan Mollick
Ethan Mollick, Wharton Professor and one of the world's leading applied thinkers on generative AI, has written a compact, practical guide to "living and working with AI."
Last fall we published our first “Book Note” in Confluence, on Mustafa Suleyman’s The Coming Wave1. This week we’re sharing our notes from Ethan Mollick’s recently-published Co-Intelligence: A Guide to Living and Working with AI, which many in our firm have already read and found valuable.
Overview
Readers of Confluence will know how much we admire Ethan Mollick’s work. For those who aren’t familiar with Mollick, he is an Associate Professor of Management at the University of Pennsylvania’s Wharton School and the author of the popular Substack One Useful Thing, which he describes as “a research-based view on the implications of AI.” We’ve followed Mollick and recommended that others do the same for nearly two years now. His work is consistently thoughtful, grounded in research, and focused on the practical implications and applications of AI.
It should come as no surprise, then, that the book exhibits those same qualities. Part I, which comprises roughly a quarter of the book, provides an overview of the current class of generative AI technologies, the challenges and opportunities that come with them, and some principles for integrating them into our lives (professional and personal). The rest of the book, in Part II, considers the practical implications and applications of AI through the lens of different personas (AI as a Creative, Coworker, Tutor, and Coach).
As always with Mollick’s work, the value is in its thoughtfulness and practicality. While the book does consider certain possible future scenarios, it is light on speculation. It’s more focused on the present near future: on what these technologies mean for us today, and on how we can make the most of them (and mitigate their downsides).
“Even if AI development were paused, the impact of AI on how we live, work, and learn is going to be huge, and warrants considerable discussion … The reality is that we are already living in the early days of the AI age, and we need to make some very important decisions about what that actually means.”
Notes
On AI Principles
Always invite AI to the table.
“You should try inviting AI to help you in everything you do, barring legal or ethical barriers. 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.”
On the Jagged Frontier of AI’s capabilities: “Imagine a fortress wall, with some towers and battlements jutting out into the countryside, while others fold back toward the center of the castle. That wall is the capability of AI, and the farther from the center, the harder the task. Everything inside the wall can be done by the AI; everything outside is hard for the AI to do. The problem is that the wall is invisible, so some tasks that might logically seem to be the same distance away from the center, and therefore equally difficult — say, writing a sonnet and an exactly fifty-word poem — are actually on different sides of the wall … To figure out the shape of the frontier, you will need to experiment.”
“As artificial intelligence proliferates, users who intimately understand the nuances, limitations, and abilities of AI tools are uniquely positioned to unlock AI’s full innovative potential … Workers who figure out how to make AI useful for their jobs will have a large impact.”
Be the human in the loop.
“For now, AI works best with human help, and you want to be that helpful human. As AI gets more capable and requires less human help — you still want to be that 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 is often more important than another goal, ‘be accurate.’”
“So, to be the human in the loop, you will need to be able to check the AI for hallucinations and lies and be able to work with it without being taken in by it. You provide crucial oversight, offering your unique perspective, critical thinking skills, and ethical considerations. This collaboration leads to better results and keeps you engaged with the AI in the process, preventing overreliance and complacency.”
Treat AI like a person (but tell it what kind of person it is).
“As imperfect as the analogy is, working with AI is easiest if you think of it like an alien person rather than a human-built machine.”
“Imagine your AI collaborator as an infinitely fast intern, eager to please but prone to bending the truth. Despite our history of thinking about AI as unfeeling, logical robots, LLMs act more like humans. They can be creative, witty, and persuasive, but they can also be evasive and make up plausible, but wrong, information when pressed to give an answer. They are not experts in any domain, but they can mimic the language and style of experts in ways that can be either helpful or misleading. They are unaware of the real world but can generate plausible scenarios and stories based on common sense and patterns … They are, in short, suggestible and even gullible.”
“To make the most of this relationship, you must establish a clear and specific AI persona, defining who the AI is and what problems it should tackle.”
Assume this is the worst AI you will ever use.
“Bigger, smarter Frontier Models are coming, along with an increasing range of smaller and open-source AI platforms. In addition, AIs are becoming connected to the world in new ways: they can read and write documents, see and hear, produce voice and images, and surf the web. LLMs will become integrated with your email, web browser, and other common tools. And the next phase of AI development will involve more ‘agents’ – semi-autonomous, AIs that can be given a goal (‘plan a vacation for me’) and execute it with minimal human help. After this, however, things start to get hazy, the future becomes less clear, and the risks, and benefits, of AI start to multiply … There is one obvious conclusion, one that is hard for a lot of us to grasp: whatever AI you are using right now is going to be the worst AI you will ever use.”
“We are playing Pac-Man in a world that will soon have PlayStation 6s.”
“As AI becomes increasingly capable of performing tasks once thought to be exclusively human, we’ll need to grapple with the awe and excitement of living with increasingly powerful alien co-intelligences — and the anxiety and loss they’ll also cause. Many things that once seemed exclusively human will be able to be done by AI.”
On AI Personas
“Traditional software is predictable, reliable, and follows a strict set of rules. When properly built and debugged, software yields the same outcomes every time. AI, on the other hand is anything but predictable and reliable. It can surprise us with novel solutions, forget its own abilities, and hallucinate incorrect answers.”
“AI doesn’t act like software, but it does act like a human being. I’m not suggesting that AI systems are sentient like humans, or that they will ever be. Instead, I’m proposing a pragmatic approach: treat AI as if it were human because, in many ways, it behaves like one.”
“AI excels at tasks that are intensely human. It can write, analyze, code, and chat. It can play the role of marketer or consultant, increasing productivity by outsourcing mundane tasks. However, it struggles with tasks that machines typically excel at, such as repeating a process consistently or performing complex calculations without assistance. AI systems also make mistakes, tell lies, and hallucinate answers, just like humans. Each system has its own idiosyncratic strengths and weaknesses, just like each human colleague does … The abilities of AI systems range widely, from middle-school to PhD level, depending on the task.”
AI as a Creative
“The biggest issue limiting AI is also one of its strengths: its notorious ability to make stuff up, to hallucinate … The same feature that makes LLMs unreliable and dangerous for factual work also makes them useful. The real question becomes how to use AI to take advantage of its strengths while avoiding its weaknesses.”
“How can AI, a machine, generate something new and creative? The issue is that we often mistake novelty for originality. New ideas do not come from the ether; they are based on existing concepts. Innovation scholars have long pointed to the importance of recombination in generating ideas … LLMs are connection machines. They are trained by generating relationships between tokens that may seem unrelated to humans but represent some deeper meaning.”
“It would be naïve to see only the upside here. Especially as AI work becomes easy to generate at the push of a button. I mean that literally, as every major office application and email client will include a button to help you create a draft of your work. It deserves capital letters: The Button … When faced with the tyranny of the blank page, people are going to push The Button. It is so much easier to start with something than nothing. Students are going to use it to start essays. Managers will use it to start emails, reports, or documents. Teachers will use it when providing feedback. Scientists will use it to write grants. Concept artists will use it for their first draft. Everyone is going to use The Button … The implications of having AI write our first drafts (even if we do the work ourselves, which is not a given) are huge.”
AI as a Coworker
“One of the first questions people ask when they start using AI seriously is whether it will affect their job. The answer is probably yes.”
“Regardless of its nature, your job is likely to overlap with AI in the near future. That doesn’t mean your job will be replaced. To understand why, we need to consider jobs more carefully, viewing them from multiple levels. Jobs are composed of bundles of tasks. Jobs fit into larger systems. Without considering systems and tasks, we can’t really understand the impact of AI on jobs.”
“Individual workers, who are keenly aware of their problems and can experiment a lot with alternative ways of solving them, are far more likely to find powerful and targeted use cases … At least for now, 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.”
AI as a Coach
“The biggest danger to our educational system posed by AI is not its destruction of homework, but rather its undermining of the hidden system of apprenticeship that comes after formal education.”
“People have traditionally gained expertise by starting at the bottom. The carpenter’s apprentice, the intern at a magazine, the medical resident. These are usually pretty horrible jobs, but they serve a purpose. Only by learning from more experienced experts in a field, and trying and failing under their tutelage, do amateurs become experts. But that is likely to change rapidly with AI. As much as the intern or first-year lawyer doesn’t like being yelled at for doing a bad job, their boss would rather just see the job done fast than deal with the emotions and errors of a real human being. So they will do it themselves with AI, which, if not yet the equivalent of a senior professional in many tasks, is often better than a new trainee. This could create a major training gap.”
“Even as experts become the only people who can effectively check the work of ever more capable AIs, we are in danger of stopping the pipeline that creates experts. The way to be useful in the world of AI is to have high levels of expertise as a human … An AI future requires that we lean into building our own expertise as human experts.”
On Possible Futures
“Even if AI doesn’t advance further, some of its implications are already inevitable. The first set of certain changes from AI is going to be about how we understand, and misunderstand, the world … The online information environment is going to become completely unmanageable, with fact-checkers overwhelmed by the flood … Our already fragile consensus about what facts are real is likely to fall apart, quickly.”
“If we focus solely on the risks or benefits of building super-intelligent machines, it robs us of our abilities to consider the more likely [scenarios] where AI is ubiquitous but very much in human control. And in those worlds, we get to make choices about what AI means.”
“The thing about a widely applicable technology is that decisions about how it is used are not limited to a small group of people. Many people in organizations will play a role in shaping what AI means for their team, their customers, their students, their environment. But to make those choices matter, serious discussions need to start in many places, and soon. We can’t wait for decisions to be made for us, and the world is advancing too fast to remain passive.”
Quick Quotes
“I believe the cost of getting to know AI — really getting to know AI — is at least three sleepless nights.”
“I can assure you that there is nobody who has the complete picture of what AI means, and even the people making and using these systems do not understand their full implications.”
“We have invented technologies, from axes to helicopters, that boost our physical capabilities; and others, like spreadsheets, that automate complex tasks; but we have never built a generally applicable technology that can boost our intelligence.”
“Given that AI is a General Purpose Technology, there is no single manual or instruction book that you can refer to in order to understand its value and its limits.”
“AI can be very useful. Not just for job tasks… but also because an alien perspective can be helpful.”
“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.”
“AI is trained on vast swaths of humanity’s cultural heritage, so it can often be best wielded by people who have a knowledge of that heritage.”
“…as my students learn, if you work interactively with the AI, the outcome doesn’t feel generic, it feels like a human did it.”
“No company hired employees based on their AI skills, so AI skills might be anywhere … As a result, companies need to include as much of their organization as possible in their AI agenda.”
“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 that AI was trained on. By breaking the pattern, you can get much more useful and interesting outputs.”
“Being ‘good at prompting’ is a temporary state of affairs. The current AI systems are already very good at figuring out your intent, and they are getting better.”
“If you want to do something with AI, just ask it to help you do the thing. ‘I want to write a novel; what do you need to know to help me?’ will get you surprisingly far.”
“For slightly more advanced prompts, think about what you are doing as programming in prose.”
“LLMs are just one approach to AI; other successor technologies may overcome [their] limits.”
AI Disclosure: We used generative AI in creating imagery for this post. We also used it as a proofreader.Note that since the time of our publishing that Book Note in September of 2023, Suleyman has left Inflection and is now the head of consumer AI at Microsoft.