The reader's edition
Co-Intelligence: Living and Working with AI: the summary
Ethan Mollick is a professor at the Wharton School of the University of Pennsylvania who studies innovation and entrepreneurship and writes the One Useful Thing newsletter. He argues that AI is best treated as a strange new kind of co-worker: very good at some tasks, surprisingly bad at others that look similar, and only understood by using it. He calls that uneven edge the jagged frontier, and offers four rules for working with it: always invite AI to the table, be the human in the loop, treat AI like a person but tell it what kind of person it is, and assume this is the worst AI you will ever use. The middle of the book looks at AI as a person, a creative, a coworker, a tutor and a coach. It draws on his own classroom experiments and on research with working professionals, including a study of consultants at Boston Consulting Group, and ends with four scenarios for where AI could go next. Read a chapter at a time, with a printable action book at the end.
- Ethan Mollick
- 2024
- 4 chapters
- 6 min read
- 9 takeaways
This is HourLife's reading of Co-Intelligence: Living and Working with AI, in our own words. It is not a substitute for the book.
Chapter 01
Before you start
The book in a minute
Tap a paragraph to highlight it. Turn pages with the arrows, the arrow keys, or a swipe.
Ethan Mollick is a professor at the Wharton School of the University of Pennsylvania who studies innovation and entrepreneurship and writes the One Useful Thing newsletter. He argues that AI is best treated as a strange new kind of co-worker: very good at some tasks, surprisingly bad at others that look similar, and only understood by using it. He calls that uneven edge the jagged frontier, and offers four rules for working with it: always invite AI to the table, be the human in the loop, treat AI like a person but tell it what kind of person it is, and assume this is the worst AI you will ever use. The middle of the book looks at AI as a person, a creative, a coworker, a tutor and a coach. It draws on his own classroom experiments and on research with working professionals, including a study of consultants at Boston Consulting Group, and ends with four scenarios for where AI could go next.
Below are the 9 ideas HourLife readers vote up most, each in our words with a note on what it asks of you, and then the steps that put them to work.
Chapter 02
What readers keep
The takeaways
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1
HourLife takeaway
AI's abilities form a jagged frontier, so how it does on one task tells you little about the next.
The line between what AI does well and what it does badly is uneven, and tasks that feel equally hard to us can land on opposite sides of it. Mollick describes a study with Boston Consulting Group consultants: on tasks inside the frontier, those using GPT-4 did better work, and on a task chosen to sit just outside it, they did worse than colleagues working without it.
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2
HourLife takeaway
The only way to learn where the frontier runs through your work is to use AI on your work.
Nobody has a manual for this, and the people who build these systems are often surprised by what they can do. That is the reason for the first rule, always invite AI to the table. Try it on the tasks you actually do, within your legal and ethical limits, and notice where it helps and where it fails.
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3
HourLife takeaway
Talk to AI like a person, and tell it which person to be.
Mollick knows AI is software, not a person, but finds it works better when you give it a role and some context: an editor, a sceptical critic, a teacher for a particular audience. A persona moves the answer from generic to specific. He also warns against forgetting what it really is.
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4
HourLife takeaway
The work stays yours, so stay the human in the loop.
AI can state invented facts with total confidence, and it cannot reliably tell you when it is wrong. Being the human in the loop means checking, judging and owning what goes out. It also means keeping your own skill sharp, because you can only catch a mistake you know how to spot.
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5
HourLife takeaway
Centaurs split the work with AI along a clean line; cyborgs weave it through every step.
A centaur divides a job: you choose the argument, the AI drafts the chart. A cyborg works back and forth inside the task, handing over a sentence and taking it back rewritten. Mollick treats both as good ways to work. What matters is choosing the split on purpose.
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6
HourLife takeaway
Sort your tasks into Just Me, Delegated and Automated, and expect the sort to change.
Just Me tasks stay with you, because AI cannot do them well or because you want them to be yours. Delegated tasks go to AI and come back to you to check. Automated tasks can run on their own. As the tools improve, tasks move from one pile to the next.
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7
HourLife takeaway
Assume today's AI is the worst you will ever use.
The fourth rule is a warning against settling your opinion early. Something AI fails at this year may be easy for it next year. Write down the tasks you have ruled out, and test them again when a new model arrives.
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8
HourLife takeaway
AI can tutor and coach you, but it cannot do the learning for you.
In the chapters on AI as a tutor and a coach, Mollick sees real promise in explanation and feedback pitched at your level. The effort of learning still has to happen in your own head, though. Using AI to skip the struggle means skipping the skill, and the skill is what lets you judge the AI.
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9
HourLife takeaway
Where AI goes next is not settled, and the book sketches four possible futures.
The last chapter lays out four scenarios: AI stays about as good as it is, it keeps improving slowly, it improves exponentially, or it reaches something like a machine god. Mollick's point is that people and organisations still choose how AI is used at work, whichever future arrives.
Chapter 03
Put it to work
Your action book
Do the setup steps once, then keep the habits going. The setup changes your week; the habits keep it changed after the first good one.
The download puts this whole reading and a printable action book in one PDF: the setup checklist, then a page of real calendar days for each habit, starting on the day you choose.
Set up once
Map the tasks in your week
Write down eight to twelve things you do in a normal week. Sort each one as Just Me, Delegated or Automated, and rate how well you think AI handles it today.
Check what you may share
Before you paste work into an AI tool, find your employer's or school's policy on it. Note which kinds of data, such as client names or health details, must never go in.
Write three reusable personas
Write three short role briefs you can paste at the top of a prompt, such as a blunt editor, a sceptical analyst and a patient tutor. Keep them in one note.
Set your checking rules
For each Delegated task, write down what you check before anything leaves your hands: names, numbers, dates, quotes and sources. Keep the list next to where you work.
Retest a task you wrote off
Pick one task where AI let you down before. Try it again with the current model, a clear persona and more context, and write down what changed.
Keep it up
Invite AI to one new task a week
Each Monday, pick one task you have never tried with AI and try it once. Afterwards, decide whether it belongs in Just Me, Delegated or Automated.
Ask for many options, then choose
When you need ideas, ask for twenty rather than one, and ask for some odd ones. Your job is to pick and combine the best, not to accept the first.
Keep a frontier log
After each real use, write one line: the task, what worked and what failed. Read the log once a month to see where your frontier has moved.
Chapter 04
The last word
Before you go
Pick one step from the action book and do it today. An idea from a book starts to count once it changes what one ordinary day looks like.
Find the edge by working on it: bring AI in, keep the judgement yours, and test again when the tools change.
That is the end of our reading. Where to go from here, or go back to the full Co-Intelligence: Living and Working with AI page.
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