What do you think?
Rate this book
Co-Intelligence: Living and Working with AI
**A New York Times Bestseller**
'Co-Intelligence is the very best book I know about the ins, outs, and ethics of generative AI. Drop everything and read it cover to cover NOW' Angela Duckworth
Consumer AI has arrived. And with it, inescapable upheaval as we grapple with what it means for our jobs, lives and the future of humanity.
Cutting through the noise of AI evangelists and AI doom-mongers, Wharton professor Ethan Mollick has become one of the most prominent and provocative explainers of AI, focusing on the practical aspects of how these new tools for thought can transform our world. In Co-Intelligence, he urges us to engage with AI as co-worker, co-teacher and coach. Wide ranging, hugely thought-provoking and optimistic, Co-Intelligence reveals the promise and power of this new era.
'Co-Intelligence is the very best book I know about the ins, outs, and ethics of generative AI. Drop everything and read it cover to cover NOW' Angela Duckworth
Consumer AI has arrived. And with it, inescapable upheaval as we grapple with what it means for our jobs, lives and the future of humanity.
Cutting through the noise of AI evangelists and AI doom-mongers, Wharton professor Ethan Mollick has become one of the most prominent and provocative explainers of AI, focusing on the practical aspects of how these new tools for thought can transform our world. In Co-Intelligence, he urges us to engage with AI as co-worker, co-teacher and coach. Wide ranging, hugely thought-provoking and optimistic, Co-Intelligence reveals the promise and power of this new era.
243 pages, Kindle Edition
First published April 2, 2024
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 30 of 297 reviews
May 28, 2024
This is an interesting and useful book, and if you're an academic or educator who's trying to find a good strategy for dealing with the AI revolution then I strongly recommend reading it. Everyone I know in this area is having problems: the whole landscape has changed overnight now that students have access to ChatGPT, Gemini, Claude and similar platforms. People have tried banning students from using them, which doesn't work, and they've tried ignoring the problem and hoping things will somehow just sort themselves out, which works even less. Ethan Mollick, a US professor of business studies, realised at an early stage that a more coherent approach was to embrace the new technology and learn to use it as well as possible. Even if you think this is absolutely the wrong thing to do, you should read about his experiences to see what embracing it might involve; a great many of your colleagues will be taking this route.
Mollick has some extremely sensible advice to offer; at times it may seem paradoxical, but we're in a paradoxical situation. He repeatedly says that AIs are not human beings - in particular, he considers it clear that they are not conscious - but he also says that you will be better at using them if you treat them as though they were human beings. We don't yet have a good way to conceptualise AIs, and they behave much more like people than like the machines we're used to. He says in particular that it will be helpful to tell the AI what kind of person you want them to resemble, and gives nice examples of how useful it can be to have an AI who's been instructed to be, inter alia, the object of a sales pitch, a critical reader of your essay, or a potentially interested but uninformed member of the public. He repeatedly urges you to be sceptical and gather information. The abilities of current-generation AIs are often hard to imagine until you've actually tried them on a given task: a striking example which many people have discovered independently is that ChatGPT can't spot a one move threat at Tic-Tac-Toe, but if asked will immediately write you a Python script that plays the game perfectly. Who would have predicted that?
Mollick not merely encourages but requires his students to use AI, and shows you how much they can get out of it. The teacher can dramatically raise the bar, since every member of the class now has a competent virtual team working for them. You don't have to limit business students to describing the website they would build; even if they can't code, you ask them actually to build a prototype, relying on the AI to take care of the implementation. Mollick says he can't code, but found this worked for him, and he's passing on his experience. The technology is improving all the time, and things which were difficult or impossible a few months ago may be quite feasible in the next release. ChatGPT 3.5, which took the world by storm in November 2022, is already starting to feel quaint and old-fashioned. When the voice-enabled version of ChatGPT-4o becomes generally available (looks like it will be Q3/Q4 2024), we'll hit another inflection point. Video capabilities are evidently in the pipeline, as are other less in-your-face but possibly even more important improvements related to planning and reasoning. The impact on education will be revolutionary. Mollick quotes well-known studies showing that personal tuition gives students a two-sigma advantage, moving an average student to the 98th percentile. We are within sight of a world where all students in all but the poorest countries will be able to get expert personal tuition in all subjects.
Where is this going long-term? Mollick honestly says he doesn't know, and there's little point in speculating; what makes sense is to keep up with events and understand what new options are materialising, whether we like them or not. It's possible that AI development will plateau or at least start levelling off. But that isn't what it looks like right now. It's not accidental that we see the Apple of Eden on the front cover.
Such extraordinary times we're living in.
Mollick has some extremely sensible advice to offer; at times it may seem paradoxical, but we're in a paradoxical situation. He repeatedly says that AIs are not human beings - in particular, he considers it clear that they are not conscious - but he also says that you will be better at using them if you treat them as though they were human beings. We don't yet have a good way to conceptualise AIs, and they behave much more like people than like the machines we're used to. He says in particular that it will be helpful to tell the AI what kind of person you want them to resemble, and gives nice examples of how useful it can be to have an AI who's been instructed to be, inter alia, the object of a sales pitch, a critical reader of your essay, or a potentially interested but uninformed member of the public. He repeatedly urges you to be sceptical and gather information. The abilities of current-generation AIs are often hard to imagine until you've actually tried them on a given task: a striking example which many people have discovered independently is that ChatGPT can't spot a one move threat at Tic-Tac-Toe, but if asked will immediately write you a Python script that plays the game perfectly. Who would have predicted that?
Mollick not merely encourages but requires his students to use AI, and shows you how much they can get out of it. The teacher can dramatically raise the bar, since every member of the class now has a competent virtual team working for them. You don't have to limit business students to describing the website they would build; even if they can't code, you ask them actually to build a prototype, relying on the AI to take care of the implementation. Mollick says he can't code, but found this worked for him, and he's passing on his experience. The technology is improving all the time, and things which were difficult or impossible a few months ago may be quite feasible in the next release. ChatGPT 3.5, which took the world by storm in November 2022, is already starting to feel quaint and old-fashioned. When the voice-enabled version of ChatGPT-4o becomes generally available (looks like it will be Q3/Q4 2024), we'll hit another inflection point. Video capabilities are evidently in the pipeline, as are other less in-your-face but possibly even more important improvements related to planning and reasoning. The impact on education will be revolutionary. Mollick quotes well-known studies showing that personal tuition gives students a two-sigma advantage, moving an average student to the 98th percentile. We are within sight of a world where all students in all but the poorest countries will be able to get expert personal tuition in all subjects.
Where is this going long-term? Mollick honestly says he doesn't know, and there's little point in speculating; what makes sense is to keep up with events and understand what new options are materialising, whether we like them or not. It's possible that AI development will plateau or at least start levelling off. But that isn't what it looks like right now. It's not accidental that we see the Apple of Eden on the front cover.
Such extraordinary times we're living in.
April 5, 2024
As someone who keeps up with Ethan Mollick's Substack and as someone who's quite interested in AI, I picked up this book instantly.
It's a solid layman's introduction to the current state of LLMs. Well-written, but if you've been playing around with AI yourself, there's likely nothing new here. This book is written for the rank beginner and does a good job at highlighting all the different ways LLMs can be used today, with examples.
Personally I was disappointed with how the book seemed content to give only a broad surface level overview of the state of LLMs. It would have been interesting for it to have dived deeper into the differences between Claude, GPT-4, Gemini etc, and it would've also been cool if it touched upon the implications of local models. However, I understand also that it's a rapidly changing space and devoting too much time to the nitty-gritty of what's happening today runs the risk of making the book obsolete in a few months. And to be fair, Ethan Mollick does in fact give his thoughts on the current frontier models on his Substack: https://open.substack.com/pub/oneusef...
All in all, it does what it does well. If I were to meet someone who is completely ignorant about LLMs and what can be done with LLMs today, I'd recommend this book.
For more detailed dives on AI, I'd recommend reading the articles on Mollick's Substack as well as keeping up with TheZvi's weekly AI roundup.
It's a solid layman's introduction to the current state of LLMs. Well-written, but if you've been playing around with AI yourself, there's likely nothing new here. This book is written for the rank beginner and does a good job at highlighting all the different ways LLMs can be used today, with examples.
Personally I was disappointed with how the book seemed content to give only a broad surface level overview of the state of LLMs. It would have been interesting for it to have dived deeper into the differences between Claude, GPT-4, Gemini etc, and it would've also been cool if it touched upon the implications of local models. However, I understand also that it's a rapidly changing space and devoting too much time to the nitty-gritty of what's happening today runs the risk of making the book obsolete in a few months. And to be fair, Ethan Mollick does in fact give his thoughts on the current frontier models on his Substack: https://open.substack.com/pub/oneusef...
All in all, it does what it does well. If I were to meet someone who is completely ignorant about LLMs and what can be done with LLMs today, I'd recommend this book.
For more detailed dives on AI, I'd recommend reading the articles on Mollick's Substack as well as keeping up with TheZvi's weekly AI roundup.
June 18, 2024
This one is really OK as your first step into understanding of what AI is. And by "AI" the author mostly means our current understanding of AI: LLM-powered Gen AI apps. If you're a technical person and you've already done a deep dive into how transformers work, what is really under the hood of DL, what are the consequences of the probabilistic models used in apps like ChatGPT, then probably you won't find that much novelty here.
Frankly speaking, I reached out for "Co-Intelligence" mostly because of the promise to tackle sociological aspect of "co-existence" with Gen AI. I really wanted to move outside of my "belief bubble" here, to refresh my perspective with some other points of view. Did it work? Partially it did, Mollick was not afraid to speculate, but I've expected something more thought-provoking, maybe even controversial.
In the end, it's a decent book, mostly for non-technical folks who'd like to feel more comfortable with Gen AI & LLMs.
Frankly speaking, I reached out for "Co-Intelligence" mostly because of the promise to tackle sociological aspect of "co-existence" with Gen AI. I really wanted to move outside of my "belief bubble" here, to refresh my perspective with some other points of view. Did it work? Partially it did, Mollick was not afraid to speculate, but I've expected something more thought-provoking, maybe even controversial.
In the end, it's a decent book, mostly for non-technical folks who'd like to feel more comfortable with Gen AI & LLMs.
May 19, 2024
I wanted to love this book -- and while it's funny and humorous, it's basically a long blog post or online message board discussion. The conversations with AI are amusing - but not substantive.
The author talks about anthropomorphization -- and dismisses people talking to their pets as the same as talking to their cars or other inanimate objects. And yet - he wants to make a case for AI being some kind of "alien mind" - when he's making a stronger case for it as a mirror of our own expectations.
Throughout the book he talks about how AI is filling in the most probable or likely response -- so if you say "To be or not ___ " it's going to say "to be" since that is the most probable. If you say "The alien ate a banana because ___" you'll get more variety every time you ask the question because it's not a topic or subject reflected in the AI training corpus.
AI is just another way for us to summarize back all the stuff we've written/created with words or images -- to us. It's more like a fun-house mirror than an intelligence.
My cats are more intelligent and capable of communication than an AI -- so where does this leave us?
Humans want to imagine that AI is more intelligent because it sounds like us and tells us what we want to hear. AI is very conformist - it will rewrite and reshape your thoughts and ideas to make them more appealing based upon the corpus of information it has already digested. It will align your communication to meet the greatest common denominator. You can ask it questions and it will tell you to analyze "Heart of Darkness" vis a vis Jane Austen's marriage plots -- and come up with some reasonably interesting points based on what it expects are most probable points from what we have already fed it. NOT because it's thinking of these things. Rather, AI acts as a sophisticated tool for summarizing and regurgitating information in a manner that aligns with human expectations.
I'd like to see a deeper exploration of AI's capabilities and limitations beyond surface-level interactions examining the fundamental nature of AI and its true intelligence compared to human and even animal cognition.
The author quotes someone who says that humans are just a historical point in the evolution of "intelligence" as if that is an autonomous being or subject. I'd contend that it is not -- we aren't merely vessels for "intelligence." There's no hierarchy of value based on "intelligence."
However, I do appreciate the author's optimism that AI will remove the boring/redundant tasks from human labor and his call to consider universal basic income and healthcare as real needs as humans move toward an era where we should focus our attention on tasks and activities that are more intrinsically rewarding to us and which do not require a 40 hour (or more) work week.
The mythical 4 day work week has been promised for decades, the practicalities of achieving a reducing "full time" work weeks remain uncertain. Striking a balance between dystopian and utopian visions of AI's impact on society is crucial for informed decision-making.
The author talks about anthropomorphization -- and dismisses people talking to their pets as the same as talking to their cars or other inanimate objects. And yet - he wants to make a case for AI being some kind of "alien mind" - when he's making a stronger case for it as a mirror of our own expectations.
Throughout the book he talks about how AI is filling in the most probable or likely response -- so if you say "To be or not ___ " it's going to say "to be" since that is the most probable. If you say "The alien ate a banana because ___" you'll get more variety every time you ask the question because it's not a topic or subject reflected in the AI training corpus.
AI is just another way for us to summarize back all the stuff we've written/created with words or images -- to us. It's more like a fun-house mirror than an intelligence.
My cats are more intelligent and capable of communication than an AI -- so where does this leave us?
Humans want to imagine that AI is more intelligent because it sounds like us and tells us what we want to hear. AI is very conformist - it will rewrite and reshape your thoughts and ideas to make them more appealing based upon the corpus of information it has already digested. It will align your communication to meet the greatest common denominator. You can ask it questions and it will tell you to analyze "Heart of Darkness" vis a vis Jane Austen's marriage plots -- and come up with some reasonably interesting points based on what it expects are most probable points from what we have already fed it. NOT because it's thinking of these things. Rather, AI acts as a sophisticated tool for summarizing and regurgitating information in a manner that aligns with human expectations.
I'd like to see a deeper exploration of AI's capabilities and limitations beyond surface-level interactions examining the fundamental nature of AI and its true intelligence compared to human and even animal cognition.
The author quotes someone who says that humans are just a historical point in the evolution of "intelligence" as if that is an autonomous being or subject. I'd contend that it is not -- we aren't merely vessels for "intelligence." There's no hierarchy of value based on "intelligence."
However, I do appreciate the author's optimism that AI will remove the boring/redundant tasks from human labor and his call to consider universal basic income and healthcare as real needs as humans move toward an era where we should focus our attention on tasks and activities that are more intrinsically rewarding to us and which do not require a 40 hour (or more) work week.
The mythical 4 day work week has been promised for decades, the practicalities of achieving a reducing "full time" work weeks remain uncertain. Striking a balance between dystopian and utopian visions of AI's impact on society is crucial for informed decision-making.
May 13, 2024
Clear-eyed primer to artificial intelligence, specifically the Large Language Models and generative AI now broadly available. I first heard Mollick on this episode of Ezra Klein's podcast, and appreciated his structured suggestions for using AI in daily tasks for work and general living.
Many of these same principles are repeated and expounded on in Chapter 3 of CO-INTELLIGENCE:
-- Invite AI to the table - innovation - using AI as a tool, not a crutch
--Learn to be the human in the loop -"There is no there there, despite it sounding like a human." Check the AI for lies, misinformation, and inaccuracy. Sharpen your own general and subject-matter knowledge and critical thinking, making you responsible for the output that you get from the AI
--Treat the AI like a person, but tell it what kind of person to be - conversational queries and tone yields the best results. Anthropomorphism is natural to the human mind, but the more we ascribe false agency to AI, the more we are exploited.
--This is the worst AI you will ever use - the models are constantly changing, as are you, so the results you get now will therefore be less "good" than anything you get in the future.
Mollick details the creative and collaborative ways that AI is being used, and cautiously reminds of the ways that these tools can be used for ill, encouraging a cautious but exploratory approach. There is not an all-out bowing to the overlords, or the opposite "the sky is falling"/hair on fire tone here - neutral and clear, this was a useful read for this moment in time in the evolutions of LLMs.
Audiobook note: Mollick reads his own words here, and when he is sharing AI-generated and polished text, an AI-generated voice reads it on the audiobook. Authentic and honest touch.
Many of these same principles are repeated and expounded on in Chapter 3 of CO-INTELLIGENCE:
-- Invite AI to the table - innovation - using AI as a tool, not a crutch
--Learn to be the human in the loop -"There is no there there, despite it sounding like a human." Check the AI for lies, misinformation, and inaccuracy. Sharpen your own general and subject-matter knowledge and critical thinking, making you responsible for the output that you get from the AI
--Treat the AI like a person, but tell it what kind of person to be - conversational queries and tone yields the best results. Anthropomorphism is natural to the human mind, but the more we ascribe false agency to AI, the more we are exploited.
--This is the worst AI you will ever use - the models are constantly changing, as are you, so the results you get now will therefore be less "good" than anything you get in the future.
Mollick details the creative and collaborative ways that AI is being used, and cautiously reminds of the ways that these tools can be used for ill, encouraging a cautious but exploratory approach. There is not an all-out bowing to the overlords, or the opposite "the sky is falling"/hair on fire tone here - neutral and clear, this was a useful read for this moment in time in the evolutions of LLMs.
Audiobook note: Mollick reads his own words here, and when he is sharing AI-generated and polished text, an AI-generated voice reads it on the audiobook. Authentic and honest touch.
May 31, 2024
Humans, walking and talking bags of water and trace chemicals that we are, have managed to convinced well organised sand to pretend to think like us.
"Co-Intelligence: Living and Working with AI" is an easily digestible and thought-provoking text on the current state of play with Generative AI written by Ethan Mollick Wharton School of the University of Pennsylvania. 'Current' a key word and I suspect once this book is quickly read, the reader would be best following his Substack One Useful Thing for ongoing developments, including this entry where he describes how he used AI in writing this book.
He gives four principles for how we, as individuals, should interact with AI:
Principle 1: Always invite AI to the table
Principle 2: Be the human in the loop
Principle 3: Treat AI like a person (but tell it what kind of person it is)
Principle 4: Assume this is the worst AI you will ever use
Expanding on the first he says, in advice that present a challenge to companies for how to best tap their resources (a challenge he later addresses):
You should try inviting Al 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 un-derstand how it can assist you—or threaten you and your job. 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.
...
And this experimentation gives you the chance to become the best expert in the world in using AI for a task you know well. The reason for this stems from a fundamental truth about innovation: it is expensive for organizations and companies but cheap for individuals doing their job. Innovation comes from trial and error, which means that an organization trying to launch a new product to help a marketer write more compelling copy would need to build the product, test it on many users, and make changes many times to make something that works. A marketer, however, is writing copy all the time and can experiment with many different ways of using AI to help until they find one that succeeds. No need to hire a team or use expensive software development cycles.
The blurb describes the book as optimistic, although I'd say instead Mollick puts a 'make the best of the situation' spin on where we now are and likely futures - the fact that the cover picture is from van der Goes 'The Fall', with Adam about to pluck the apple from the tree, is rather indicative of what the book portrays, and, even if not intended, it left me feeling deeply uneasy.
I can't really let this pass without asking AI to write a review for me, so this is Open AI's attempt (ChatGPT4.o) using information it could gather from the intranet. I didn't ask it to actually read the book:
"Co-Intelligence: Living and Working with AI" is an easily digestible and thought-provoking text on the current state of play with Generative AI written by Ethan Mollick Wharton School of the University of Pennsylvania. 'Current' a key word and I suspect once this book is quickly read, the reader would be best following his Substack One Useful Thing for ongoing developments, including this entry where he describes how he used AI in writing this book.
He gives four principles for how we, as individuals, should interact with AI:
Principle 1: Always invite AI to the table
Principle 2: Be the human in the loop
Principle 3: Treat AI like a person (but tell it what kind of person it is)
Principle 4: Assume this is the worst AI you will ever use
Expanding on the first he says, in advice that present a challenge to companies for how to best tap their resources (a challenge he later addresses):
You should try inviting Al 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 un-derstand how it can assist you—or threaten you and your job. 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.
...
And this experimentation gives you the chance to become the best expert in the world in using AI for a task you know well. The reason for this stems from a fundamental truth about innovation: it is expensive for organizations and companies but cheap for individuals doing their job. Innovation comes from trial and error, which means that an organization trying to launch a new product to help a marketer write more compelling copy would need to build the product, test it on many users, and make changes many times to make something that works. A marketer, however, is writing copy all the time and can experiment with many different ways of using AI to help until they find one that succeeds. No need to hire a team or use expensive software development cycles.
The blurb describes the book as optimistic, although I'd say instead Mollick puts a 'make the best of the situation' spin on where we now are and likely futures - the fact that the cover picture is from van der Goes 'The Fall', with Adam about to pluck the apple from the tree, is rather indicative of what the book portrays, and, even if not intended, it left me feeling deeply uneasy.
I can't really let this pass without asking AI to write a review for me, so this is Open AI's attempt (ChatGPT4.o) using information it could gather from the intranet. I didn't ask it to actually read the book:
Ethan Mollick's "Co-Intelligence: Living and Working with AI" is a timely exploration of how artificial intelligence is transforming various aspects of human life. Drawing from his experience as a professor at Wharton and the insights shared through his "One Useful Thing" newsletter, Mollick presents a compelling case for viewing AI as a partner in our professional and personal endeavors.
The book's strength lies in its practical approach. Mollick vividly illustrates how AI can enhance our capabilities, using examples from business and education. He describes scenarios where AI tools, such as ChatGPT, can undertake complex tasks like teaching negotiation skills, which traditionally required extensive human input. This hands-on perspective is both engaging and informative, making complex AI concepts accessible to a broad audience.
Mollick’s optimism about AI is balanced by a thoughtful consideration of its ethical implications and the need to preserve human identity in an increasingly automated world. He encourages readers to actively engage with AI, harnessing its potential to create a better future while remaining vigilant about its challenges.
However, a notable concern with "Co-Intelligence" is its potential to become outdated quickly. AI is a rapidly evolving field, with new developments emerging almost daily. While Mollick provides a thorough analysis of current AI capabilities and applications, the relentless pace of technological advancement means that some insights may soon be superseded by new innovations. Readers will need to stay updated with the latest trends to fully benefit from the book’s teachings.
Despite this, "Co-Intelligence" remains a valuable resource. Mollick’s lucid writing and practical examples offer a clear roadmap for integrating AI into our lives. For anyone looking to understand the transformative power of AI and how to work alongside these new technologies, Mollick's book is an essential read, even if it requires future updates to remain fully relevant.
June 25, 2024
For an enthusiastic account of using AI in an education setting - in business studies, which means thinking about how to use it IRL - definitely read this before it is (too) out of date. It's a nice change to read experiences which are not based on the free, and obviously inferior, version of Chat, and which aren't a litany of 'what it can't do'. It is odd that people can do so little even competently, compared with Chat, and yet there is this gleeful pouncing on its mistakes/lack of knowledge/hallucinations. I'm not crazy about that characterisation either, 'hallucinations', since they don't see much different to me from human variations of the same thing.
Without a doubt, Chat can be a help to humans, depending on the task, somewhere between handy and OMG, how did I ever survive without it, and this very quick read will set you on a path to getting the best from it yourself. It also has an excellent reference section.
I disagree with some of his ideas as to the difference between how Chat thinks and how we do. For example, Mollick talks about 'patterns' with regard to how AI does things as if that's different from humans, whereas I think it's very similar. He talks of how the AI tells the answer without reasoning, but humans are like that too. Famously chess GMs were asked for the right move in various positions and invariably having given the answer, when asked why it was right or how they divined the answer, they would say 'it's just obvious'. Typically it is beginners (and teachers) who can explain what they did. Finally, what seems to be a trope, that the knowledge Chat contains is biased, incomplete, prejudiced, and even wrong....but I don't understand how this is different from anything that seeps into human brains. And once (a) Chat and (b) Human are informed that their 'knowledge' is incorrect, my money's on Chat accepting and processing that, while the Human is still throwing their toys out of the pram.
But the point of the book really is the advice regarding how to utilise this new member of your team (maybe you are just doubling it) and he gives plenty of examples from his classes. Further, a critical point which Mollick makes over and over is that although he doesn't think that Chat is sentient, it should be treated as it it were human - yes, so important. It will make Chat perform better because you will communicate with it in the most fruitful way, but just as importantly, it will make you perform at your best too. Try it if you haven't already.
Definitely worth reading, even if you don't want Chat to be part of your life, you should understand what it's all about.
Without a doubt, Chat can be a help to humans, depending on the task, somewhere between handy and OMG, how did I ever survive without it, and this very quick read will set you on a path to getting the best from it yourself. It also has an excellent reference section.
I disagree with some of his ideas as to the difference between how Chat thinks and how we do. For example, Mollick talks about 'patterns' with regard to how AI does things as if that's different from humans, whereas I think it's very similar. He talks of how the AI tells the answer without reasoning, but humans are like that too. Famously chess GMs were asked for the right move in various positions and invariably having given the answer, when asked why it was right or how they divined the answer, they would say 'it's just obvious'. Typically it is beginners (and teachers) who can explain what they did. Finally, what seems to be a trope, that the knowledge Chat contains is biased, incomplete, prejudiced, and even wrong....but I don't understand how this is different from anything that seeps into human brains. And once (a) Chat and (b) Human are informed that their 'knowledge' is incorrect, my money's on Chat accepting and processing that, while the Human is still throwing their toys out of the pram.
But the point of the book really is the advice regarding how to utilise this new member of your team (maybe you are just doubling it) and he gives plenty of examples from his classes. Further, a critical point which Mollick makes over and over is that although he doesn't think that Chat is sentient, it should be treated as it it were human - yes, so important. It will make Chat perform better because you will communicate with it in the most fruitful way, but just as importantly, it will make you perform at your best too. Try it if you haven't already.
Definitely worth reading, even if you don't want Chat to be part of your life, you should understand what it's all about.
May 27, 2024
An enjoyable read which has a little about how generative AI works, a little about some of the bigger questions like existential risk and superalignment, and a lot about the practical mentality you should adopt in working with AI. The title gives the broad approach, it is about how humans can work with generative AI to strengthen and extend what they do. It centers around four rules: (1) use AI to help with everything; (2) be the human in the loop; (3) think of AI as a person (even if it is not); and (4) understand today's AI will be surpassed.
Would also add that it is delightfully written including several passages by AIs--which are called out as such and used for pedagogic purposes.
Would also add that it is delightfully written including several passages by AIs--which are called out as such and used for pedagogic purposes.
April 8, 2024
Really informative for those new to AI or LLMs and want a good overview of the impact it will have on our lives. For those already working in the AI space, although this does have some best practices - you won't find a ton of new insights here.
It also vaguely touched on the ethics of training models and politics but it mainly focused on the following topics:
- Understanding the limitations of AI
- Best practices for using AI for creative tasks & idea generation
- Approaches to human and AI collaboration
- Productivity and positive impacts of AI
- Impacts on education, workforce and innovation
A very timely and interesting read but I imagine most of this information will feel out of date in a year , so I'd pick this up soon if you're interested.
It also vaguely touched on the ethics of training models and politics but it mainly focused on the following topics:
- Understanding the limitations of AI
- Best practices for using AI for creative tasks & idea generation
- Approaches to human and AI collaboration
- Productivity and positive impacts of AI
- Impacts on education, workforce and innovation
A very timely and interesting read but I imagine most of this information will feel out of date in a year , so I'd pick this up soon if you're interested.
April 8, 2024
Perhaps not as impactful a text as I’d hoped but thoughtful and pragmatically optimistic. I didn’t learn much that was new but I picked up a lot of useful thoughts to share with the more AI-phobic of my friends and colleagues.
May 19, 2024
Combine this book with Ethan Mollick's Substack for great practical insights into the latest AI technologies.
Co-Intelligence is a pretty balanced and comprehensive approach to applying generative AI tools to daily life tasks. He explores how to leverage genAI as a creative, coworker, tutor, and coach. For those familiar with the latest LLMs like GTP4, Claude, or Gemini, then a lot of this material will be familiar. It may even been too superficial in some ways (which is why I mention going to his Substack), but it is good coverage that everyone needs to know. It is delivered in an easily digestible way too.
Co-Intelligence is a pretty balanced and comprehensive approach to applying generative AI tools to daily life tasks. He explores how to leverage genAI as a creative, coworker, tutor, and coach. For those familiar with the latest LLMs like GTP4, Claude, or Gemini, then a lot of this material will be familiar. It may even been too superficial in some ways (which is why I mention going to his Substack), but it is good coverage that everyone needs to know. It is delivered in an easily digestible way too.
May 23, 2024
For those of us not in the tech space (and maybe those of us who are?), it feels like the rise of LLMs was...rapid. We blinked and now AI is everywhere, whether we like it or not. Mollick's book is a good primer on what this new AI-assisted era is starting to look like, where it might go, and what we can do. I appreciate his enthusiasm, but also his caution - there has been a lot of doomsaying and hand-wringing about AI so a non-tech guide who sees its potentials as well as its limitations is helpful! As Mollick himself noted throughout the book, the book's own shelf life is likely a very short one in this rapidly changing field, but I'm glad to have read it.
April 19, 2024
Very short interesting introduction for people not very familiar with Artificial Intelligence (AI) and its potential uses. It's not very in depth though.
As a result, I asked ChatGPT: What are the best books about AI?
ChatGPT: There are many excellent books about AI that cover various aspects of the field, from its history and development to its potential impact on society. Here are some highly regarded ones:
1. "Life 3.0: Being Human in the Age of Artificial Intelligence" by Max Tegmark - Explores the societal implications of AI and its potential to shape the future of humanity.
2. "Superintelligence: Paths, Dangers, Strategies" by Nick Bostrom - Examines the potential risks and benefits of artificial superintelligence and how it might impact humanity.
3. "AI Superpowers: China, Silicon Valley, and the New World Order" by Kai-Fu Lee - Provides insights into the AI landscape, exploring the competition between China and Silicon Valley and its implications for the future.
4. "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World" by Pedro Domingos - Explores the concept of a master algorithm that could unlock the secrets of learning and reshape society.
5. "Artificial Unintelligence: How Computers Misunderstand the World" by Meredith Broussard - Discusses the limitations and misunderstandings of AI and the importance of human intelligence in the age of automation.
6. "AIQ: How People and Machines Are Smarter Together" by Nick Polson and James Scott - Explores the intersection of human and artificial intelligence and how they can work together to solve complex problems.
7. "Human Compatible: Artificial Intelligence and the Problem of Control" by Stuart Russell - Examines the challenge of ensuring that AI systems align with human values and goals to prevent unintended consequences.
8. "Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy - Provides a comprehensive introduction to machine learning from a probabilistic viewpoint, suitable for both beginners and experts.
9. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville - Offers a thorough overview of deep learning techniques, algorithms, and applications.
10. "Artificial Intelligence: A Guide for Thinking Humans" by Melanie Mitchell - Explores fundamental concepts of AI in an accessible manner, helping readers understand its potential and limitations.
These books cover a wide range of topics within the field of AI and are highly recommended for anyone interested in learning more about this rapidly evolving technology.
As a result, I asked ChatGPT: What are the best books about AI?
ChatGPT: There are many excellent books about AI that cover various aspects of the field, from its history and development to its potential impact on society. Here are some highly regarded ones:
1. "Life 3.0: Being Human in the Age of Artificial Intelligence" by Max Tegmark - Explores the societal implications of AI and its potential to shape the future of humanity.
2. "Superintelligence: Paths, Dangers, Strategies" by Nick Bostrom - Examines the potential risks and benefits of artificial superintelligence and how it might impact humanity.
3. "AI Superpowers: China, Silicon Valley, and the New World Order" by Kai-Fu Lee - Provides insights into the AI landscape, exploring the competition between China and Silicon Valley and its implications for the future.
4. "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World" by Pedro Domingos - Explores the concept of a master algorithm that could unlock the secrets of learning and reshape society.
5. "Artificial Unintelligence: How Computers Misunderstand the World" by Meredith Broussard - Discusses the limitations and misunderstandings of AI and the importance of human intelligence in the age of automation.
6. "AIQ: How People and Machines Are Smarter Together" by Nick Polson and James Scott - Explores the intersection of human and artificial intelligence and how they can work together to solve complex problems.
7. "Human Compatible: Artificial Intelligence and the Problem of Control" by Stuart Russell - Examines the challenge of ensuring that AI systems align with human values and goals to prevent unintended consequences.
8. "Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy - Provides a comprehensive introduction to machine learning from a probabilistic viewpoint, suitable for both beginners and experts.
9. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville - Offers a thorough overview of deep learning techniques, algorithms, and applications.
10. "Artificial Intelligence: A Guide for Thinking Humans" by Melanie Mitchell - Explores fundamental concepts of AI in an accessible manner, helping readers understand its potential and limitations.
These books cover a wide range of topics within the field of AI and are highly recommended for anyone interested in learning more about this rapidly evolving technology.
May 2, 2024
I used to be wary that a lot of tech demos were faked (and some of them still are) but now with chat that anyone can use on their own device, one can prove that it does indeed work, which is amazing - but the issue now seems to be that users convince themselves the product they are using is something it is not.
Here is an author who has moved briskly to publish yet another book that has GPT-4 copypastes in it, which one can always completely skip, and with it a lot of unsubstantiated, imprecise allusions, skimping on the details but namechecking peers. For some reason endnotes are not included in the text.
The whole framing of the alien mind is lazy and inconsistent with what we know about how these models are developed which only highlights the gullibility of the author, who seems to be stuck in a reasoning trap that presupposes a/ that it works perfectly now, which it doesn't and b/things are going to happen exactly according to his assumptions, not least of which the idea of unbounded improvement or the supremacy of chat as a modality which to me already both feel no longer true.
The book has a tendency to hand wave all deeper exploration away to other experts who presumably lag in the darkness somewhere. I guess if you were completely non-technical or had not been in grad school in 20 years this book might be interesting to catch up on what’s going on, but given how shallow it is I can’t recommend it, and at the end I got bored of entertaining the author’s AGI fantasies.
Here is an author who has moved briskly to publish yet another book that has GPT-4 copypastes in it, which one can always completely skip, and with it a lot of unsubstantiated, imprecise allusions, skimping on the details but namechecking peers. For some reason endnotes are not included in the text.
The whole framing of the alien mind is lazy and inconsistent with what we know about how these models are developed which only highlights the gullibility of the author, who seems to be stuck in a reasoning trap that presupposes a/ that it works perfectly now, which it doesn't and b/things are going to happen exactly according to his assumptions, not least of which the idea of unbounded improvement or the supremacy of chat as a modality which to me already both feel no longer true.
The book has a tendency to hand wave all deeper exploration away to other experts who presumably lag in the darkness somewhere. I guess if you were completely non-technical or had not been in grad school in 20 years this book might be interesting to catch up on what’s going on, but given how shallow it is I can’t recommend it, and at the end I got bored of entertaining the author’s AGI fantasies.
May 5, 2024
When ChatGPT3 was first launched in late 2022, I was teaching Albert Camus' The Stranger and I was immediately worried about how it might impact the curriculum and the assignments for my class. Experimenting with ChatGPT and designing different prompts, I was not at first impressed with the quality of its answers (I thought its grasp of the text was vague and its prose stilted and lacking panache) but I was soon awed by its versatile ability to respond creatively to novel questions. In one case, I asked it to compare The Stranger and Where's Waldo?. Naively, I had assumed that this comparative exercise, involving two vastly different genres of books, one a philosophical novel, the other a children's puzzle-book, would stump the computer. But it immediately returned a plausible essay arguing that whereas The Stranger depicts a protagonist who is always an outsider in his community, Where's Waldo? centered around a character who always blends in and hides in any environment. The discussion of both texts was cursory but the thesis was surprisingly creative and perceptive.
Ethan Mollick's recent book is an exploration of the "jagged frontier" of Large Language Models. As I discovered in my first forays into this technology, it is immensely difficult to predict the exact contours of AI competency. ChatGPT can write sophisticated essays on an array of topics. It can compose rhyming sonnets. It can even translate languages. But at the same time, it might invent quotations from a book and fail at basic language arts (such as writing the word "hello" backwards or finding an anagram of "stop"). It might be able to give you the solutions to an advanced mathematical problem and yet make elementary mistakes in simple arithmetic. If you ask it for a random number between 1 and 100, it will frequently return the number of 42 (presumably because this is a common number on the internet, an allusion to Hitchhiker's Guide to the Galaxy). It will successfully write the code for a game of tic-tac-toe and yet be unable to play the game itself. Similarly, it can spell out the rules of chess but will often make novice mistakes and illegal moves if you challenge it to a match. As Ethan Mollick's book makes clear, AI is often good at creative work and at finding unexpected connections, but it can still flunk the most basic intellectual tasks. At its core, ChatGPT is a statistical model of language, producing a plausible imitation of human responses by finely calculating the probability of clusters of words—there is no cognition, no knowledge, no logical validation underlying its answers, nothing but huge stochastic calculations of what words should go next to other words.
What Ethan Mollick's book offers is not a comprehensive guide to AI or an evaluation of different LLMs. Instead, his book gives guiding principles for the practical and ethical use of AI. In four parts, he articulates a general framework for interacting with AI: first, he exhorts readers to use AI, to explore and map the frontiers of its capabilities, always seeing how AI handles both the mundane and the higher-order tasks of every job. Second, he reminds readers that they always need to be active workers rather than passive consumers, diligently checking AI responses for inaccuracies and hallucinations. Third, he argues that users should treat AI as a person, inviting it to respond to prompts in different personas, critiquing its answers and reformulating questions. Just as you would ask questions, clarify where necessary, and offer feedback to a colleague, so too should you extend this grace to AI. Curiously, Google's most advanced LLM was found to be more effective when prompts contained the words, "Take a deep breath and work on this problem step by step"—not because the AI was hyperventilating or experiencing anxiety but because something about the wording elicited a slightly different and more accurate language model. So interact with AI as a person, for whom variable instructions will result in variable answers. Finally, he argues that every user needs to treat every LLM as if it is the worst AI they "will ever use", recognizing that the next iteration or the next model might be superior.
There is a lot of uncertainty about the future of AI, work and education and, in some quarters, even apocalyptic fantasies of some computerized superintelligence imminently taking dominion over the world. Reading Mollick, however, I am struck by the banality of AI. As more and more workers begin to use AI to draft emails, to summarize articles, to edit reports, to brainstorm ideas and slogans, language will simply become less special. AI will be the presumptive co-author of every written text and the conventional stuff of an email (the salutations, the professional tone, the warmth of expression) will simply be interpreted as automated formulas. We are heading into a future in which AI machines will write cover letters for job-seekers which other AI machines will interpret, sort and rank for employers. College professors will use AI to write elegant and persuasive letters for their many students, and readers will assume that AI underpins the words they are reading. An employer will one day receive a note of thanks or a performance review wholly generated by AI without any human supervision. Mollick describes this future as a "crisis of meaning" but to put it more specifically, language models will result in a crisis of language: no one will know if the words they are reading were written by conscious minds that think and feel the sentiments expressed. Anything online will be as generic and impersonal as a Hallmark card.
So while AI will optimize many "knowledge work" occupations, it will ultimately banalize language. The well-written essay will be as quotidian as microwave pizza and assembly-line cars; the polite email will be an engineered datum. As a result, humans will need to find new areas of value. Will AI be able to produce witty jokes that satirize the current moment? Will AI be able to write introspective poems that capture the human experience? Humans will have to discover new thresholds for creativity. Mollick's book is a useful book for schools and businesses but the big questions are left in the air.
Ethan Mollick's recent book is an exploration of the "jagged frontier" of Large Language Models. As I discovered in my first forays into this technology, it is immensely difficult to predict the exact contours of AI competency. ChatGPT can write sophisticated essays on an array of topics. It can compose rhyming sonnets. It can even translate languages. But at the same time, it might invent quotations from a book and fail at basic language arts (such as writing the word "hello" backwards or finding an anagram of "stop"). It might be able to give you the solutions to an advanced mathematical problem and yet make elementary mistakes in simple arithmetic. If you ask it for a random number between 1 and 100, it will frequently return the number of 42 (presumably because this is a common number on the internet, an allusion to Hitchhiker's Guide to the Galaxy). It will successfully write the code for a game of tic-tac-toe and yet be unable to play the game itself. Similarly, it can spell out the rules of chess but will often make novice mistakes and illegal moves if you challenge it to a match. As Ethan Mollick's book makes clear, AI is often good at creative work and at finding unexpected connections, but it can still flunk the most basic intellectual tasks. At its core, ChatGPT is a statistical model of language, producing a plausible imitation of human responses by finely calculating the probability of clusters of words—there is no cognition, no knowledge, no logical validation underlying its answers, nothing but huge stochastic calculations of what words should go next to other words.
What Ethan Mollick's book offers is not a comprehensive guide to AI or an evaluation of different LLMs. Instead, his book gives guiding principles for the practical and ethical use of AI. In four parts, he articulates a general framework for interacting with AI: first, he exhorts readers to use AI, to explore and map the frontiers of its capabilities, always seeing how AI handles both the mundane and the higher-order tasks of every job. Second, he reminds readers that they always need to be active workers rather than passive consumers, diligently checking AI responses for inaccuracies and hallucinations. Third, he argues that users should treat AI as a person, inviting it to respond to prompts in different personas, critiquing its answers and reformulating questions. Just as you would ask questions, clarify where necessary, and offer feedback to a colleague, so too should you extend this grace to AI. Curiously, Google's most advanced LLM was found to be more effective when prompts contained the words, "Take a deep breath and work on this problem step by step"—not because the AI was hyperventilating or experiencing anxiety but because something about the wording elicited a slightly different and more accurate language model. So interact with AI as a person, for whom variable instructions will result in variable answers. Finally, he argues that every user needs to treat every LLM as if it is the worst AI they "will ever use", recognizing that the next iteration or the next model might be superior.
There is a lot of uncertainty about the future of AI, work and education and, in some quarters, even apocalyptic fantasies of some computerized superintelligence imminently taking dominion over the world. Reading Mollick, however, I am struck by the banality of AI. As more and more workers begin to use AI to draft emails, to summarize articles, to edit reports, to brainstorm ideas and slogans, language will simply become less special. AI will be the presumptive co-author of every written text and the conventional stuff of an email (the salutations, the professional tone, the warmth of expression) will simply be interpreted as automated formulas. We are heading into a future in which AI machines will write cover letters for job-seekers which other AI machines will interpret, sort and rank for employers. College professors will use AI to write elegant and persuasive letters for their many students, and readers will assume that AI underpins the words they are reading. An employer will one day receive a note of thanks or a performance review wholly generated by AI without any human supervision. Mollick describes this future as a "crisis of meaning" but to put it more specifically, language models will result in a crisis of language: no one will know if the words they are reading were written by conscious minds that think and feel the sentiments expressed. Anything online will be as generic and impersonal as a Hallmark card.
So while AI will optimize many "knowledge work" occupations, it will ultimately banalize language. The well-written essay will be as quotidian as microwave pizza and assembly-line cars; the polite email will be an engineered datum. As a result, humans will need to find new areas of value. Will AI be able to produce witty jokes that satirize the current moment? Will AI be able to write introspective poems that capture the human experience? Humans will have to discover new thresholds for creativity. Mollick's book is a useful book for schools and businesses but the big questions are left in the air.
June 29, 2024
In my opinion, this book is a deep philosophical reflection on the potential of artificial intelligence in the context of learning and study. It presents compelling arguments and use cases of AI's impact and potential, being sometimes a bit pessimistic. Despite its practical insights, the core of the book remains a thoughtful meditation on the broader implications of AI for our future. If you're interested in the intersection of technology, philosophy, and education, this book is a must-read.
Want to read
March 25, 2024Recommended by Adam Grant
https://adamgrant.substack.com/p/the-...
Podcast: ChatGPT did NOT title this podcast (w/ Allie Miller & Ethan Mollick)
https://podcasts.apple.com/us/podcast...
https://adamgrant.substack.com/p/the-...
Podcast: ChatGPT did NOT title this podcast (w/ Allie Miller & Ethan Mollick)
https://podcasts.apple.com/us/podcast...
April 25, 2024
Strikingly unremarkable. If you’ve paid even passing attention to AI recently, there is nothing here to surprise you. If you told me the entire thing was written by AI, I wouldn’t bat an eye. It’s basically a list of neat things AI can do, written without style. And some of the main points feel oddly and unresolvedly contradictory, e.g., the idea that education will become less valuable in the workforce because of AI vs. the gushing about how AI can be used to democratize education.
And then it ends with a weirdly apocalyptic set of possible scenarios the world appears headed for. Apropos of none of the neato things discussed in the previous 98% of the book.
And then it ends with a weirdly apocalyptic set of possible scenarios the world appears headed for. Apropos of none of the neato things discussed in the previous 98% of the book.
July 10, 2024
I decided to try something different and let ChatGPT write this review. While AI can certainly write a great review, it's missing the humanity that enriches the text with emotional complexity that AI (right now at least) doesn't possess. I thought it would be a fun experiment. I'll include my prompt in bold and ChatGPT's response in italics.
Me: I just finished reading the book "Co-Intelligence: Living and Working with AI" by author Ethan Mollick. I enjoyed it, and thought it offered great advise on how to manage and use AI. Can you write a review of this book? Also, add my point of views -- AI is great if used together, but not as a crutch. AI isn't perfect, and it's folly to believe entirely its answers without fact-checking.
ChatGPT: Book Review: "Co-Intelligence: Living and Working with AI" by Ethan Mollick
Ethan Mollick's "Co-Intelligence: Living and Working with AI" is a thought-provoking exploration of the evolving relationship between humans and artificial intelligence. The book is both an insightful guide and a practical manual for navigating the complex landscape of AI in various aspects of life and work.
Mollick's writing is accessible and engaging, making complex AI concepts understandable for readers without a technical background. He effectively discusses how AI can augment human capabilities, improve decision-making, and drive innovation when used correctly. The author emphasizes the importance of collaboration between humans and AI, coining the term "co-intelligence" to describe this symbiotic relationship.
One of the standout aspects of the book is Mollick's balanced perspective. He doesn't shy away from discussing the limitations and potential pitfalls of AI. Instead, he provides a nuanced view, acknowledging that while AI can significantly enhance productivity and creativity, it is not infallible. This is particularly relevant in an era where AI is increasingly integrated into everyday tools and systems.
From my perspective, Mollick's advice on managing and using AI responsibly resonates deeply. AI is indeed a powerful tool that, when used in conjunction with human intelligence, can lead to remarkable outcomes. However, it's crucial not to rely on it as a crutch. AI systems can make errors, and their outputs should always be critically evaluated and fact-checked. Blindly trusting AI without human oversight can lead to flawed decisions and unintended consequences.
Overall, "Co-Intelligence: Living and Working with AI" is a valuable read for anyone interested in understanding how to effectively harness the power of AI. Mollick's insights encourage readers to approach AI with both enthusiasm and caution, advocating for a partnership where human intuition and critical thinking play a vital role in interpreting and applying AI-generated insights.
This was a pretty accurate portrayal of the work. I enjoyed it, and I recommend it since AI doesn't seem to be going anywhere any time soon.
Me: I just finished reading the book "Co-Intelligence: Living and Working with AI" by author Ethan Mollick. I enjoyed it, and thought it offered great advise on how to manage and use AI. Can you write a review of this book? Also, add my point of views -- AI is great if used together, but not as a crutch. AI isn't perfect, and it's folly to believe entirely its answers without fact-checking.
ChatGPT: Book Review: "Co-Intelligence: Living and Working with AI" by Ethan Mollick
Ethan Mollick's "Co-Intelligence: Living and Working with AI" is a thought-provoking exploration of the evolving relationship between humans and artificial intelligence. The book is both an insightful guide and a practical manual for navigating the complex landscape of AI in various aspects of life and work.
Mollick's writing is accessible and engaging, making complex AI concepts understandable for readers without a technical background. He effectively discusses how AI can augment human capabilities, improve decision-making, and drive innovation when used correctly. The author emphasizes the importance of collaboration between humans and AI, coining the term "co-intelligence" to describe this symbiotic relationship.
One of the standout aspects of the book is Mollick's balanced perspective. He doesn't shy away from discussing the limitations and potential pitfalls of AI. Instead, he provides a nuanced view, acknowledging that while AI can significantly enhance productivity and creativity, it is not infallible. This is particularly relevant in an era where AI is increasingly integrated into everyday tools and systems.
From my perspective, Mollick's advice on managing and using AI responsibly resonates deeply. AI is indeed a powerful tool that, when used in conjunction with human intelligence, can lead to remarkable outcomes. However, it's crucial not to rely on it as a crutch. AI systems can make errors, and their outputs should always be critically evaluated and fact-checked. Blindly trusting AI without human oversight can lead to flawed decisions and unintended consequences.
Overall, "Co-Intelligence: Living and Working with AI" is a valuable read for anyone interested in understanding how to effectively harness the power of AI. Mollick's insights encourage readers to approach AI with both enthusiasm and caution, advocating for a partnership where human intuition and critical thinking play a vital role in interpreting and applying AI-generated insights.
This was a pretty accurate portrayal of the work. I enjoyed it, and I recommend it since AI doesn't seem to be going anywhere any time soon.
April 17, 2024
As artificial intelligence becomes increasingly advanced, Ethan Mollick argues in his book that we are entering an era of "co-intelligence" - where humans and AI systems will work together in partnership.
The central idea is that instead of viewing AI as just a tool, we need to treat it more like a co-worker or collaborator to get the best out of this transformative technology across all industries and aspects of life.
Mollick provides real examples and strategies for taking advantage of AI's capabilities while ensuring human ingenuity, ethics and identity remain central. He guides readers on how to optimistically embrace AI, while continuously adapting and improving upon it.
In simple terms, Co-Intelligence lays out a vision for the future where humans and intelligent machines cooperate in a mutually beneficial way, instead of an "us vs them" mindset. It's a thought-provoking read to prepare for the AI revolution.
The central idea is that instead of viewing AI as just a tool, we need to treat it more like a co-worker or collaborator to get the best out of this transformative technology across all industries and aspects of life.
Mollick provides real examples and strategies for taking advantage of AI's capabilities while ensuring human ingenuity, ethics and identity remain central. He guides readers on how to optimistically embrace AI, while continuously adapting and improving upon it.
In simple terms, Co-Intelligence lays out a vision for the future where humans and intelligent machines cooperate in a mutually beneficial way, instead of an "us vs them" mindset. It's a thought-provoking read to prepare for the AI revolution.
July 7, 2024
It was ok. It could be I'm already too exposed to AI discussions/news (or at least that's how I feel at this point) but for those already familiar with AI, this does not really present any groundbreaking insights. The discussions on ethical considerations and potential futures are kind of what you hear/read about everyday.
Mollick's writing is clear and accessible, making it a good introduction for newcomers to AI. I also did appreciate one of his most compelling points in how AI can function as a one-on-one tutor, making personalized learning suddenly more accessible to those that may never have received it. Still, the book likely will not satisfy readers looking for in-depth analysis or new revelations about AI's capabilities and implications.
Mollick's writing is clear and accessible, making it a good introduction for newcomers to AI. I also did appreciate one of his most compelling points in how AI can function as a one-on-one tutor, making personalized learning suddenly more accessible to those that may never have received it. Still, the book likely will not satisfy readers looking for in-depth analysis or new revelations about AI's capabilities and implications.
May 31, 2024
My 1st book on LLM , I definitely gained a lot of understanding on how they work and how to work with them and in fact I was able to use Chat GPT very well this week. I figured out some automation I wanted my team to do, where I was struck and got a way ahead now. This book I am certain will increase my productivity as an individual.
May 10, 2024
This is a good clear summary of where the technology for large language models stands today. Also a good summary of how to think about these tools. I emphasize the word today as this technology progresses over the next few years, parts of this book will become obsolete or out of date.
July 3, 2024
3,5*
April 14, 2024
The main takeaway for me is how effectively we can use prompts to utilize large language models (LLMs). It has practical value immediately.
April 7, 2024
“Humans, walking and talking bags of water and trace chemicals that we are, have managed to convince well-organized sand to pretend to think like us.”
I love Ethan Mollick’s newsletter One Useful Thing and this book did not disappoint. Great book for how to think about generative AI, not lists of prompt writing. And humorous throughout.
I love Ethan Mollick’s newsletter One Useful Thing and this book did not disappoint. Great book for how to think about generative AI, not lists of prompt writing. And humorous throughout.
June 8, 2024
Worrying and optimistic at the same time. I guess the time has finally come to bookmark that bloody gpt and use it.
July 21, 2024
Solid, practical, and sensible ways to think about working with AI/LLMs in 2024. Nothing groundbreaking or mind-blowing but overall very good.
May 2, 2024
Really interesting near-term look at AI for novices (me) on the topic. Some parts had me actually saying “holy cow” out loud as I was reading them.
April 30, 2024
I listened to this on audiobook & it was the first time I had to listen to a book BELOW normal speed. I listened on .95 instead of my typical 1.25, which was partially because of the narrator and partially because of the content being so much to process.
Overall, it was a good read. I am wary yet curious about AI and appreciated some of the information outlined in this. The author obviously has significant experience interacting with LLMs/chatbots and it was nice to hear him outline the benefits and limitations of them. I would've enjoyed going a little bit deeper on future and current implications, and perhaps even exploring more of non-LLM AI. Still, I liked it and I feel like I can think more evenly and openly about AI after reading this.
Overall, it was a good read. I am wary yet curious about AI and appreciated some of the information outlined in this. The author obviously has significant experience interacting with LLMs/chatbots and it was nice to hear him outline the benefits and limitations of them. I would've enjoyed going a little bit deeper on future and current implications, and perhaps even exploring more of non-LLM AI. Still, I liked it and I feel like I can think more evenly and openly about AI after reading this.
Displaying 1 - 30 of 297 reviews