Co-Intelligence: Living and Working with AI Hardcover – April 2, 2024

The first half is more destined to those who have yet to use generative AI on a regular basis – in all probability a shrinking crowd. Anyone who interacted with ChatGPT 3.5 and then 4 will have similar anecdotes. And while certainly useful, I found Ethan’s four principles to mix rules of thumb with prompting techniques and more general observations.Part two I personally found of much greater interest, as Ethan delves into the implications for workers, demonstrating how they can learn to use AI to great effect, e.g. in creative work. Ethan dives deep into how gen-AI can produce efficiencies and superior results, but also lead to disaster if users get too comfy and “fall asleep at the wheel”. While several studies and research papers exist on these topics, it’s one of the first books that explains these concepts to laymen. It’s also enjoying to see him, rather than trying to dissect office jobs he may not be familiar with, instead humbly take himself as a guinea pig to explain in great minutiae how he wields this revolutionary tool in his work, at times using the very paragraphs we read as examples.I found in several occasions echoes of my own book, e.g. when Ethan insists on how technology cannot be treated in a vat but goes hand in hand with frameworks and trends, thus how the way corporations have work organized is likely to change in serious ways, as it did in previous industrial revolutions. He too does not fall for the fallacy that because certain tasks in a job cannot be automated, the job is immune to disruption. He too notes the risks associated with a greater deployment of metrics and the diktat of data, what others have called “Digital Taylorism”, and alludes to what I termed being “pushed off of the sumo ring of cognition” by an AI that calls the shots.He also takes a lucid and pragmatic approach to how such disruptive technology will be deployed in the workforce, detailing how employees use it covertly out of fear that their managers find out, though less convincing are his recommendations to leaders on how to instill a pro Gen-AI culture in the company – a pity given how this is fast becoming a concern for managers. A few other considerations also went neglected, like how those companies that fail to adapt will quickly fall behind those that do. But I feel this is also because he is primarily addressing employees, and that is nice to see in contrast to all the books guiding managers.My favorite is his insistence that AI is proving most beneficial to juniors, who can boost their performance level to the vicinity of veterans; rather than concluding in the lines that “See, this is a great enhancement tool, not something that will eliminate jobs - so don't be afraid!”, or “it’s not AI that will displace workers, but the workers who master AI that will displace those who don’t” as the majority of so-called experts yell and parrot from every hilltop, he questions what implications this might have for seasoned workers, for those whose expertise becomes somewhat eroded and may no longer justify their wages. Following what I called the commoditization effect, AI could become a great equalizer, but (Duh!!) overall this will drag wages down. He notes how now some companies hire fresh graduates for jobs there where they used to hire people with at least five years of experience, because they can do practically just as well now with the help of AI.Alas he also rightly note that expertise will still play a role, with solid arguments. But he dares not venture say how much of this expertise will still be required and how this will reshape companies - indeed, only time will tell. We could end up with a split of say 80% of juniors – or rather people paid with junior salaries – and only 20% of experts there where we had a more balanced split before, and such junior talent could be outsourced instead of employed, etc.I pass on the final chapters on education and the future of AI, not for lack of interest but to avoid too long a commentary. Also great observations, for instance on how a future AI-mentor would be superior both for providing more constant feedback but also in its ability to take on several different roles (as opposed to the subjectivity of a single human coach, teacher or mentor). And here again there is the risk of overdependence, for instance (with his example of architect) consulting the AI on every single stroke.All in all, a very good read that remains concise and echoes some of my concerns which I believe will only balloon with time as organizations reshape work.

Just finished reading Co-Intelligence by Ethan Mollick. In many ways it is an introductory 'primer' on AI (artificial intelligence).Written by Ethan Mollick, a professor at Wharton, it explores what AI is, how we can utilize is as a 'co-intelligence' and what the future might look like with AI.As someone who has used ChatGPT and other tools, but did not have much understanding of how they work, the book provided that background. On the other hand, I found it lacking in the depth and creativity I hoped for in exploring what a future world with AI might look like.Some insights from the book:- AI is built on Large-Language Models (LLM's). These models have huge datasets at their core. By using this information, it can generate responses by predicting (and displaying) the word that is most likely to come next as a response to a prompt (and as a response to what it has already generated. The association between words are called 'weights' and these are adjusted based on the frequency and association between terms (if I have understood this correctly.)- Because of the way that LLM's are built, the biases that we have as humans will get translated into AI. AI tools have a stage called Reinforced Learning from Human Feedback (RLHF) which is a process by which humans look to remove the bias. (Of course, this introduces another source of bias, but is important in ensuring that AI does not become a mirror of the uglier parts of ourselves which often manifest online and in other places which may be sources of data for AI.)- This process means that unlike other areas of technological development, AI finds it harder to be consistent and structured and instead seems to be actively creative. An analogy which is not found in a book, but which seems apropos was the shift in computer graphics from Euclidian Geometry to Fractal Geometry as the basis of graphics.- Mollick notes that the nature of AI makes it extremely difficult to predict exactly what it will be great at and what it will not. It also means that AI will include mistakes and fabrications without any self-awareness that it is doing so.- Mollick believes we are better for 'inviting AI to the table' while maintaining human involvement (you can get great results by working with AI, and poorer results [at least today] from handing over tasks to AI without oversight. He recommends viewing AI as a person in the sense that AI will be quirky and unpredictable. He also notes that whatever AI you are using today will likely be the worse than any version you ever use in the future as the technology continues to develop.- In the book Mollick shows how to use AI (engage with it, provide it with specific instructions "Give me a Mexican recipe that takes under 20 minutes to make using ingredients X, Y and Z [items in my fridge] and can be done by a 12 year-old without any instruments that would potentially be dangerous [like blender's etc]." He recommends breaking down problems into steps (a process you can ask AI to assist etc.)- Mollick is generally pretty optimistic about AI. He points to studies that show that it helps people who struggle in areas to elevate themselves and believes it may help resolve income inequality etc.- Mollick mentions, but in my opinion does not give enough attention to potential issues. He notes that people often hand off tasks to AI without engaging mentally and we are in real trouble if we take another step back in critical thinking (in my opinion). He does not focus on the ways that AI could easily exacerbate income inequality as those with money put guardrails around the best tools etc. He also does give almost any focus on the way that AI can spit out endless content in little time and in the hands of bad actors, can take our current issues with fakenews, and make it 1000x worse very quickly.- Mollick notes that practical changes occur within systems and the changes we are talking about need to contend with the structures (economic, social, political etc) which currently exist. This reminds me of Kuhn's descriptions of changes and the slow pace of the Copernican Revolution, in part because it bumped into theological systems.- As I noted above, I felt like Mollick did not spend nearly enough time exploring the issues that could easily arise from AI. What happens in a world where there is endless content being generated and no clarity on the legitimacy of it? Does it lead to additional conflict? How does it play a role in elections, campaigns etc.? Is additional government regulation generated to crack down? A social media platform exclusive to non-AI where you have to validate everything you are writing (somehow)? Influencers with "Real Human - no AI content" badges? What about Human-Reviewed AI Content? Is there a reason that is a bad thing?All in all, I think that AI is likely to have a dramatic impact on the world of the future. This book is a good intro. In all likelihood large aspects of it will become outdated rather quickly. And I wish it had done some more deep thinking about the future. It feels like just a shallow exploration.

"Co-Intelligence: Living and Working with AI" offers a really insightful look into navigating the evolving landscape of artificial intelligence. The book does a great job of moving beyond the typical hype or fear, instead focusing on how we can effectively collaborate with AI to enhance our work and lives. It's thought-provoking and practical, providing a balanced perspective on integrating AI into our daily routines. If you're looking for a grounded and optimistic guide to the future of human-AI partnership, this is definitely worth a read.

Thank you, Doctor Ethan Mollick.I only wish I had read this book 2 years ago when it first published. Nonetheless, I feel jettisoned in my understanding and thrilled to use AI as co-intelligence into my future. Thank you.(no AI was used in this review)

I have gotten a few AI books - this is the one that I listened to from start to finish. It was exactly what I wanted - a book that I could read/listen to and finish with the sense that I know the basics of AI as a technology, its place in the world right now, and have a leg up on most. I found myself mentioning the book and the information several times in conversation as my own company sets AI policy.

Multiple informations and advices useful in 2025 how to work with Ai. I think, however just few of ideas in this book is universally useful for communicating with computer system and virtual world intelligent being in near future. 4 stars for good writing and knowledge for now. I expected more visionary approach to future of ai. Rapid development of ai will make the content of this book outdated very soon in my opinion.