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Rebooting AI: Building Artificial Intelligence We Can Trust

3.89  ·  Rating details ·  415 ratings  ·  68 reviews
Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust AI.

Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we are led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the foref
Hardcover, 288 pages
Published September 10th 2019 by Pantheon Books
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Aug 04, 2019 rated it liked it
Shelves: non-fiction, tech
The central thesis of this book is that AI is not good enough. It is much closer to basic statistical inference than something that understands the world like a human. However, this is really all the authors needed. A short OpEd would be just as valuable as writing a 200-page book.

They have a lot of examples, which do advance their point, but it makes the writing feel repetitive. Yes, AI today cannot understand the implied points of a sentence. However, they then end up providing a bunch of simi
Dec 06, 2019 rated it it was amazing
I've read a lot of books on AI and the future of tech and economics in general and this is by far the most mature and sober. It's not a downer like some of the books that are all "everything that is capitalism is bad" but it's also not a breathless "AI and tech will save us and change everything." AI is really good at a few things--like playing Go, Jeopardy, finding facts, sorting, etc etc. But it's really bad at all the things that humans basically learn by the time they turn 5--like common sen ...more
Nestor Rychtyckyj
Nov 11, 2019 rated it it was amazing
This well-written and very accessible book by Gary Marcus and Ernest Davis should be required reading for anybody that is overwhelmed by the current boom (and hype) in Artificial Intelligence (AI). For most people - the term AI is referring exclusively to Deep Learning and ignoring all of the other significant work that is going on in the area. When every product from golf clubs to vacuum cleaners is now advertised as being “powered by AI”, perhaps it’s time to step back and take a look at where ...more
Nov 13, 2019 rated it liked it
Shelves: non-fiction
The first part of this book, covering the limits of current AI research, was quite solid. The number of examples might be a bit excessive, but it helped show me that I've fallen victim to the tendency to make assumptions about rates of progress. The book was worth it for this part.

Unfortunately, the book doesn't have much to offer in terms of solutions despite spending a large number of pages on it. There's no point in saying that AI would be better if we could solve extremely complex problems,
Harsha Kokel
Aug 08, 2020 rated it really liked it
Shelves: recommend
This book is written for lay audience who tend to get carried away by impressive headlines. It is a tale of caution to not get excited by the current progress in AI and communicate the research at its scale; not make an exorbitant story out of it. This is important. Not only news articles but even research paper titles have seen a trend to make bold statements, but proving very little. So this book is a great reminder to call a spade a spade.

However, I think the tone of the book is a little sni
Aug 07, 2020 rated it liked it

The book is aimed at an audience of readers who are fascinated by the possibilities of AI but who are not technicians in the field. With this book, this reader is able not to be uninformed when reading blog articles on the subject.
The main point is that nowadays IA is not robust (i.e. it cannot be predicted when and to what extent it will go wrong) and for safety and security reasons it cannot be used in all areas (such as driving a car).


The authors analyze the state of the art of A
This is a nice, fairly short, introduction to the current limits to deep learning and AI. The authors point out how to watch for hype, explain where we actually are currently, and give suggestions on how we should approach making general AIs rather than the narrow AIs we currently have.

As somewhat of a skeptic when it comes to AI as it is now (I wouldn't trust a self-driving car right now), it is nice to see a comprehensive accounting for the problems AI now has while still acknowledging the ama
Yunke Xiang
Jan 06, 2020 rated it really liked it
This book tries to argue that we need some paradigm change for the current AI development. Instead of building machines that’s primarily fueled by big data and can handle specific tasks, we should have bolder vision and action and design machines that actually understands the world (have common sense, capable of reasoning).

The book has offered a lot of examples on where current AI long on promise but short on delivery. I enjoyed reading it because these are all most up to date examples from the
Kiwi Begs2Differ  ✎
Disappointed by this book. Besides stating the obvious, it barely scratches the surface of the AI topic. If you have a good understanding of the subject and have read a few recent technical articles you are not likely to learn much new.

The authors highlight the limits of current AI research and development (predominantly based on deep learning) but they hardly add anything of value in terms of the direction that AI development should go instead. What this book proposes is a long term goal/vision
Filip Ilievski
May 24, 2020 rated it it was amazing
Brilliant storytelling and a balanced view of today's AI. As an AI researcher, this book was very suitable for me, though I expect it to be easy to follow by laymen too. I especially enjoyed the many examples throughout the book. The writing could be more compact, but I can leave with that
Sep 02, 2020 rated it really liked it
Naturally I broadly agree with the call for symbolic knowledge representation, allowing mechanical reasoning, to be brought (back) to bear in combination with deep learning, which is inherently limited in statistical approximation of intelligence.
Tom Satterthwaite
Feb 18, 2020 rated it really liked it
Provides great insight into the state of AI, how far it has come and how far it still has to go to attain the current levels of hype.
Ricardo Acuña
Nov 10, 2019 rated it really liked it  ·  review of another edition
Throughout the history, there are generally cycles that oscillate between the extremes of two dialectically opposed positions resulting in a new stage in the historical development of contraries. REBOOTING AI analyzes the current hype of the AI, and especially the "Deep Learning". The AI has reached such a point that it covers a good part of startup investments, technological developments, new products, and even politics. REBOOTING AI on this sense analyzes this current AI hype emphasizing that ...more
Oct 13, 2019 rated it it was ok
Christopher Flesher
Oct 29, 2019 rated it it was ok
Just a bunch of complaints
Oct 14, 2020 rated it liked it
(Spoiler free part)

The title is more telling than I first thought. The book is really about rebooting AI efforts, implying reconsidering 60 years of AI, and correcting the arguably poor direction of the Deep Learning-focused field/industry now. The authors do a very good job, going all the way back to the beginning of AI, presenting compelling arguments from their areas of expertise, and venturing in other key areas. The whole is to me restricted and biased, yet solid and constructive. Restricti
Becky B
Apr 15, 2020 rated it really liked it
Shelves: nonfiction, science
A realistic look at the current abilities and limitations of modern AI and the author's suggestions about what needs to happen in order to get AI to the place where it could take care of household chores or put Grandpa to bed without calamity.

This was a good dose of reality to combat all the bells and whistles that AI makers throw at you in press releases. AI is nowhere near understanding language, it is lightyears away from any common sense, and the fact that search results or voice recognition
Derek Bridge
Mar 28, 2020 rated it really liked it
This book starts off as a good appraisal of the state-of-play in AI, especially the limitations of deep learning (which is the current in-vogue version of subsymbolic AI). The book is very clear about what deep learning is lacking, in particular representations of relational knowledge (especially common-sense knowledge ) and (relatedly) compositionality. The book acknowledges too that "classical AI" (symbolic AI) is brittle. So, the diagnosis is good. But there are two problems.

First is that the
Feb 05, 2020 rated it liked it
Shelves: science
Humans have been trying to make computers that think at least since the 1950s and during that time I think it's fair to say that there have been two main camps:

(1) A group that feels it is important to develop systems with a solid philosophical, mathematical and scientific foundation, in such a way that we understand what they are doing, why they are doing it, and whether what they are doing truly constitutes "intelligence."

(2) A group that feels it is more important to first develop systems tha
Oct 05, 2020 rated it liked it
Argues (repetitively) that "AI is, by and large, on the wrong path with the majority of current efforts devoted to building comparatively unintelligent machines that perform narrow tasks and rely primarily on big data rather than on what we call deep understanding."

The problem is that we've relied too much on deep learning which, “just ain’t that deep” - it is generally good at perceptual tasks (provided it has been trained on massive data sets similar to the test cases) but it has no understand
Frederick Gault
Oct 07, 2019 rated it liked it
Shelves: nonfiction, science
This book is long on examples of what current "AI" based systems don't do properly. The authors contend that the current approach, neural net based deep learning based on big data, is only part of the problem space facing commercial AI based products. They would like to see more "common sense", among other things. They freely admit that right now no one seems to know how to do common sense and in fact most research is focused on the current approach. In their opinion, current research is erroneo ...more
I received a finished copy from the publisher via a friend, with no expectation to leave a personal review.

This is a fun, accessible, and balanced approach to AI--which helpfully gives context for the nearly messianic claims newspapers so often provide about how AI is developing--from authors who, unexpectedly, are in favor of its further development. I didn't realize until I read the first chapter that that would be the case; I had just assumed that a title like this, despite the happy cover, w
Dec 28, 2019 rated it really liked it
The book reflects a belief I've been having for some time now, mainly that we are currently barking up the wrong tree when it comes to AI.
We are making amazing tools, thats certain, but most people see the latest improvements in solving a very specific problem and extrapolate from that to believe we are close to having a general purpose AI, or True AI.

It compares classical AI with modern ML driven AI and talks about the strengths and weaknesses of both. Modern AI is amazing, but the flawed cla
Mar 08, 2020 rated it really liked it
Half read, half listened to.

This was a very interesting book that echoed so many of my views on current trends to use more machine learning in more and more applications. They reached a similar conclusion that ML will not be enough on it’s own, that something more is needed.

The start and middle of the book were great - fast paced, clear examples, sharp arguments and points. The final chapters were a lot more subdued and seemed to drag a bit. I understand that there are no solutions to these har
Adam Sherman
Feb 17, 2020 rated it it was amazing
I thought this was a very tempered look at AI from an intelligence perspective. Pointing out specific issues and problems that AI doesn't seem to be able to solve easily with current approaches. The necessity of instituting logic, moral values drawn from logic, and hard rules with probabilistic Bayesian and neural networks. Gary Marcus disagrees with many of the potential problems AI will cause in the upcoming future but lays out the more pragmatic and realistic ones as opposed to existential is ...more
Feb 20, 2020 rated it liked it
Pretty interesting read. Takes a skeptical approach about the current state of AI. The authors believe we are still a long way off from any sort of machine take over. The most repeated idea seemed to be the gap between human intelligence and machines is the development of common sense. Their arguments were persuasive, but they kept beating the drum so I found myself skimming from time to time.

I liked the Chapter about trust the most. Discussed Asimov's rules, why Bostroms paper clip example can
Prashant Singh
Mar 19, 2020 rated it really liked it
Shelves: 2020-books-read
A good book explains what current AI is capable of which is already quite impressive. It also points out how media and companies making AI are hyping minor incremental advances. This unnecessary hyping has also made people to have either unnecessary expectations ranging from a star trek world in a decade to terminator like ending where ai will take over humans. The book in my opinion is written well so as a non technical person who wishes to know current progress of ai in little detail.
I am imp
Oct 24, 2019 rated it liked it
Has its ups and downs, but overall very interesting

I kind of ruined it for me by reading some of the negative comments on here. Therefore, I cannot say if the first few chapters are really annoyingly pessimistic or the reviews have blown it out of proportion for me.

So yeah, the first few chapters are a bit tough to get through, but it gets better. The chapters on the technology behind deep learning and the limitations of current AI techniques were just deep enough for a layman. So yeah, overall
Adriel N.
Apr 13, 2020 rated it really liked it
Pretty accessible book that looks at the current, limited state of Artificial Intelligence and presents suggestions on how to improve the field in the future. This was my first foray into AI related literature and I found it engaging and thought provoking. The book fell apart a bit at the end by providing sweeping generalizations of where the field needs to go moving forward but, all in all, I enjoyed it and I would recommend to anyone who has some interest or general curiosity about Artificial ...more
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Gary Marcus is an award-wining Professor of Psychology at New York University and director of the NYU Center for Child Language. He has written three books about the origins and nature of the human mind, including Kluge (2008, Houghton Mifflin/Faber), and The Birth of the Mind (Basic Books, 2004, translated into 6 languages). He is also the editor of The Norton Psychology Reader, and the author of ...more

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