This Program Includes An Introduction Read By The Author No Recent Scientific Enterprise Has Proved As Alluring, Terrifying, And Filled With Extravagant Promise And Frustrating Setbacks As Artificial Intelligence The Award Winning Author Melanie Mitchell, A Leading Computer Scientist, Now Reveals Its Turbulent History And The Recent Surge Of Apparent Successes, Grand Hopes, And Emerging Fears That Surround AI In Artificial Intelligence, Mitchell Turns To The Most Urgent Questions Concerning AI Today How Intelligent Really Are The Best AI Programs How Do They Work What Can They Actually Do, And When Do They Fail How Humanlike Do We Expect Them To Become, And How Soon Do We Need To Worry About Them Surpassing Us Along The Way, She Introduces The Dominant Methods Of Modern AI And Machine Learning, Describing Cutting Edge AI Programs, Their Human Inventors, And The Historical Lines Of Thought That Led To Recent Achievements She Meets With Fellow Experts Like Douglas Hofstadter, The Cognitive Scientist And Pulitzer Prize Winning Author Of The Modern ClassicG Del, Escher, Bach, Who Explains Why He Is Terrified About The Future Of AI She Explores The Profound Disconnect Between The Hype And The Actual Achievements In AI, Providing A Clear Sense Of What The Field Has Accomplished And How Much Farther It Has To Go Interweaving Stories About The Science And The People Behind It, Artificial Intelligence Brims With Clear Sighted, Captivating, And Approachable Accounts Of The Most Interesting And Provocative Modern Work In AI, Flavored With Mitchell S Humor And Personal Observations This Frank, Lively Book Will Prove An Indispensable Guide To Understanding Today S AI, Its Quest For Human Level Intelligence, And Its Impacts On All Of Our Futures PLEASE NOTE When You Purchase This Title, The Accompanying PDF Will Be Available In Your Audible Library Along With The Audio

3 thoughts on “Artificial Intelligence: A Guide for Thinking Humans

  1. Customer Customer says:

    I m blown away by how good this book is both in content and style It describes Deep Learning in a simple, informed and objective way You learn how face recognition works, how DeepMind conquered Go and how Google Translate translates Further, the book itself is very pretty and contains many pictures and informative diagrams.

  2. Brian Clegg Brian Clegg says:

    As Melanie Mitchell makes plain, humans have limitations in their visual abilities, typified by optical illusions, but artificial intelligence AI struggles at a much deeper level with recognising what s going on in images Similarly in some ways, the visual appearance of this book misleads It s worryingly fat and bears the ascetic light blue cover of the Pelican series, which since my childhood have been markers of books that were worthy but have rarely been readable This, however, is an excellent book, giving a clear picture of how many AI systems go about their business and the huge problems designers of such systems face.Not only does Mitchell explain the main approaches clearly, her account is readable and engaging I read a lot of popular science books, and it s rare that I keep wanting to go back to one when I m not scheduled to be reading it this is one of those rare examples.We discover how AI researchers have achieved the apparently remarkable abilities of, for example, the Go champion AlphaGo, or the Jeopardy playing Watson In each case these systems are tightly designed for a particular purpose and arguably have no intelligence in the broad sense As for what s probably the most impressively broad AI application of modern times, self driving cars, Mitchell emphasises how limited they truly are Like so many AI applications, the hype far exceeds the reality when companies and individuals talk of self driving cars being commonplace in a few years time, it s quite clear that this could only be the case in a tightly controlled environment.One example, that Mitchell explores in considerable detail are so called adversarial attacks, a particularly AI form of hacking where, for example, those in the know can make changes to images that are invisible to the human eye but that force an AI system to interpret what they are seeing as something totally different It s a sobering thought that, for example, by simply applying a small sticker to a stop sign on the road unnoticeable to a human driver an adversarial attacker can turn the sign into a speed limit sign as far as an AI system is concerned, with potentially fatal consequences.Don t get me wrong, Mitchell, a professor of computer science who has specialised in AI, is no AI luddite But unlike many of the enthusiasts in the field or, for that matter, those who are terrified AI is about to take over the world , she is able to give us a realistic, balanced view, showing us just how far AI has to go to come close to the general abilities humans make use of all the time even in simple tasks AI does a great job, for example, in something like Siri or Google Translate or unlocking a phone with a face but AI systems still have no concept of, for example, understanding as opposed to recognising what is in an image Mitchell makes it clear that where systems learn from large amounts of data, it is usually impossible to uncover how they are making decisions which makes the EU s law requiring transparent AI decisions pretty much impossible to implement , so we really shouldn t trust them with important outcomes as they could easily be basing their outcomes on totally irrelevant inputs.Apart from occasionally finding the explanations of the workings of types of neural network a little hard to follow, the only thing that made me raise an eyebrow was being told that Marvin Minsky coined the phrase suitcase word I would have thought derived the phrase from Lewis Carroll s term portmanteau word would have been closer to reality.There have been good books on the basics of AI already, and excellent ones on the problems that deep learning and big data systems throw up But without a doubt, Mitchell s book sets a new standard in giving an understanding of what s possible and how difficult it is to go further It should be read by every journalist, PR person and politician before they pump out yet hype on the AI future Recommended.

  3. CMB CMB says:

    I was lucky enough to receive an advance reading copy of this book, before it s published.The book is neither scaremongering nor hyping it up, but is well balanced and gives clear explanations and helps you see through the fallacies surrounding AI It s quite a rollercoaster at first as the viewpoints of both are covered, so we understand first the apocalyptic reasoning the singularity, when AI enhances itself at an exponential rate , specialism chess, Go etc , then hype self awareness, even consciousness through to brittleness what we find easy, AI finds hard, and vice versa, so AI can easily be fooled.It s a remarkably easy and interesting book to read, not dry at all I dabbled in neural networks in 1990, the explanation here, and its limitations, would have helped me enormously then It s not a tutorial for creating an AI system, though if you re a keen programmer you could probably work out from first principles from the explanations here Certainly, it made me want to get back into it One of the strengths of this book is it will give you a good grounding in the principles and history underlying AI, and its current limitations.Examples of the brittleness of image and speech recognition are given, but I was left waiting for details of how these adversarial attacks worked For example, if a few pixel changes can make AlexNet consider an image of a dog as an ostrich how were those few pixel changes found It could be giving hints as to what the AI is actually making judgements on.The book is annotated with notes including references but unfortunately, at least in the advance copy, no index.Essential reading for anyone interested or involved with artificial intelligence.