Melanie Mitchell > Quotes

“as the AI researcher Pedro Domingos so memorably put it, “People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.”21”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“We should be afraid. Not of intelligent machines. But of machines making decisions that they do not have the intelligence to make. I am far more afraid of machine stupidity than of machine intelligence. Machine stupidity creates a tail risk. Machines can make many many good decisions and then one day fail spectacularly on a tail event that did not appear in their training data. This is the difference between specific and general intelligence.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“This statement is not provable.” Think about it for a minute. It’s a strange statement, since it talks about itself—in fact, it asserts that it is not provable. Let’s call this statement “Statement A.” Now, suppose Statement A could indeed be proved. But then it would be false (since it states that it cannot be proved). That would mean a false statement could be proved—arithmetic would be inconsistent. Okay, let’s assume the opposite, that Statement A cannot be proved. That would mean that Statement A is true (because it asserts that it cannot be proved), but then there is a true statement that cannot be proved—arithmetic would be incomplete. Ergo, arithmetic is either inconsistent or incomplete.”
― Melanie Mitchell, Complexity: A Guided Tour

“As the nineteenth-century philosopher Henry David Thoreau put it, “All perception of truth is the detection of an analogy.”
― Melanie Mitchell, Complexity: A Guided Tour

“Whew, this might be getting a bit confusing. I hope you are following me so far. This is the point in every Theory of Computation course at which students either throw up their hands and say "I can't get my mind around this stuff!" or clap their hands and say "I love this stuff!"

Needless to say, I was the second kind of student, even though I shared the confusion of the first.”
― Melanie Mitchell, Complexity: A Guided Tour

“Above all, the take-home message from this book is that we humans tend to overestimate AI advances and underestimate the complexity of our own intelligence. Today’s”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“complex system: a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution.”
― Melanie Mitchell, Complexity: A Guided Tour

“A pile of narrow intelligences will never add up to a general intelligence. General intelligence isn’t about the number of abilities, but about the integration between those abilities.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“Linearity is a reductionist’s dream, and nonlinearity can sometimes be a reductionist’s nightmare. Understanding the distinction between linearity and nonlinearity is very important and worthwhile. To”
― Melanie Mitchell, Complexity: A Guided Tour

“In short, what Brown, Enquist, and West are saying is that evolution structured our circulatory systems as fractal networks to approximate a “fourth dimension” so as to make our metabolisms more efficient. As West, Brown, and Enquist put it, “Although living things occupy a three-dimensional space, their internal physiology and anatomy operate as if they were four-dimensional … Fractal geometry has literally given life an added dimension.”
― Melanie Mitchell, Complexity: A Guided Tour

“In any ranking of near-term worries about AI, superintelligence should be far down the list. In fact, the opposite of superintelligence is the real problem. Throughout this book, I’ve described how even the most accomplished AI systems are brittle; that is, they make errors when their input varies too much from the examples on which they’ve been trained. It’s often hard to predict in what circumstances an AI system’s brittleness will come to light. In transcribing speech, translating between languages, describing the content of photos, driving in a crowded city—if robust performance is critical, then humans are still needed in the loop. I think the most worrisome aspect of AI systems in the short term is that we will give them too much autonomy without being fully aware of their limitations and vulnerabilities. We tend to anthropomorphize AI systems: we impute human qualities to them and end up overestimating the extent to which these systems can actually be fully trusted.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“We have a poor mathematical, as well as a poor intuitive understanding of the nature of coincidence.”
― Melanie Mitchell, Complexity: A Guided Tour

“Hofstadter ended his talk with a direct reference to the very Google engineers in that room, all listening intently: “I find it very scary, very troubling, very sad, and I find it terrible, horrifying, bizarre, baffling, bewildering, that people are rushing ahead blindly and deliriously in creating these things.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“New companies have sprung up to offer labeling data as a service; Mighty AI, for example, offers “the labeled data you need to train your computer vision models” and promises “known, verified, and trusted annotators who specialize in autonomous driving data.”11 The”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“Hofstadter... fears that AI might show us that the human qualities we most value are disappointingly simple to mechanize.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“How is it that those systems in nature we call complex and adaptive—brains, insect colonies, the immune system, cells, the global economy, biological evolution—produce such complex and adaptive behavior from underlying, simple rules?”
― Melanie Mitchell, Complexity: A Guided Tour

“Kurzweil is not only a director of engineering at Google but also a cofounder (with his fellow futurist entrepreneur Peter Diamandis) of Singularity University (SU), a “trans-humanist” think tank, start-up incubator, and sometime summer camp for the tech elite. SU’s published mission is “to educate, inspire, and empower leaders to apply exponential”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“Define your terms … or we shall never understand one another.”10 This admonition from the eighteenth-century philosopher Voltaire is a challenge for anyone talking about artificial intelligence, because its central notion—intelligence—remains so ill-defined. Marvin Minsky himself coined the phrase “suitcase word”11 for terms like intelligence and its many cousins, such as thinking, cognition, consciousness, and emotion. Each is packed like a suitcase with a jumble of different meanings. Artificial intelligence inherits this packing problem, sporting different meanings in different contexts.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“has definitive answers. Although I do not address the first question here, there has been some fascinating research on it in the complex systems community. The second question—what is life, exactly?—has been on the minds of people probably for as”
― Melanie Mitchell, Complexity: A Guided Tour

“Reflecting on real-life machine morality, the mathematician Norbert Wiener noted as long ago as 1960 that “we had better be quite sure that the purpose put into the machine is the purpose which we really desire.”18”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“The defining idea of chaos is that there are some systems—chaotic systems—in which even minuscule uncertainties in measurements of initial position and momentum can result in huge errors in long-term predictions of these quantities. This is known as “sensitive dependence on initial conditions.”
― Melanie Mitchell, Complexity: A Guided Tour

“Kurzweil cites numerous quotations from prominent people in history who completely underestimated the progress and impact of technology. Here are a few examples. IBM’s chairman, Thomas J. Watson, in 1943: ‘I think there is a world market for maybe five computers.’ Digital Equipment Corporation’s co-founder Ken Olsen in 1977: ‘There’s no reason for individuals to have a computer in their home.’ Bill Gates in 1981: ‘640,000 bytes of memory ought to be enough for anybody.”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“Tony Rothman points out, “Why the second law should distinguish between past and future while all the other laws of nature do not is perhaps the greatest mystery in physics.”
― Melanie Mitchell, Complexity: A Guided Tour

“so many people were shocked and upset when, in 1997, IBM’s Deep Blue chess-playing system defeated the world chess champion Garry Kasparov. This event so stunned Kasparov that he accused the IBM team of cheating; he assumed that for the machine to play so well, it must have received help from human experts.2 (In a nice bit of irony, during the 2006 World Chess Championship matches the tables were turned, with one player accusing the other of cheating by receiving help from a computer chess program.3) Our collective human angst over Deep Blue quickly receded. We accepted that chess could yield to brute-force machinery; playing chess well, we allowed, didn’t require general intelligence after all. This seems to be a common response when computers surpass humans on a particular task; we conclude that the task doesn’t actually require intelligence. As John McCarthy lamented, ‘As soon as it works, no one calls it AI any more.’4”
― Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans

“You”
― Melanie Mitchell, Complexity: A Guided Tour

“Turing’s first goal was to make very concrete this notion of definite procedure. The idea is that, given a particular problem to solve, you can construct a definite procedure for solving it by designing a Turing machine that solves it. Turing machines were put forth as the definition of “definite procedure,” hitherto a vague and ill-defined notion.”
― Melanie Mitchell, Complexity: A Guided Tour

“But twentieth-century science was also marked by the demise of the reductionist dream. In spite of its great successes explaining the very large and very small, fundamental physics, and more generally, scientific reductionism, have been notably mute in explaining the complex phenomena closest to our human-scale concerns.”
― Melanie Mitchell, Complexity: A Guided Tour

“forward to the day when we can together tour those new”
― Melanie Mitchell, Complexity: A Guided Tour

“Information, as narrowly defined by Shannon, concerns the predictability of a message source. In the real world, however, information is something that is analyzed for meaning, that is remembered and combined with other information, and that produces results or actions. In short, information is processed via computation.”
― Melanie Mitchell, Complexity: A Guided Tour

“As in all adaptive systems, maintaining a correct balance between these two modes of exploring is essential. Indeed, the optimal balance shifts over time. Early explorations, based on little or no information, are largely random and unfocused. As information is obtained and acted on, exploration gradually becomes more deterministic and focused in response to what has been perceived by the system. In short, the system both explores to obtain information and exploits that information to successfully adapt.”
― Melanie Mitchell, Complexity: A Guided Tour