AI: A Modern Approach is by far the dominant textbook in the field. It is used in 1200 universities, and is currently the 22nd most-cited publication in computer science. Its authors, Stuart Russell and Peter Norvig, devote significant space to AI dangers and Friendly AI in section 26.3, “The Ethics and Risks of Developing Artificial Intelligence.”

The first 5 risks they discuss are:

• People might lose their jobs to automation.
• People might have too much (or too little) leisure time.
• People might lose their sense of being unique.
• AI systems might be used toward undesirable ends.
• The use of AI systems might result in a loss of accountability.

Each of those sections is one or two paragraphs long. The final subsection, “The Success of AI might mean the end of the human race,” is given 3.5 pages. Here’s a snippet:

The question is whether an AI system poses a bigger risk than traditional software. We will look at three sources of risk. First, the AI system’s state estimation may be incorrect, causing it to do the wrong thing. For example… a missile defense system might erroneously detect an attack and launch a counterattack, leading to the death of billions…

Second, specifying the right utility function for an AI system to maximize is not so easy. For example, we might propose a utility function designed to minimize human suffering, expressed as an additive reward function over time… Given the way humans are, however, we’ll always find a way to suffer even in paradise; so the optimal decision for the AI system is to terminate the human race as soon as possible – no humans, no suffering…

Third, the AI system’s learning function may cause it to evolve into a system with unintended behavior. This scenario is the most serious, and is unique to AI systems, so we will cover it in more depth. I.J. Good wrote (1965),

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then be unquestionably be an “intelligence explosion,” and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.

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Richard Posner is a jurist, legal theorist, and economist. He is also the author of nearly 40 books, and is by far the most-cited legal scholar of the 20th century.

In 2004, Posner published Catastrophe: Risk and Response, in which he discusses risks from AGI at some length. His analysis is interesting in part because it appears to be intellectually independent from the Bostrom-Yudkowsky tradition that dominates the topic today.

In fact, Posner does not appear to be aware of earlier work on the topic by I.J. Good (1970, 1982), Ed Fredkin (1979), Roger Clarke (1993, 1994), Daniel Weld & Oren Etzioni (1994), James Gips (1995), Blay Whitby (1996), Diana Gordon (2000), Chris Harper (2000), or Colin Allen (2000). He is not even aware of Hans Moravec (1990, 1999), Bill Joy (2000), Nick Bostrom (1997; 2003), or Eliezer Yudkowsky (2001). Basically, he seems to know only of Ray Kurzweil (1999).

Still, much of Posner’s analysis is consistent with the basic points of the Bostrom-Yudkowsky tradition:

[One class of catastrophic risks] consists of… scientific accidents, for example accidents involving particle accelerators, nanotechnology…, and artificial intelligence. Technology is the cause of these risks, and slowing down technology may therefore be the right response.

…there may some day, perhaps some day soon (decades, not centuries, hence), be robots with human and [soon thereafter] more than human intelligence…

…Human beings may turn out to be the twenty-first century’s chimpanzees, and if so the robots may have as little use and regard for us as we do for our fellow, but nonhuman, primates…

…A robot’s potential destructiveness does not depend on its being conscious or able to engage in [e.g. emotional processing]… Unless carefully programmed, the robots might prove indiscriminately destructive and turn on their creators.

…Kurzweil is probably correct that “once a computer achieves a human level of intelligence, it will necessarily roar past it”…

One major point of divergence seems to be that Posner worries about a scenario in which AGIs become self-aware, re-evaluate their goals, and decide not to be “bossed around by a dumber species” anymore. In contrast, Bostrom and Yudkowsky think AGIs will be dangerous not because they will “rebel” against humans, but because (roughly) using all available resources — including those on which human life depends — is a convergent instrumental goal for almost any set of final goals a powerful AGI might possess. (See e.g. Bostrom 2012.)

In 1979, Michael Rabin proved that his encryption system could be inverted — so as to decrypt the encrypted message — only if an attacker could factor n. And since this factoring task is computationally hard for any sufficiently large n, Rabin’s encryption scheme was said to be “provably secure” so long as one used a sufficiently large n.

Since then, creating encryption algorithms with this kind of “provable security” has been a major goal of cryptography,¹ and new encryption algorithms that meet these criteria are sometimes marketed as “provably secure.”

Unfortunately, the term “provable security” can be misleading,² for several reasons³.

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1. An encryption system is said to be provably secure if its security requirements are stated formally, and proven to be satisfied by the system, as was the case with Rabin’s system. See Wikipedia. ↩
2. Security reductions can still be useful (Damgård 2007). My point is just that term “provable security” can be misleading, especially to non-experts. ↩
3. For more details, and some additional problems with the term “provable security,” see Koblitz & Menezes’ Another Look website and its linked articles, especially Koblitz & Menezes (2010). ↩