Society of Mind

These resources were developed in anticipation of Ed Fredkin's lecture this Wednesday (27 Feb). You should look over the topics in advance; the more opinions, questions, and criticisms you develop in advance, the more you will gain from the lecture. In particular (see topic #3), you may want to think of ways to avert a robot apocalypse— just in case.

Preparing for intelligent machines

1. Architecture. What exotic hardware is required to build machines with human-level intelligence? For example, is parallelism the key to human-like thinking? Is nondeterminism and/or randomness and/or quantum mechanics? Alternately, could our existing hardware support intelligent programs if we knew how to design the right software?
2. Technical requirements. The technical specs of the human brain can give an idea of the technical requirements for intelligent machines. How much information do we gather over the course of a lifetime? How fast do nerve impulses travel? How much does the memory capacity of the human genome limit the potential complexity of our brains?
3. Avoiding apocalypse. Science fiction presents countless stories of homicidal intelligent machines.
   • What are the real risks involved with the invention of intelligent machines? Which risks are not real?
   • Might we prevent machines from becoming dangerous by building in safety protocols or laws to obey into their hardware? Or by isolating them physically, on a separate network, on a separate power grid, etc.? What are the obstacles involved in doing so? How do security issues with machines that can think differ from security issues with, for example, nuclear reactors?
   • What are the ethics of perscribing a different set of laws for mechanical intelligence and biological intelligence? Might we prevent machines from becoming dangerous by teaching them ethics in the same way that we teach each other ethics? Might machines be in a position to teach humans about ethics instead?

Suggested excellent reading

Architecture and technical requirements
• [link] In his PhD thesis on the Connection Machine, Danny Hillis discusses the paradox that computers seem so much faster than brains yet currently do so much less. (See section 1.1, pages 6-8).
• [link] Prof. Minsky argues that parallel computing makes it harder to do many things at once, because the available resources must be rationed among all available processes. (See the section called "Fragmentation and the parallel paradox")
• [link] This article analyzes the energy limits of the brain, showing that the computational power of the brain must be similarly limited.
• [link]. Some argue that the brain is a quantum computer. The authors of this paper conclude that the argument is wrong-headed.

---

Avoiding apocalypse
• [link]. The Machine Intelligence Research Institute is an organization dedicated to developing artificial intelligence software responsibly, and to raising awareness about the benefits and dangers of creating intelligent machines. This paper discusses the risks of AI, and proposes some solutions.
• [link]. Eliezer Yudkowsky, one of the co-founders of the Machine Intelligence Research Institute, has proposed and run the AI box experiment to challenge the assumption that humans could successfully incarcerate a superhuman intelligence.
• [link] Aaron Sloman argues that it is unethical to impose different laws for human and non-human intelligent beings.