Bostrom (2012). The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents.
This paper discusses the relation between intelligence and motivation in artificial agents, developing and briefly arguing for two theses. The first, the orthogonality thesis, holds (with some caveats) that intelligence and final goals (purposes) are orthogonal axes along which possible artificial intellects can freely vary—more or less any level of intelligence could be combined with more or less any final goal. The second, the instrumental convergence thesis, holds that as long as they possess a sufficient level of intelligence, agents having any of a wide range of final goals will pursue similar intermediary goals because they have instrumental reasons to do so. In combination, the two theses help us understand the possible range of behavior of superintelligent agents, and they point to some potential dangers in building such an agent.
Yampolskiy & Fox (2012a). Safety engineering for artificial general intelligence.
Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we challenge the scientific community to develop intelligent systems that have humanfriendly values that they provably retain, even under recursive self-improvement.
Yampolskiy & Fox (2012b). Artificial general intelligence and the human mental model.
When the first artificial general intelligences are built, they may improve themselves to far-above-human levels. Speculations about such future entities are already affected by anthropomorphic bias, which leads to erroneous analogies with human minds. In this chapter, we apply a goal-oriented understanding of intelligence to show that humanity occupies only a tiny portion of the design space of possible minds. This space is much larger than what we are familiar with from the human example; and the mental architectures and goals of future superintelligences need not have most of the properties of human minds. A new approach to cognitive science and philosophy of mind, one not centered on the human example, is needed to help us understand the challenges which we will face when a power greater than us emerges.
The new double-issue of Journal of Consciousness Studies focuses on responses to David Chalmers’ 2010 paper on the Singularity, and includes several articles relevant to Friendly AI.
Luke Muehlhauser and Anna Salamon of the Singularity Institute have released a draft version of their forthcoming book chapter “Intelligence Explosion: Evidence and Import.”
Humans may create human-level artificial intelligence (AI) this century. Shortly thereafter, we may see an “intelligence explosion” or “technological singularity” — a chain of events by which human-level AI leads, fairly rapidly, to intelligent systems whose capabilities far surpass those of biological humanity as a whole.
How likely is this, and what will the consequences be? Others have discussed these questions previously…; our aim is to provide a brief review suitable both for newcomers to the topic and for those with some familiarity with the topic but expertise in only some of the relevant fields.
MIT’s Paul Christiano has written many substantive blog posts related to Friendly AI theory on his blog, Ordinary Ideas.
A new website, Friendly-AI.com, provides a quick introduction to the concept of Friendly AI.
Luke Muehlhauser and Louie Helm have posted a draft of their forthcoming article The Singularity and Machine Ethics:
Many researchers have argued that a self-improving artificial intelligence (AI) could become so vastly more powerful than humans that we would not be able to stop it from achieving its goals. If so, and if the AI’s goals differ from ours, then this could be disastrous for humans. One proposed solution is to program the AI’s goal system to want what we want before the AI self-improves beyond our capacity to control it. Unfortunately, it is difficult to specify what we want. After a brief digression concerning human intuitions about intelligence, we offer a series of “intuition pumps” in moral philosophy for our conclusion that human values are complex and difficult to specify. We then survey the evidence from the psychology of motivation, moral psychology, and neuroeconomics that supports our position. We conclude by recommending ideal preference theories of value as a promising approach for developing a machine ethics suitable for navigating the Singularity.
Video of Eliezer’s talk for Singularity Summit 2011, entitled “Open Problems in Friendly AI,” is now online. (Slides here.)
The open problems he lists are:
He also notes:
Most things you need to know to build Friendly AI are rigorous understanding of AGI rather than Friendly parts per se – contrary to what people who dislike the problem would have you believe, we don’t spend all our time pondering morality.
FHI’s Stuart Armstrong, Anders Sandberg, and Nick Bostrom have released a new article on Oracle AI:
There is no strong reason to believe human level intelligence represents an upper limit of the capacity of artificial intelligence, should it be realized. This poses serious safety issues, since a superintelligent system would have great power to direct the future according to its possibly flawed goals or motivation systems. Solving this issue in general has proven to be considerably harder than expected. This paper looks at one particular approach, Oracle AI. An Oracle AI is an AI that does not act in the world except by answering questions. Even this narrow approach presents considerable challenges and we analyse and critique various methods of control. In general this form of limited AI might be safer than unrestricted AI, but still remains potentially dangerous.
Steve Omohundro has posted an early copy of the article he has submitted to Springer’s The Singularity Hypothesis, titled “Rationally-Shaped Artificial Intelligence.” Abstract:
Systems with the computational power of the human brain are likely to be cheap and ubiquitous within the next few decades. As technology becomes more intelligent, we need to ensure that it remains safe and beneficial. This paper describes a rational framework for analyzing intelligent systems and a strategy for developing them safely. The analysis is based on von Neumann’s model of rational economic behavior. We introduce the “Rationally-Shaped Minds” model of intelligent systems with bounded computation. We show that as computational resources increase, there is a natural progression through stimulus-response systems, learning systems, reasoning systems, self-improving systems, to fully rational systems. We show that rational systems are subject to “drives” toward self-protection, resource acquisition, replication, goal preservation, efficiency, and self-improvement. Several of these drives are anti-social and need to be counteracted with analogs of human cooperativeness and compassion. We analyze the three basic strategies for controlling the behavior of intelligent systems. We describe the “Safe-AI Scaffolding” strategy which builds intentionally limited but safe systems to use in the construction of more powerful systems.
The piece builds on his earlier work, “The Nature of Self-Improving Artificial Intelligence” (2007) and “The Basic AI Drives” (2008). The latter was cited in the latest edition of Russell and Norvig’s famous AI textbook.