Abstract
Oxford physicist David Deutsch recently claimed that AI researchers had made no progress towards creating truly intelligent agents and were unlikely to do so until they began making machines that could produce creative explanations for themselves. Deutsch argued that AI must be possible because of the Universality of Computation, but that progress towards it would require nothing less than a new philosophical direction: a rejection of inductivism in favour of fallibilism. This paper sets out to review and respond to these claims. After first establishing a broad framework and terminology with which to discuss these questions, it examines the inductivist and fallibilist philosophies. It argues that Deutsch is right about fallibilism, not only because of the need for creative explanations but also because it makes it easier for agents to create and maintain models—a crucial ability for any sophisticated agent. However, his claim that AI research has made no progress is debatable, if not mistaken. The paper concludes with suggestions for ways in which agents might come up with truly creative explanations and looks briefly at the meaning of knowledge and truth in a fallibilist world.
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Notes
- 1.
While agents commonly have well-defined physical boundaries, there is no obvious need for such a restriction, c.f. distributed agents and the extended mind hypothesis.
- 2.
Nothing in what follows actually depends on there being a physical reality; there is simply no way we can prove that an external world exists, or that it has existed for more than a few seconds prior to the present moment, nor that it is not a figment of the individual’s imagination.
- 3.
Agents may not know what these states are, and initially may have them fulfilled either accidentally or purposefully through the actions of other agents, such as parents.
- 4.
What the states are, how they are mapped, and how they are recognised and interpreted are also important questions.
- 5.
Of course, the model’s states and their interpretation may well change between implementations.
- 6.
Not every material is necessarily suitable.
- 7.
Some people include abduction and other uncertain inferences under the general heading of induction. In this paper I use induction in the narrow sense outlined above, rather than adopting this broader sense.
- 8.
There is an exact parallel here with the idea from the Philosophy of Science that all experimentation is carried out within the context of a particular theory.
- 9.
The inability to find a suitable analogy has led some physicists to suggest that intuitions provided by realist analogies (models) are unnecessary, and that the highly abstract mathematical formulations (also models) are sufficient in and of themselves. Deutsch disagrees and devotes a large part of his book to explaining his realist model of a quantum mechanical universe.
- 10.
Modern society promotes individual development by explicitly creating such encounters, in the form of schools, museums, exhibitions, concerts, etc.
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Davenport, D. (2016). Explaining Everything. In: Müller, V.C. (eds) Fundamental Issues of Artificial Intelligence. Synthese Library, vol 376. Springer, Cham. https://doi.org/10.1007/978-3-319-26485-1_20
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