ABSTRACTWhile over the last few decades AI research has largely focused on building tools and applications, recent technological developments have prompted a resurgence of interest in building a genuinely intelligent artificial agent – one that has a mind in the same sense that humans and animals do. In this paper, I offer a theoretical and methodological framework for this project of investigating “artificial minded intelligence” that can help to unify existing approaches and provide new avenues for research. I first outline (...) three desiderata that a framework for AMI research should satisfy. In Section 1, I further motivate the desiderata as well as the need for a new framework. Section 2 develops a general methodological approach, the “generative methodology,” and Section 3 develops a version of this methodology, the “Competence Framework for AI research”. (shrink)

After more than 60 years, Shannon’s research continues to raise fundamental questions, such as the one formulated by R. Luce, which is still unanswered: “Why is information theory not very applicable to psychological problems, despite apparent similarities of concepts?” On this topic, S. Pinker, one of the foremost defenders of the widespread computational theory of mind, has argued that thought is simply a type of computation, and that the gap between human cognition and computational models may be illusory. In this (...) context, in his latest book, titled Thinking Fast and Slow, D. Kahneman provides further theoretical interpretation by differentiating the two assumed systems of the cognitive functioning of the human mind. He calls them intuition (system 1) determined to be an associative (automatic, fast and perceptual) machine, and reasoning (system 2) required to be voluntary and to operate logical-deductively. In this paper, we propose a mathematical approach inspired by Ausubel’s meaningful learning theory for investigating, from the constructivist perspective, information processing in the working memory of cognizers. Specifically, a thought experiment is performed utilizing the mind of a dual-natured creature known as Maxwell’s demon: a tiny “man–machine” solely equipped with the characteristics of system 1, which prevents it from reasoning. The calculation presented here shows that the Ausubelian learning schema, when inserted into the creature’s memory, leads to a Shannon-Hartley-like model that, in turn, converges exactly to the fundamental thermodynamic principle of computation, known as the Landauer limit. This result indicates that when the system 2 is shut down, both an intelligent being, as well as a binary machine, incur the same minimum energy cost per unit of information (knowledge) processed (acquired), which mathematically shows the computational attribute of the system 1, as Kahneman theorized. This finding links information theory to human psychological features and opens the possibility to experimentally test the computational theory of mind by means of Landauer’s energy cost, which can pave a way toward the conception of a multi-bit reasoning machine. (shrink)

As highly intelligent autonomous robots are gradually introduced into the home and workplace, ensuring public safety becomes extremely important. Given that such machines will learn from interactions with their environment, standard safety engineering methodologies may not be applicable. Instead, we need to ensure that the machines themselves know right from wrong; we need moral mechanisms. Morality, however, has traditionally been considered a defining characteristic, indeed the sole realm of human beings; that which separates us from animals. But if only humans (...) can be moral, can we build safe robots? If computationalism—roughly the thesis that cognition, including human cognition, is fundamentally computational—is correct, then morality cannot be restricted to human beings (since equivalent cognitive systems can be implemented in any medium). On the other hand, perhaps there is something special about our biological makeup that gives rise to morality, and so computationalism is effectively falsified. This paper examines these issues by looking at the nature of morals and the influence of biology. It concludes that moral behaviour is concerned solely with social well-being, independent of the nature of the individual agents that comprise the group. While our biological makeup is the root of our concept of morals and clearly affects human moral reasoning, there is no basis for believing that it will restrict the development of artificial moral agents. The consequences of such sophisticated artificial mechanisms living alongside natural human ones are also explored. (shrink)