Intelligence and consciousness in natural and artificial systems

Humans are highly intelligent, and their brains are associated with rich states of consciousness. We typically assume that animals have different levels of consciousness, and this might be correlated with their intelligence. Very little is known about the relationships between intelligence and consciousness in artificial systems. Most of our current definitions of intelligence describe human intelligence. They have severe limitations when they are applied to non-human animals and artificial systems. To address this issue, this chapter sets out a new interpretation of intelligence that is based on a system’s ability to make accurate predictions. Human intelligence is measured using tests whose results are converted into values of IQ and g-score. This approach does not work well with non-human animals and AIs, so people have been developing universal algorithms that can measure intelligence in any type of system. In this chapter a new universal algorithm for measuring intelligence is described, which is based on a system’s ability to make accurate predictions. Many people agree that consciousness is the stream of colorful moving noisy sensations that starts when we wake up and ceases when we fall into deep sleep. Several mathematical algorithms have been developed to describe the relationship between consciousness and the physical world. If these algorithms can be shown to work on human subjects, then they could be used to measure consciousness in non-human animals and artificial systems. At present we can use our own imagination, intelligence and consciousness to picture possible relationships between intelligence and consciousness in non-human systems. In the future, we could use mathematical algorithms to measure intelligence, measure consciousness and identify correlations between intelligence and consciousness. This would lead to a more rigorous scientific understanding of the relationships between intelligence and consciousness in natural and artificial systems