As AI becomes a transformative part of our technology landscape, a common vocabulary about the capabilities of each new tool and technique is essential. Common vocabularies create shared intellectual spaces allowing all stakeholders to accelerate understanding, increase adoption, facilitate collaboration, benchmark progress and drive innovation. So far, the most widely known tool for benchmarking AI is the Turing Test. However, the field of artificial intelligence (AI) has come a long way since the inception of the Turing Test in 1950. As such, it is becoming increasingly clear that the Turing Test is insufficient for evaluating the full range of AI capabilities that are emerging today -- or are likely to emerge in the future.

Learning is a lifelong process. It starts when we're babies and follows us into old age. Education is essential to our development and to how we see the world. The desire for knowledge starts at a young age through an exploration of one's surroundings, followed by formal education and beyond. Throughout life, we learn to retain information in a certain way and whatever your preferred style is, it's crucial to understand why it works for you. If you understand the basics, you can improve and build on them to further your knowledge.

This article discusses recent trends and concepts in developing new kinds of artificial intelligence (AI) systems which relate to complex facets and different types of human intelligence, especially social, emotional, attentional and ethical intelligence, which to date have been under-discussed. We describe various aspects of multiple human intelligence and learning styles, which may impact on a variety of AI problem domains. Using the concept of multiple intelligence rather than a single type of intelligence, we categorize and provide working definitions of various AI depending on their cognitive skills or capacities. Future AI systems will be able not only to communicate with human actors and each other, but also to efficiently exchange knowledge with abilities of cooperation, collaboration and even co-creating something new and valuable and have meta-learning capacities. Multi-agent systems such as these can be used to solve problems that would be difficult to solve by any individual intelligent agent.

In part 1, we considered the Multiple Intelligences that Artificial Intelligence already exhibit today. In part two, we consider the three intelligences for which A.I. does not exist. Existential Intelligence is one of the intelligences in Howard Gardener's taxonomy of multiple intelligences. It is the intelligence ascribed to those who think philosophically and involves an individual's ability to contemplate values and intuition to understand themselves and the world around them. People who possess this intelligence are able to see the big picture and ask the big questions. Existential intelligence was not included in the original seven intelligences that Gardner listed in his original list of Multiple Intelligences.

How do we define "Intelligence"? One definition is to say intelligence is the ability to think in abstract terms. This is what separates us from animals. Polar bears, walruses, otters and other mammals have a marvellous ability to survive in their habitat. However, "intelligent" isn't a word that leaps to mind when we describe them. It is humans who have the ability to think in abstract terms -- to use metaphors, to devise calculus, to convert music to notes, to associate colour with emotions, to use logic, to think about thinking, to moralise, to contemplate eternity, and so on.

Early I brought up Howard Gardner's theory of multiple intelligences. That is, humans exhibit strengths in different kinds of intelligences. Specifically these are interpersonal, intrapersonal, verbal, logical, spatial, rhythmic, naturalistic and kinaesthetic intelligence. Clearly there are many kinds of ways of thinking, each with their own strengths. Therefore, one may ask if we can use this notion of multiple intelligences to explore the different ways that AGI research may evolve.

Early I brought up Howard Gardner's theory of multiple intelligences. That is, humans exhibit strengths in different kinds of intelligences. Specifically these are interpersonal, intrapersonal, verbal, logical, spatial, rhythmic, naturalistic and kinaesthetic intelligence. Clearly there are many kinds of ways of thinking, each with their own strengths. Therefore, one may ask if we can use this notion of multiple intelligences to explore the different ways that AGI research may evolve.

One of the most commonly used methods of measuring human intelligence is the IQ test. However, this approach has received widespread criticism due to its perceived inability to capture the whole gamut of elements that determines human intelligence. Howard Gardner, proposed the theory of multiple intelligences in 1983. According to him, IQ tests have little relevance in reality. He denies there is general intelligence, and his theory instead suggests the presence of separate domains of ability.