Future Trends for Human-AI Collaboration: A Comprehensive Taxonomy of
AI/AGI Using Multiple Intelligences and Learning Styles
- URL: http://arxiv.org/abs/2008.04793v4
- Date: Fri, 11 Dec 2020 10:38:05 GMT
- Title: Future Trends for Human-AI Collaboration: A Comprehensive Taxonomy of
AI/AGI Using Multiple Intelligences and Learning Styles
- Authors: Andrzej Cichocki and Alexander P. Kuleshov
- Abstract summary: We describe various aspects of multiple human intelligences and learning styles, which may impact on a variety of AI problem domains.
Future AI systems will be able not only to communicate with human users and each other, but also to efficiently exchange knowledge and wisdom.
- Score: 95.58955174499371
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This article discusses some trends and concepts in developing new generation
of future Artificial General Intelligence (AGI) systems which relate to complex
facets and different types of human intelligence, especially social, emotional,
attentional and ethical intelligence. We describe various aspects of multiple
human intelligences and learning styles, which may impact on a variety of AI
problem domains. Using the concept of 'multiple intelligences' rather than a
single type of intelligence, we categorize and provide working definitions of
various AGI depending on their cognitive skills or capacities. Future AI
systems will be able not only to communicate with human users and each other,
but also to efficiently exchange knowledge and wisdom 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.
Key words: Artificial General Intelligence (AGI), multiple intelligences,
learning styles, physical intelligence, emotional intelligence, social
intelligence, attentional intelligence, moral-ethical intelligence, responsible
decision making, creative-innovative intelligence, cognitive functions,
meta-learning of AI systems.
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