Group-Assign: Type Theoretic Framework for Human AI Orchestration
In today’s Information Age, we work under the constant drive to be more productive. Unsurprisingly, we progress towards being an AI-augmented workforce where we are augmented by AI assistants and collaborate with each other (and their AI assistants) at scale. In the context of humans, a human langua...
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| Autores principales: | , , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2021
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/75694 |
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| Sumario: | In today’s Information Age, we work under the constant drive to be more productive. Unsurprisingly, we progress towards being an AI-augmented workforce where we are augmented by AI assistants and collaborate with each other (and their AI assistants) at scale. In the context of humans, a human language suffices to describe and orchestrate our intents (and corresponding actions) with others. This, however, is clearly insufficient in the context of humans and machines. To achieve this, communication across a network of different humans and machines is crucial. With this objective, our research scope covers and presents a type theoretic framework and language built upon type theory (a branch of symbolic logic in mathematics), to enable the collaboration within a network of humans and AI assistants. While the idea of human-machine or human-computer collaboration is not new, to the best of our knowledge, we are one of the first to propose the use of type theory to orchestrate and describe human-machine collaboration. In our proposed work, we define a fundamental set of type theoretic rules and abstract functions Group and Assign to achieve the type theoretic description, composition and orchestration of intents and implementations for an AI-augmented workforce. |
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| ISBN: | 978-1-83968-807-2 |
| DOI: | 10.5772/intechopen.96739 |