  The field of artificial intelligence (AI) represents an enormous endeavour of
humankind that is currently transforming our societies down to their very
foundations. Its task, building truly intelligent systems, is underpinned by a
vast array of subfields ranging from the development of new electronic
components to mathematical formulations of highly abstract and complex
reasoning. This breadth of subfields renders it often difficult to understand
how they all fit together into a bigger picture and hides the multi-faceted,
multi-layered conceptual structure that in a sense can be said to be what AI
truly is. In this perspective we propose a system of five levels/layers of
abstraction that underpin many AI implementations. We further posit that each
layer is subject to a complexity-performance trade-off whilst different layers
are interlocked with one another in a control-complexity trade-off. This
overview provides a conceptual map that can help to identify how and where
innovation should be targeted in order to achieve different levels of
functionality, assure them for safety, optimise performance under various
operating constraints and map the opportunity space for social and economic
exploitation.
