Engineering Responsible AI

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Artificial intelligence technology is growing at an astonishing pace giving rise to transformative Innovations. However AI is not a homogeneous mass but a multifaceted kaleidoscope of subfields to facilitate communication between innovators, investors policy makers and the public. The Centre for Electronics Frontiers and the Royal Academy of Engineering have created a five layer taxonomy for navigating AI. At the base is the hardware layer the components that form the physical building blocks of an AI system. Innovations in semiconductor materials and devices here can maximize the speed and efficiency of an AI system. Next is the functional layer this includes all fundamental mathematical functions that underpin the systems computation from simple pocket calculator style processing to collections of artificial neurons that can render biologically inspired processing capabilities. The third computational layer is all about the labelling of data creating a vocabulary of symbols that a machine can use to identify and understand meaningful units within images speech or other data. In the fourth semantic layer machines can predict how how complex systems might evolve and expand their previous learning to be able to deal with completely new situations. The final agency layer is the part of AI that enables machines to understand goals and evaluate their actions. This is where capability meets intention, giving rise to key ethical dilemmas of artificial intelligence. It is also where autonomy reaches its highest capabilities. Naturally all the layers are tightly interconnected and the boundaries between them are blurred but the use of this taxonomy can provide a better understanding on how innovations in any layer can bring significant improvements to others. Creating a natural innovation chain ecosystem, improving collaboration across layers and bringing together researchers from different disciplines leading to even greater AI innovation.

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