The future of AI is on the Edge

Artificial Intelligence (AI) algorithms have become an inevitable part of our lives and are so pervasive that users often engage with them unconsciously. Both users and systems contribute vast amounts of data to train these algorithms.

AI addresses a wide range of critical and sensitive problems, from medical diagnostics and climate change mitigation to assisted driving and financial technologies.

However, AI systems come with their advantages and drawbacks. One significant concern is the security of AI systems, as they are vulnerable to sophisticated malicious attacks, unintentional changes, omissions of context in training data, sensor ageing, changes in the training environment, and other unforeseen circumstances. This makes AI applications at the edge—such as smartphones and cars—susceptible to defects in training data and AI models.

Edge AI focuses on safeguarding data integrity and the quality of learning associated with AI algorithms when they are exposed to cyber-attacks in edge computing environments, such as those in the EPSRC National Edge Artificial Intelligence Hub.