Hype Will Harm Artificial Intelligence

After exploring AI deployment in some depth and chairing the SCL's overview of AI in Dublin in September, I've been particularly conscious of the hype vs reality. Nobody should deny that narrow artificial intelligence is here to stay - for good and bad. We just have to be realistic about its capabilities and shortcomings - and how to detect their consequences - so that AI is developed and deployed responsibly.

In a recent report on 'smart cities', for example, the Oliver Wyman Forum found that no city on Earth is ready for the disruptive effects of artificial intelligence. 

Talk of 'killer robots' and beating humans at board games is also all the rage, but Barry O'Sullivan assured us in Dublin that robots take ages to 'train' for any one sequence, can't cope with door handles and their batteries soon run down. It took $50m in electricity to train a computer to beat a human at Go. 

AI can be used for good, but it can also be 'weaponised' against a population, and 'hacked' by altering the appearance of things or people's appearance in quite subtle ways - without actually interfering with the AI itself. 

In the 'real world' of AI, the genuine concerns are inaccuracy, lack of explainability and the inability to remove bias. And there remain vast challenges associated with the reliability of evidence and how to resolve disputes arising from their use. 

That means we have to challenge the use of AI where the consequences of false positives or negatives are fatal or otherwise unacceptable, such as denying fundamental rights or compensation for loss, for example. 

Instead, artificial neural networks and deep learning are better used to automate decision-making where "the level of accuracy only needs to be "tolerable" for commercial parties [who are] interested only in the financial consequences... than for individuals concerned with issues touching on fundamental rights."

Being realistic about AI and its shortcomings also has implications for how it is regulated. Rather than risk an effective ban on AI by regulating it according to the hype, regulation should instead focus on certifying AI's development and transparency in ways that enable us to understand its shortcomings to aid in our decision about where it can be developed and deployed appropriately.