AI: Beyond the Hype
Many people today are confused, and even fearful, about Artificial Intelligence. They read and hear stories that make bold claims about the capabilities of AI and how these systems are going to ‘take over the world’. But the reality is much more down-to-earth than that, with AI making great inroads into providing enterprises with valuable new insights about the way they run their businesses.
Much of the confusion and fear comes from a conflation of general purpose AI (usually called Artificial General Intelligence, or AGI) and special-purpose AI (usually called Artificial Narrow Intelligence, or ANI). There is a huge, if not insurmountable, difference between these two forms of AI. Everything that exists today in the world of AI is ANI - this is because all of the AI applications that are built are very good at doing one single thing very well indeed. This includes such things as image recognition, speech recognition, natural language understanding and prediction. A system built for speech recognition would not be able to recognise images. But it gets even narrower than that - an image recognition system that was trained to recognise pictures of dogs would not be able to suddenly recognise pictures of cats - it would need to be trained from scratch again to do that. Even AlphaGo, Deepmind’s AI system which beat the best player in the world at Go last year, would not be able to beat you at Noughts-and-Crosses [Tic-Tac-Toe]. To do so, it would have to have its memory wiped (this is called Catastrophic Forgetting) and then trained to play Noughts-and-Crosses.
What our brain is very good at is taking a concept from one thing and being able to apply it to another. For example when we are young we learn to ride a tricycle, then a bicycle and eventually we learn to drive a car. We take some of the concepts from each stage into the next. An AI couldn’t do that - it would be trained on either riding a tricycle, riding a bike or driving a car. Our brain is able to pull together all of our thoughts (images, sounds, feelings, smells, etc) to create new thoughts and concepts that we use to make decisions and create things, which is what we usually call intelligence, but is more accurately called ‘general intelligence’.
Now, it’s true that there have been some very recent developments from companies like Deepmind that have started to get systems to take learnings from one computer game and use them in others, but it is still very early days. And this is just one, very specific environment. Taking that out into ‘the wild’, i.e. real life, presents a whole different order of magnitude of challenges. So, it’s likely that at some point there will be some very limited examples of AGI but I am very sceptical that we will ever recreate the full capabilities of our brain.
There are many examples of ANI being used in business and by people on a day to day basis. Email spam filters use Natural Language Processing (NLP) and Prediction capabilities to differentiate between normal and spam emails. Voice assistants, such as Siri and Alexa, using Speech Recognition and NLP to understand what we want them to do. Satnavs use Problem Solving capabilities to find the optimum route. Many people don’t realise they are using AI in these situations because it has become so commonplace.
In business, where I advise companies on their AI strategies, we are seeing an increasing interest and usage of AI to improve efficiency but also – and this is where AI comes into its own – to improve decision making. To give a few examples: Virgin Trains use Celaton’s AI software to ‘read’ all of their incoming emails to determine who is the best person in the organisation to deal with it; Deutsche Bank use Speech Recognition AI capabilities to ‘listen’ to all of their dealer’s client calls for hints of non-compliance or fraud; PayPal use AI Prediction capabilities to identify fraudulent transactions almost as they are happening (PayPal’s transaction fraud rate is just 0.32% compared to an industry average of 1.32%); and Google used AI Optimisation capabilities to reduce the cooling bill in their data centres by 40%.
AI has the ability to transform the way that companies do business, but they need to understand what it is capable of and how to implement it. Once AI has been demystified, business executives can then start to understand how these capabilities can transform their businesses. The Executive Guide to Artificial Intelligence provides a roadmap for starting on that AI journey, helping business leaders understand, identify and apply AI into their own organisations in a pragmatic and meaningful way.
Andrew Burgess is the author of The Executive Guide to Artificial Intelligence: How to identify and implement applications for AI in your organization. An advisor, author and speaker with over 25 years’ experience, he is considered an authority on innovative and disruptive technologies and business models, including artificial intelligence and robotic process automation.