Opinion: artificial intelligence will continue to do great things, but only for limited rather than general tasks

Artificial intelligence systems perform some tasks better than humans. That’s a fact. In our hospitals, for example, AI systems are being used in medical imaging to analyse images scans to help radiologists to diagnose tumours that the human eye can miss.

AI is embedded into our national priorities for education and for research. It’s the focus of many of our technology companies and businesses. It’s seeping into advertising, consumer products and into our homes, through conversational assistants like Amazon’s Alexa. Almost by stealth, AI is being used to make decisions for us and about us. What’s to stop them making decisions without us? Could AI systems become so intelligent that they programme themselves to outsmart us?

From RTÉ Radio One's The Business, Elaine Burke from Silicon Republic discusses Voice Activated Technology like Alexa with Richard Curran 

This concept is referred to as "the Singularity", meaning an uncontrolled, runaway technology growth, a self-fuelling super-intelligence that takes over the world and changes our civilisation. This idea that a computer programme could modify itself to do things other than what it was initially designed for is well-established in software engineering. So too is the notion of computer software that repairs itself when it discovers bugs or is infected by a software virus. In theory, we could have AI singularity, where AI-based programmes improve themselves to the level of super-intelligence. Some people, like the late Stephen Hawking, believed that this could lead to the end of the human race. 

Let’s examine whether it could actually happen. Almost all the AI systems we currently use are based on matching patterns using very sophisticated mathematical modelling. Machine learning, deep learning in particular, is no more than that.These systems use massive amounts of data to detect hidden patterns. Self-driving cars work because Tesla has logged over one billion miles of driving data to use as a basis for mining patterns.

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Facebook and Google accurately describe the images and videos we upload because they have billions of our previous images and videos to mine for patterns of what cats and dogs and roads and flowers look like. Automated translation across languages works because systems have been trained to detect the patterns of language use across different languages. Alexa is able to recognise our speech because she has been trained to recognise the patterns that exist between sound waves and the words that are spoken.

The only AI system to approach human intelligence, which is not based on pattern matching, is IBM’s Watson system. This is a system which reads in and processes large amounts of text information or even images and then answers questions about what is in the text or images. It does more than just finding simple facts from the text like names and dates. It is able to answer complex logical questions that require inference; the kind that appear in the TV programme Only Connect. Watson famously beat the world champion at the US TV game show Jeopardy and is now being used in medical applications, helping to answer questions from doctors about patient diagnosis based on clinical data in some US hospitals.

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While Watson’s function is very impressive, and accurate, it doesn’t work like the human brain. Watson assumes ALL answers to a question are possible answers and it calculates a probability for each possible answer by computing all of these in parallel. Thus, Watson takes a brute force approach and needs huge computer resources.

Human intelligence may be a bit slower at figuring out answers to questions as we don’t always remember everything quickly enough. We may be that fraction of a second slower at translating languages, recognising speech or describing images, but our reasoning is based on cause, not association. We figure out why things are because we understand causes and effects. AI and machine learning figures out its answers based on patterns of association. 

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This means that when we understand things like how electricity works or how the earth revolves around the sun, we understand based on cause and effect. We can propel ourselves to higher levels of understanding that are way more sophisticated than any amount of training data and pattern mining could reach. 

So with this simple but hugely limiting factor, we can rest assured, there won’t be an AI singularity based on current methodologies. All AI is doing is very fast pattern-mining for regularities, and intelligence is not based on the replication of regularities.

AI will continue to do great things, some faster and more reliably than we can, but only for limited rather than general tasks. Taking over the world would be a general task category so we’re safe - for now.


The views expressed here are those of the author and do not represent or reflect the views of RTÉ