The future of artificial intelligence: two experts disagree

The future of artificial intelligence: two experts disagree

Artificial intelligence (AI) promises to revolutionise our lives, drive our cars, diagnose our health problems, and lead us into a new future where thinking machines do things that we’re yet to imagine.

Or does it? Not everyone agrees.

Even billionaire entrepreneur Elon Musk, who admits he has access to some of the most cutting-edge AI, said recently that without some regulation “AI is a fundamental risk to the existence of human civilization”.

So what is the future of AI? Michael Milford and Peter Stratton are both heavily involved in AI research and they have different views on how it will impact on our lives in the future.

How widespread is artificial intelligence today?


Answering this question depends on what you consider to be “artificial intelligence”.

Basic machine learning algorithms underpin many technologies that we interact with in our everyday lives - voice recognition, face recognition - but are application-specific and can only do one very specific defined task (and not always well).

More capable AI - what we might consider as being somewhat smart - is only now becoming widespread in areas such as online retail and marketing, smartphones, assistive car systems and service robots such as robotic vacuum cleaners.


The most obvious and useful examples of current AI are the speech recognition on your phone, and search engines such as Google. There is also IBM’s Watson, which in 2011 beat human champion players at the US TV game show Jeopardy, and is now being trialled in business and healthcare.

Most recently, Google’s DeepMind AI called AlphaGo beat the world champion Go player, surprising a lot of people – especially since Go is an extremely complex game, way surpassing chess. What major advances in AI will we see over the next 10 years?


Many auto manufacturers and research institutions are competing to create practical driverless cars for general road use. While currently these cars can drive themselves for much of the time, many challenges remain in dealing with bad weather (heavy rain, fog and snow) and random real-world events such as roadworks, accidents and other blockages.

These incidents often require some degree of human judgement, common sense and even calculated risk to successfully navigate through. We are still a long way from fully autonomous vehicles that don’t need a licensed driver ready to take control in an instant.

The same can be said for all the AI that we will see over the coming 10-20 years, such as online virtual personal assistants, accountants, legal and financial advisers, doctors and even physical shop-bots, museum guides, cleaners and security guards.

They will be advanced tools that are very useful in specific situations, but they will never fully replace people because they will have little common sense (probably none, in fact).


We will definitely see a range of steady, incremental improvements in everyday AI. Online product recommendations will get better, your phone or car will understand your voice increasingly well and your vacuum cleaner robot won’t get stuck as often.

It’s likely that we’ll see some major advances beyond today’s technology in some but not all of the following areas: self-driving cars, healthcare, utilities (electricity, water, and so on) management, legal, and service areas such as cleaning robots.

I disagree on self-driving cars - there’s no real reason why there won’t be fully autonomous controlled ride-sharing fleets in the affluent centres of cities, and this is indeed the strategy of companies such as NuTonomy, working in Singapore and Boston.

What approaches will lead to the biggest improvements in AI?


Major advances will come from two sources.

First, there is a long runway of steady incremental improvements left in many areas of conventional AI - large, complex neural networks and algorithms. These systems will continue to improve steadily as more training data becomes available and as scientists perfect them.

The second area will likely be biological inspiration. Scientists are only just starting to tap into the knowledge about how brain networks work, and it’s likely they will copy or adapt what we know about animal and human brains to make current deep learning networks far more capable.


Old-fashioned AI, which was based on pure logic and computer programs that tried to get machines to behave intelligently, basically failed to do anything that humans are good at and computers are not (speech and image recognition, playing complex strategic games, for example).

What’s quite clear now is that our best-performing AI is based on how we think the brain works.

But our current brain-based AI (called Deep Artificial Neural Networks) is still light years away from emulating an actual brain. Enhanced AI capabilities in the future will come from developing better theories of how the brain works.

The fundamental science needed to cultivate these theories will probably come from publicly funded research institutions, which will then be spun off into commercial start-up companies, and then quickly acquired by interested large corporations if they look like they might be successful.

How will artificial intelligence affect society and jobs?


Most jobs won’t be under threat for a long time, probably several generations. Real people are needed to actually make any significant decisions because AI currently has no common sense.

Instead of replacing jobs, our overall quality of life will go up. For example, right now few people can afford a personal assistant, or a full-time life coach. In the near future, we’ll all have (a virtual) one!

Our virtual doctor will be working for us daily, monitoring our health and making exercise and lifestyle suggestions.

Our houses and workplaces might be cleaner, but we will still need people to clean the spots the robots miss. We’ll also need people to deploy, retrieve and maintain all the robots.