Despite existing for years as an academic curiosity, the concept of Artificial Intelligence (AI) and the dream of creating computers that can think and reason like human beings is finally becoming a reality that impacts on our everyday lives. More and more businesses are finding practical uses for AI from healthcare to gaming and from finance to energy saving. In the words of former Apple, Google and Microsoft executive Kai Fu Lee, AI has moved from “rocket science to the mainstream”.
As with all new technologies, this brings a new set of legal and ethical challenges, notably around data privacy and anonymity. AI in its modern form is based on the concept of Machine Learning. Rather than trying to build computers that mimic the incredible complexities of the human brain - as scientists had been trying (and failing) to do since the days of Alan Turing and the Enigma code, Machine Learning focuses on putting in place the
fundamental networks that allow computers to learn like babies do - by repetition and gradually developing neural pathways (or in this case algorithms) to make sense of words, pictures, emotions etc.
For example, Google’s Image Search application will be fed hundreds of images of groups of two adults and more than one child that have been identified as families and can then be taught to recognise that other images of adults and children are also likely to be families. The processing power of modern computers means that AI algorithms can be trained to perform tasks that can take humans months or years to learn to do competently such as drive cars or analyse retina scans. So DeepMind’s famous Alpha Go programme isn’t the best chess player in the world because it was programmed to understand all the intricacies of chess that humans have learned over the past 1500 years. It is the best because it was able to play more games of chess than any human - 44 million in 24 hours.
In the world of financial services, AI can be used to make decisions on personal loans in seconds by analysing masses of data on loans taken out by people in similar situations to calculate how likely the applicant is to default. Not only does this massively speed up the process - which benefits both the loan applicant and the finance company - but AI is already proving more accurate than humans at assessing risk.
To do any of these things, the algorithms need data. Lots of data. Companies such as Google’s DeepMind are now finding ways to harness machine learning to generate their own data to further train their algorithms, but generally that data comes from people, who in this GDPR world should be making a conscious, informed decision to hand over their personal data for use by AI.
For example, if you were providing your personal data to a healthcare research programme, you would probably want to know exactly who was going to use it and what for and who they were going to share the results with. You’d want to know that your data was going to be stored and processed securely and would remain anonymised so there would be no chance of it being traced back to you and used against you. And you’d want to know that it was being used for something important.
AI leaders throughout the world are grappling to strike the right balance between technological progress and personal privacy. Google for example has a list of AI Principles that ensures that AI products and research projects are based on fundamental principles of accountability, privacy etc.
Which brings us to China. Where China has (successfully) been playing catchup over the past two decades when it comes to web and mobile technology, it is already established as an equal to the US in the blossoming AI industry. China's tech superpowers such as Baidu, Alibaba, and Tencent benefit from a highly organised, government funded AI plan and an education system that produces huge amounts of both engineers and entrepreneurs. Most importantly though, they benefit from access to possibly the world’s most valuable resource - human data from 1.4 billion Chinese citizens, including 800 million smartphone users all using mobile phones, social media networks and mobile payments (in a country where cash and credit cards are almost obsolete) and therefore generating masses of data that can be used to further train those companies’ AI algorithms.
There remains a more cynical view though, that China has an unfair advantage in that its citizens aren’t protected by the same rules of data protection that exist in the US and Europe, so the balance between technology and data privacy is different. But even that is changing. A survey by last year by Tencent and the Chinese state broadcaster challenged the “conventional wisdom that Chinese users care little about privacy, that they accept the trade-off of giving up a large amount of personal data in return for the convenience provided by services that rely on that data and reinforces the view that Chinese consumers are becoming more aware and vocal about their privacy and how their personal data is used.”