Really, you should reject all cookies, otherwise it’s going to be gathering data and that data is going to go into machine learning algorithms, which are going to learn very uncomfortable personal things.”
WHAT DOES THE FUTURE HOLD FOR AI? Given that Professor Wooldridge predicts that AI- generated content and information will be ubiquitous within 10–20 years, there is a question around protection of data and regulation. “There are three models of AI regulation in the world,” he says. “There’s the EU regulation, which is a GDPR-type regulation designed to protect human rights. It’s very aspirational. It remains to be seen how successful it is, but nevertheless, it’s quite a high standard for protecting personal data and so on, just like GDPR does. “Then there is US regulation, which is about
brochure, every company policy, every scientific paper, every bit of Reddit and Twitter, of Facebook, is there. The entirety of Wikipedia was just 3% of that content and that shows the astronomical quantities of data collected,” he says. The new problem for tech companies is that in order
for AI to keep learning and improving in sophistication, it requires new data to be trained on. “If you’ve already used all of the data on the World Wide Web, where do you get more data from? This is not a problem for us, but it is a problem Microsoft and Google,” he says. “They’ve already used up the obvious resources of data and it turns out that using AI-generated data leads to really poor-quality AI, so you can’t train AI-generated outputs. Why should you be concerned about that? Because they really want your data, the data that we provide and that we generate.” While AI can provide incredible benefits, such as
screening large numbers of scans for suspected cancer, there is also a darker side to data collection. All of us often unknowingly consent to invasive data collection, especially through online features like cookies. Professor Wooldridge says that rejecting all cookies may be tedious, but it is an essential step toward preserving privacy. Once data is transferred to a third-party server, control over its use is significantly diminished, regardless of any protections or policies the company claims to have. In many cases, this data goes on to train machine learning algorithms, which can lead to models that reveal insights about individuals’ habits and preferences. “This is an Apple watch and I find it very useful,
but nevertheless, it’s continually gathering data about me,” he says. “You want to check the settings to make sure it’s not being uploaded to a cloud somewhere in Silicon Valley. Once you hand over your private data, you’ve effectively lost control. It doesn’t matter what covenants are being placed on that data, if it’s on a Silicon Valley server then you no longer have control.
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protecting innovation and companies. Then there is Chinese legislation, which is broadly speaking about protecting the institutions of the Chinese state. The EU regulation model is by far the most elaborate and is about protection, particularly in high-risk scenarios where AI has the potential to actually do some harm. But I have to say, the jury out on how successful that’s going to be.” As AI systems grow in sophistication and autonomy,
our responsibility as users and developers is to engage with these systems actively and thoughtfully, he says. Regulation is a key question for governments and nation states and data privacy is a big issue for individuals and companies. While AI offers many opportunities, it can also be biased, inaccurate and misleading. We all need to be aware of its dangers as well as the benefits it can bring.
GLOBAL LEADERSHIP SUPPLEMENT
AI D ATA PROTE CTION MATTER
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