Data: The World's New Currency?

Eleni Zampelis

Athens, Greece

Large data systems play an increasingly important role in our everyday / (Joshua Sortino via Unsplash)

We live in a digital world, and data is more valuable than ever. It fuels everything from the algorithms used by social networks to the newly emerging artificial intelligence. This certainly becomes more evident with AI systems, which, by their very nature, depend on abundant personal data. This means viewing privacy, ownership, and intellectual property from an entirely different perspective, whether that comes with innovations or shortcomings.

Consider Apple: well-invested in playing up privacy. To some extent, the artificial intelligence done in iOS 17 points to what comes next. For one thing, the company's assistant is personalised and based on device learning, thus improving the user's experience and utilising the tool of artificial intelligence to process data within said device. Hence, the data stays within the telephone; processing information locally rather than in the cloud gives Apple the means to offer a glimpse at artificial intelligence while ensuring the owner’s privacy of their personal data. Still, the question remains: To what extent is Machine Learning a tool that enhances the democratization of data and therefore information?

This rare balance of development and privacy is not universal and the ability to achieve it is highly debatable. Most AI systems are based on collecting mass numbers of personal data to develop their systems. Sensitive personal information, ranging from facial recognition down to voice commands or even shopping preferences is used in training these models: voice patterns, web activity, and biometric information of individuals. According to companies, even though it is normally anonymized, the simple scale involved in them makes this more traceable back to the single individual. Cybersecurity is a prominent issue in a world dictated by corporate benefit, a world in which the consumer rarely gets to consent to the misuse of their own personal data. Take a moment to think about the amount of trackers that you encounter while making a quick Google search or even the amount of “cookies” that you’ve accepted in the previous couple of days. The systematic abuse of online activity to cater to companies' benefits justly begs the question of control for the consumer who is supposedly, now more than ever, in control of their internet activity.

For example, there are data ethics issues that don't even engage with privacy: who owns it? Who publishes and who distributes it? Consider the example of Apple's Face ID. While promising better security using facial data, it instantly furthers debates on ownership of biometric data and the methods in which that data is stored. When you have millions of users creating data, mostly unconsciously, of course, huge numbers of major issues can and do crop up, especially without sufficient regulation. Wider access to the internet comes at a price, in this case, the lack of legitimacy when it comes to the democratization of information. How is one granted the ability to influence in a global spectrum that is characterized by misinformation and biases perpetuated by generative platforms that operate on an unrestricted basis?

In the digital economy, data has taken the role of the new gold. Certainly in this direction, AI is advancing regularly, but the more complex systems become, the more data they want, making personal data a hot-selling commodity. Companies like Apple demonstrate that one possible future involves on-device data processing, while many others merely make use of user data in return for increasingly developing  AI tools. However, beyond questions of privacy, there's growing tension between AI-driven innovation and intellectual property rights. For example, AI tools increasingly train on large swathes of publicly available content-including often creative works. Such a dynamic raises concerns about ownership in which the created output of a given AI is often built upon extant works, raising a host of legal and ethical questions about erosion in copyright laws. Because of the extensive training basis of these AI tools, the extent to which one’s intellectual property is traceable is highly questionable. Even though access to data is arguably easier than ever before, the value of personal data will increase even more when used in AI development, so the future can only be imagined where data turns out to be the strongest currency. While Apple's AI tools present one vision of what responsibly using data looks like, some of the critical challenges in the larger tech landscape include privacy, consent, and IP. These are issues through which students growing up in this digital age need to find their way. Living in this kind of world, where literally everything runs on data, is important to know who controls it and how.