The economy of big data — and the machine learning algorithms that feed on it — have been a gift to the leading cloud computing companies. By drawing data-intensive tasks into their massive, centralised facilities, companies such as Amazon, Microsoft and Google have thrived by bringing down the unit costs of computing.
But artificial intelligence is also starting to feed a very different paradigm of computing. This is one that pushes more data-crunching out to the network “edge” — the name given to the many computing devices that intersect with the real world, from internet-connected cameras and smartwatches to autonomous cars. And it is fuelling a wave of new start-ups which, backers claim, represent the next significant architectural shift in computing.
There is a strategic conclusion to be drawn from the allegations that Cambridge Analytica misused data from 50m Facebook users. The economic and social benefits promised by the age of data, which are only just beginning to be realised, are far too important to be left to technology companies.
Governments must intervene to build trust in the use of data, but in ways that promote rather than stifle private sector and academic innovation.
In several respects, Europe’s General Data Protection Regulation is a terrible piece of legislation. Having been so long in the making, it appears outdated even before it comes into effect on May 25. The GDPR is also overly sweeping in scope and largely unenforceable in practice. That is not a great look for what has been billed as a landmark law intended to resound around the world.
Yet, in spite of its manifest flaws, the regulation has already achieved one invaluable goal. It has forced us to focus on how we treat the most valuable assets of our digital age: data. The law’s main aim is clear: to compel all organisations to be more transparent and accountable in their use of personal data and to give consumers greater control and choice.