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Cambridge Analytica scandal one year on – the key takeaways 

A year on from this scandal and we are beginning to see data privacy regulations such as the EU’s GDPR and California’s CCPA rolled out across a variety of countries. These regulations are set to change how companies build data and AI applications and services – and for the better.
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Cambridge Analytica was not a data ‘breach’ – it was ‘bulk data sharing’. Whilst this may seem like a big statement to make, we now know that this came down to a lack of disclosure. Contributor Ben Lorica, Chief Data Scientist – O’Reilly Media.

Not only was user data made available through a programme for Facebook developers, copies of the data were stored in the hands of programme participants. Enter – Cambridge Analytica’s easy access to large volumes of data users weren’t even aware they’d given away.

A year on from this scandal and we are beginning to see data privacy regulations such as the EU’s GDPR and California’s CCPA rolled out across a variety of countries. These regulations are set to change how companies build data and AI applications and services – and for the better.

Not only this, but we’re seeing changes in users’ attitudes towards their data. Awareness is now higher among a growing number of users and an increasing number of them are calling for better transparency over what data is being collected and for greater control over how their data is used and shared. It’s not just users fearful of falling victim to an affair like this who are beginning to change their attitude towards data sharing, but companies too.

More and more companies are signalling that they take data privacy and the concerns of their users and regulators seriously. The stance companies take on data privacy and data monetisation is becoming a competitive angle for some small and large firms. Apple is a great example of a company raising the bar on data privacy and collection, with more companies beginning to follow suit.

With the volume of data available only set to rocket and opportunities to build more data products increasing, users and regulators need to be more aware as we move forward.

“If companies continue to depend on the same business models, data collection will continue and with that – the potential for misuse. We must take data privacy more seriously – and tools like machine learning and AI can help to do this. AI can help existing security teams to be more efficient, and effective, with more AI tools beginning to appear in the cybersecurity space. It’s time for companies to develop strategies that put privacy first”.

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