AI, machine learning and personal data

3 Mar 2017 01:07 PM

Blog posted by: Jo Pedder, Interim Head of Policy and Engagement, 03 March 2017.

AI, machine learning and personal data

Today sees the publication of the ICO’s updated paper on big data and data protection.

But why now? What’s changed in the two and a half years since we first visited this topic? Well, quite a lot actually:

The complexity and opacity of these types of processing operations mean that it’s often hard to know what’s going on behind the scenes. This can be problematic when personal data is involved, especially when decisions are made that have significant effects on people’s lives. The combination of these factors has led some to call for new regulation of big data, AI and machine learning, to increase transparency and ensure accountability.

In our view though, whilst the means by which the processing of personal data are changing, the underlying issues remain the same. Are people being treated fairly? Are decisions accurate and free from bias? Is there a legal basis for the processing? These are issues that the ICO has been addressing for many years, through oversight of existing European data protection legislation.

When the General Data Protection Regulation (GDPR) comes into force in 2018, the regulatory toolkit will be further sharpened. Some of the key changes will be:

These changes, and more, will contribute towards a relevant and effective regime for the regulation of personal data in the world of big data, AI and machine learning.

The paper we are publishing today takes these changes into account and gives our views on the implications both now and moving forward. For those involved in big data, the paper also offers some practical advice on tools and approaches that can help to meet and go beyond compliance with data protection legislation. There’s also some specific guidance on undertaking privacy impact assessments – a valuable tool in a big data context and one which the ICO has championed for many years now.

As a final point, this paper does not mark the end of our work on big data. Far from it. We have a number of key work-streams which are related to and will continue our work in this area, a brief taster of which is summarised below. Watch this space.