It is essential that data subjects can understand why and how data is stored by a business. With the use of AI systems to process data, a business needs to make it easy to understand the insight and specifics of how AI systems go about the job of collecting and processing data. This includes an understanding of the input, output, and the building blocks that create the algorithm that contributes to the outcome of the system. As data subjects, you have the right to be informed in a timely and precise manner, and for businesses there is a need to deploy AI systems in an explainable way.
The benefits of AI for data processing
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AI has the ability to analyse and process large datasets with speed and accuracy. This makes it an attractive and, often, an essential part of a business dealing with a large silo of data to process. Privacy is vital though, as it could be open to abuse should there not be strict protocols to manage AI data processing. For any business there is a real need to offer explainable AI benefits, enhancing privacy protection for personal data in a clear, transparent way.
Transparency obligations for AI data processing
The EU General Data Protection Regulation (GDPR) includes obligations of transparency for controllers of AI technology as well as manual data processing. In fact, transparency is one of the key overarching obligations within GDPR, and it applies to a few different areas. The first is that there is fair processing of data and provision of information to data subjects about that processing. There is also an obligation for AI data controllers to be as clear and concise as possible in communicating with data subjects about their individual rights relating to stored data under the UK/GDPR. Within this process controllers must be clear to data subjects on how they can facilitate the exercise of these rights in practice, should the need arise.
AI explainability is the right to be informed as set out by the EU and UK GDPR principles of accountability and transparency. Within these regulations you can see how it is important for clarity and transparency when processing personal data. Data controllers have a responsibility to be as clear as possible when processing data. When you then talk about controllers of AI technology and how this is used to automate certain parts of data processing, there is an importance to get this right.
The importance of AI explainability
There is a clear importance stressed by both the UK and EU GDPR when it comes to the explainability of AI use within data processing. It is vital that individuals have a clear understanding of how their data is being collected, stored, and processed by AI algorithms. Any business that utilises AI technology to help process data must therefore have the relevant documentation that details exactly how and why data is being processed by the company.
How does AI explainability work in practice?
In practice, data controllers should provide a written explanation of data processing, with information based on two sub-categories:
Processed-based explanation – this should provide all relevant information about the governance of AI systems and how they are deployed across the different phases of a project. This shows that a business has followed best practice and has implemented the best governance over the data processing processes in place.
Outcome-based explanation – this is a requirement to give clarity behind the results of a decision. Data controllers should explain any reasoning behind the decision that has been generated by an algorithm. This should be in a way that data subjects can understand in simple terms.
It is much better for data controllers to be as up front as possible about the reasons behind the use of AI in these circumstances. If individuals feel that the purposes of the data processing is unclear, you should provide an indication as to what will be done with their data. As policies are updated over time and there is more clarity about the purpose of the data processing, communicate this with the data subjects to keep them updated. The same should be done when new uses of personal data are being planned, always update the data subjects of the upcoming changes.
AI explainability is essential to data controllers where the processing of data is being processed by AI algorithms and processes. Explaining how and why certain processes and decisions are taken is vital and putting these explanations in a way that is simple and easy for data subjects to understand will help a business to stay within the boundaries of UK and EU GDPR regulations. A solid explanation framework is essential to respect the principles of fairness and transparency.