AI, the governance of data and the protection thereof

POPIA, or the Protection of Personal Information Act, Act 4 of 2013, is a new law which is in place and must be followed by most, if not all, organisations. The difference between POPI and POPIA lies in the action towards protecting personal information.

POPI is associated with the policies, procedures, processes, and practices which relate to personal information while POPIA involves a POPI programme.

Why is Data Governance important?

With advancements in technology more personal data is being used to improve customer experience in the prediction of needs, demands, and several other factors. People are providing more sensitive data and information to have technological innovations which make life easier.

Technology has gone from a side-line contributor, to being the core of businesses and this has created substantial amounts of tension and new levels of responsibility in various organisations who make use of such personal data.

While compliance and governance are not the same thing, they both work towards a common goal. Compliance is merely the implementation of mandated laws, while governance is associated with voluntary good practice.

Governance, risk, and compliance are often referred to as the Three Sisters. There must be a structure, model, or at the very least, a hierarchy of people who deal with data and the governance thereof as it is the foundation for obtaining the best from data.

Data governance and the necessary regulations, laws, processes, and other particulars in place, are not only there to deter the misuse or abuse of personal data, but it is also in place to protect people against hackers who seek such information for malicious purposes.

AI and POPI/A

Artificial Intelligence makes great use of personal data and with the rapid evolution of AI alongside improvements in computing power which have led to a rapid increase in the availability of data, organisations have to ensure that they are POPIA compliant.

Machine Learning has greatly driven AI in recent years and this process is fuelled by the collection of data which allows AI to analyse large data volumes in a sophisticated manner.

With an increase in data collection as machines learn, adapt, develop, and grow, the legal issues surrounding the data being collected has increased substantially as well.

Although businesses are free to use certain data which is captured and held for specific purposes such as AI algorithms, there is however data which is not free to use, especially when it concerns personal data.

Should personal data be used to train or test AI algorithms, the processing thereof must be in a fair and lawful manner so that data protection laws are complied with.

Data used in AI algorithms are often from a third party source and therefore confidential or provided according to a limited license, which means that such data also needs to be protected and must be accessible by the third party at all times.

Can the protection of personal data be ensured?

AI must be used responsibly, and therefore the data used in these complex algorithms must be protected at all times. This is an important step towards the wide acceptance of AI on a global scale.

Trust must be built in AI for the successful and responsible development and deployment thereof, including accountability and transparency.

Mitigating the risks and ensuring compliance and governance of data

The risks of data being exposed need to be taken into consideration so that they can be managed to prevent the misuse, abuse, and theft of data. Governance is, for the greater part, concerned with control and oversight.

Compliance entails following the law and a lot of businesses deal with compliance if and when risks become critical while they mainly focus on the governance of data. Finding the right balance between the Three Sisters is key for any business.

Governance, risk, and compliance must be scrutinised continuously and adjusted as a part of business development, growth, and evolution. They must be considered as the practical foundations for any transformation strategy.

Final Thoughts

AI is, undeniably, a part of everyday life in a variety of ways that people may not be distinctly aware of.

To ensure the improvement and further development of AI, and Machine Learning, to even more efficiently catering for the needs of humans, more personal data is necessary to drive these processes forward.

There are great opportunities for AI and AI systems for a more technologically advanced world and organisations must take great care in ensuring that personal data is not only protected, but governed, and that risks are mitigated and managed, and compliance can be ensured.

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