What GDPR Compliance Should You Be Aware of When Deploying an ML Programme?

If you’re using AI technology, it is important to remain aware of GDPR compliance. Click here to find out what compliance your AI needs to follow.

‘Artificial’ and ‘intelligence’ are the two words that every digital marketer loves in 2023. For businesses around the world, implicating AI and ML programs into their systems is not only a way to boost their speed, efficiency, and reliability, but it’s also something to capture the imagination of the consumer and demonstrate that you are ahead of the trend.

But there is a bit of a problem with this. Because AI is such a hot topic in the business world, there are a number of businesses that are integrating the tech without the ability to appropriately regulate it. This can lead to a lot of problems down the line, with the most significant being the failure to follow GDPR compliance.

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What Is GDPR Compliance?

The general rule is that, if your company harnesses and uses personal data, then you will need to follow GDPR compliance. This includes lawfulness, transparency, fairness, data minimisation, integrity, accuracy, confidentiality, and accountability.

With this in mind, if you are utilising an ML programme to analyse and apply data, your ML tech needs to follow GDPR compliance if you want to avoid any damaging reprimands.

What Specific GDPR Compliance Should You Be Aware Of?

As a company dealing with data, you need to be familiar with the full rulebook of GDPR compliance. But when it comes to your ML programme specifically, there are five key aspects that apply:

• Fairness
• Transparency
• Accuracy
• Accountability
• Data Minimal

This is why the concept of responsible AI is so important. For those unaware, responsible AI is AI and ML tech that has been developed and deployed to champion fairness, ethicality and legality. This can be achieved through an AI platform that can ensure observability, integrity and transparency throughout the AI structure.

With a solid AI platform, you can also eradicate one of the key issues circulating the world of AI today: bias.

Even during its relatively short reign in the mainstream, there has been a growing concern about ML programmes harnessing and using data that is systemically prejudiced – and because ML technology learns as it goes along, this can lead to a programme that is inherently biased with data. This will not only become detrimental to your own company, but it will also ensure that your ML programme does not pass GDPR compliance.

The Key Takeaway

Transparency is the most significant term here. In order to ensure fairness, accuracy, accountability, and data minimisation, you need to have a transparent programme that you are in complete control of – machine learning will automate previously unautomated operations, so it’s integral this is achieved transparently.

As well as this, you as a business need to be completely transparent about how data is being used. Why are you collecting data, why are you analysing it, and what do you intend to do with it? This needs to be demonstrated on every level, and it can only be achieved by developing and maintaining a GDPR-friendly ML programme. So keep compliance in mind at every level and focus on building an ML business model that works.

I hope this tutorial helped you to know about What GDPR Compliance Should You Be Aware of When Deploying an ML Programme. If you want to say anything, let us know through the comment sections. If you like this article, please share it and follow WhatVwant on Facebook, Twitter, and YouTube for more Technical tips.

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