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Scraping personal data to train AI models: What does it mean for your business? 

By Francisco Arga e Lima

Last Updated 16/10/2024

Have you been keeping up with the latest developments on AI training and data use?

Tech giants like Meta, X (formerly Twitter), Google, and LinkedIn are under scrutiny for how they use personal data to train AI models.  With discussions around user consent and legitimate interest, data protection is a hot topic. But what does it mean for your business? Let’s break it down. 

The big picture on scraping personal data for AI training 

Tech companies are constantly looking for new ways to train their AI systems using personal data. Meta has recently resumed its AI training in the UK after working with the Information Commissioner’s Office on transparency requirements. X, under pressure from the Irish Data Protection Commission (DPC), has agreed to limit certain data processing. Google is also under investigation by the DPC for potentially failing to conduct a Data Protection Impact Assessment (DPIA). Even LinkedIn is being questioned for using U.S. user data in AI training without proper notice. 

These examples highlight a bigger issue: compliance with data protection laws is crucial for ethical AI development

If you are developing or implementing AI systems, this trend is something you can’t afford to ignore. For example, using personal data for AI training requires a legal basis under GDPR.  Failure to comply can result in fines, loss of trust, and reputational damage. 

Can you train your AI model with personal data? 

 Yes, you can. But you need to follow a few rules. Here’s what you should keep in mind: 

  • Data minimization and purpose limitation: You can’t use personal data just in case it might be useful.  Be clear about why you’re processing personal data and limit the amount to what’s necessary. 
  • Public data still needs a legal basis: X and LinkedIn’s reliance on publicly available data doesn’t exempt them from GDPR compliance, which is why legitimate interest or consent remains necessary.
  • Transparency isn’t enough: Meta and LinkedIn show that transparency is just the beginning. You also need to respect user rights, including their right to object. And it must be easy for them to do so.  

How to ensure compliance when training AI 

If you’re developing or using AI systems and you want to build trust and avoid compliance risks, here’s how to do it right: 

  • Conduct a DPIA:  Before using personal data for AI training, carry out a DPIA. It helps you identify risks and prove that your practices comply with GDPR and FADP. 
  • Check your legal bases: Whether you rely on consent or legitimate interest, make sure your data processing activities are legally sound. If you’re processing large amounts of personal data, consent is often the safest route. 
  • Be transparent and respect user rights:  Tell your users how their data is being used. Also, make sure they can opt out if they want to. 

Why compliance is key 

The recent cases involving Meta, X, Google, and LinkedIn highlight how serious these issues have become. Is your business prepared? Ensuring that your AI systems comply with data protection laws isn’t just about avoiding penalties — it’s about building trust and staying competitive in a privacy-focused market. 

Need help navigating these challenges? 

We can guide you in setting up the legal frameworks, conducting DPIAs, and ensuring your AI data practices are compliant and effective. 

Contact us today and let’s ensure your business stays ahead in the AI race while respecting user privacy. In today’s tech world, compliance isn’t just a requirement—it’s a strategic advantage. 

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