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31 October 2024

Data protection-friendly AI training (glossary)

Artificial intelligence Digital society Automation Cybercrime and cybersecurity Digital transformation AI Glossary

Privacy-friendly AI training is particularly important in the areas of artificial intelligence, digital society and cybercrime and cybersecurity. The term describes methods in which artificial intelligence (AI) is "trained" in such a way that the protection of personal data is maintained at all times.

In order for an AI to learn, large amounts of data are often used, for example images, texts or customer data. In data protection-friendly AI training, however, this data is processed in such a way that it cannot be traced back to individual persons. This means that personal information such as names, addresses or sensitive details are removed, anonymised or not processed at all.

An illustrative example: A supermarket wants to use an AI to better understand shopping habits. However, instead of using individual customer data such as name or account number, the supermarket processes the data before training the AI in such a way that no personal identification is possible - for example by summarising data or omitting sensitive information.

Data protection-friendly AI training ensures that companies can develop innovative solutions without violating data protection laws or jeopardising the trust of their customers.

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Data protection-friendly AI training explained: Find out now how to use AI securely and in compliance with data protection regulations!

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Sanjay Sauldie

Sanjay Sauldie is a digital strategist, speaker and developer of the transruption toolkit, which companies can use to make their digital transformation measurable, human and sustainable. With kiROI - the AI-based approach to value creation in the digital age - he helps self-employed people and companies to integrate artificial intelligence into their processes in a practical way. With his outstanding marketing strategy iROI, he has already led countless companies to greater visibility and thus more profits. He combines digital innovation with disruptive thinking models for a sustainable business strategy. He studied mathematics and computer science at the University of Cologne, completed a Master of Science in Digital Disruption at the University of Salford (UK) and a Design Thinking programme at MIT/EMERITUS Singapore. As a multiple award-winning expert - including the Golden Web Award and the Innovation Award of the Initiative Mittelstand - he advises SMEs and corporations. His motto: "Digitalisation is not an end in itself - it must serve people."

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