Federated AI falls into the categories of artificial intelligence, big data, smart data, cybercrime and cybersecurity. This term describes a special way in which artificial intelligence (AI) works with large amounts of data without the data having to be collected in a central location.
Instead of storing all data on a server, many individual computers or devices each learn from their own data. The results or "learning progress" are then merged without sharing the sensitive original data. This increases security and protects personal information, for example.
A typical example: several hospitals want to jointly train an AI to diagnose diseases. However, due to data protection regulations, the patient data may not be stored centrally. With Federated AI, each hospital can train the AI with its own data. Afterwards, only the newly gained insights, not the actual patient data, are shared and merged.
Federated AI makes it possible to use modern AI solutions in sensitive areas such as healthcare or finance without jeopardising data protection and security. This is a major advantage, especially in times of increasing cybercrime.
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