The article Doctolib wants to train AI models with user and health data training Maria Gramsch first appeared on Basic Thinking. You always stay up to date with our newsletter.
The IT service provider Doctolib has adapted its data protection guidelines and wants to train AI models using user data in the future. The background.
In the doctor’s office, the phone is constantly occupied or just nobody decreases? Many patients have probably experienced this scenario one time or another.
More than a third of the Germans Therefore, it is therefore happy to fall back on the online appointment service, which numerous medical practices now offer. The Docolib platform, which comes from France, is often used.
Use in Germany According to the company In the meantime, 20 million people Doctolib, for example to make medical dates. Numerous user data will also come together that the IT service provider wants to use in the future to train AI models.
What data does Doctolib use for its AI models?
Doctolib has already published its updated data protection information. These should come into force from February 22nd. In it, the company relies on its legitimate interest as the person responsible for processing.
In the future, user data such as gender, month of birth and year of users should be included in the AI training. The answers to voluntary surveys of the platform as well as feedback from users for video consultation.
In an email to user, Doctolib writes that the company develops “continuously new data and AI-based products”. This includes, among other things, memories of recipe renovations or new functions in patient news.
Further information on the changes should receive users in a timely manner in their accounts. “There you also have the opportunity to give your consent,” the email continues.
Are health data also used?
In Doctolib’s updated data protection information, the use of personal health data states that the “express consent of the user” is obtained for this.
Doctolib also lists here which health data will be about. Among other things, the company wants to use medical information entered for the training of AI models, medical notes or the user on the platform.
But health data, which were collected by health specialists as part of the use of the Doctolib services, can also be included here.
Doctolib and his AI efforts
For some time now, Doctolib has been trying to gain a foothold in artificial intelligence. The company has already taken over two AI companies for this last year.
On the one hand, this includes that Company aaron.aithat offers a AI-based telephone assistant. But also the one specialized in speech recognition in the medical field Company Typeless has been part of Doctolib since 2024.
With the takeover of Typeless, Doctolib had also announced the introduction of a digital medical assistant for the end of 2024. However, this has not yet been published.
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The article Doctolib wants to train AI models with user and health data training Maria Gramsch first appeared on Basic Thinking. Follow us too Google News and Flipboard.
As a Tech Industry expert, I believe that Doctolib’s plan to train AI models with user and health data has the potential to revolutionize the healthcare industry. By utilizing AI technology, Doctolib can analyze vast amounts of data to identify patterns and trends that can improve patient care, diagnosis, and treatment.
However, it is crucial for Doctolib to prioritize data privacy and security when collecting and using this sensitive information. They must adhere to strict regulations and guidelines to ensure that user data is protected and used responsibly.
Furthermore, transparency with users about how their data is being used and giving them the option to opt out if they choose is essential. Building trust with users is key to the success of any AI-driven healthcare initiative.
Overall, if done ethically and responsibly, training AI models with user and health data has the potential to greatly benefit patients, healthcare providers, and the industry as a whole. It is an exciting development that could lead to more personalized and effective healthcare solutions.
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