Meta Ai in WhatsApp: Help or disorder? This is how it goes!

Meta Ai in WhatsApp: Help or disorder? This is how it goes!

Kosmo, Österreich - The new AI assistant of Meta, known as Meta AI, was integrated into WhatsApp at the end of March 2025 and offers a variety of functions to make life easier for users. According to Kosmo not only answers questions, but also generates images and supports in everyday tasks. Users can reach META AI via a blue circle in the chat overview, whereby the addition "@meta ai" is necessary in group chats. These functions are available in both individual and group discussions.

META AI accesses current internet data to answer specific user inquiries. His other skills include the creation of texts and translations in different languages as well as the generation and processing of images and short videos according to the requirements of the users. The assistant can also give personalized recommendations for restaurants, excursions and leisure activities and act as a memory aid for upcoming appointments. It is particularly noteworthy that Meta Ai also understands Swiss German.

data protection concerns and user experiences

Despite the practical functions, there are several criticisms that primarily affect data protection. Critics express concerns that user data may be used unintentionally to the further development of the AI. Interactions with META AI do not enjoy protection through the end-to-end encryption, which could potentially lead to details from private chats. The fact that the complete deactivation of Meta AI in WhatsApp is currently not possible is annoyed by many users who find the constant presence of this tool disturbing.

users have the option of archiving or deleting the Meta-AI chat to remove it from the chat list. It is important to note that these measures are only temporary and do not actually deactivate the assistant.

technical aspects and the future of KI

The performance of AI systems such as the META AI depends heavily on the quality of the training data used. According to itransition , careful data assignments and the integration of diversified training rates are crucial for the development of reliable AI models. In particular, taking into account the user base of social media plays a central role in avoiding algorithmic distortions.

In addition, the phenomenon of the model drift, which describes a deterioration in model output over time, becomes increasingly relevant. In order to counteract this, it is necessary to integrate special metrics and regularly carry out retaining editing edits with new data. AI systems, especially those based on deep neuronal networks, also require human supervision and should be used conscientiously and limited.