AI in home surveillance could be 'very dangerous'

Researchers have found that AI home surveillance systems operate completely randomly. But the reasons for this remain unclear due to a lack of transparency. Backgrounds.

one New study from MIT Penn State University shows that using AI for home surveillance can lead to major problems. Language models like GPT-4 are inconsistent and therefore behave unpredictably. They often recommend calling the police even when there is no obvious criminal activity. This inconsistency can be dangerous.

Even more problematic is that the models react differently to similar scenes. For example, one video showed a car being stolen and the model raised the alarm, while a similar video did not respond at all. These differences raise questions about the reliability of AI. This can have serious consequences, especially in sensitive situations.

AI Bias in Home Monitoring

Another problem lies in the way the algorithm thinks. Because the AI ​​exhibits unconscious biases, it was less likely to raise alarms in predominantly white neighborhoods, even when similar activity was seen in other areas. This suggests that the AI ​​is influenced by demographic differences. However, the exact reasons are unclear, because model training data is often not publicly available.

These biases can have serious consequences in this area. It is impossible to predict how many people may be unfairly treated as a result. However, it has become clear that caution must be exercised when using AI in sensitive areas.

Caution is needed

The study’s findings highlight the risks associated with using AI for home surveillance. That’s why you shouldn’t blindly trust the technology. It takes more transparency and control. That’s the only way to ensure that AI works fairly and reliably.

Meanwhile, the future of home surveillance could be greatly influenced by AI. But before the technologies can be used in everyday life, it needs to be verified that they actually work.

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