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    Microsoft restricts US police form using its Azure OpenAI Service for facial recognition

    In an update to its code of conduct, Microsoft has restricted the use of Azure OpenAI Service integration “for facial recognition purposes by or for a police department in the United States”. Microsoft has also prohibited the integration of Azure OpenAI Service for any real-time facial recognition technology on mobile cameras used by any law enforcement globally to attempt to identify individuals in uncontrolled, “in the wild” environments.

    This includes the use of Azure OpenAI service by police officers on patrol using body-worn or dash-mounted cameras using facial recognition technology to attempt to identify individuals present in a database of suspects or prior inmates. Interestingly, while police departments in the US have been completely restricted from using the service for facial recognition services, the same has not been applied on a global scale.

    Prior to the update, the code of conduct stated that Azure OpenAI Service “prohibits identification or verification of individual identities using media containing people’s faces by any user, including by or for state or local police in the United States”. This code of conduct had no mention of global law enforcement agencies.

    Some context:

    This isn’t the first time that Microsoft has restricted the use of facial recognition technology by the US police. In 2020, the then president of the company, Brad Smith, said that Microsoft would not sell its facial recognition technology to police departments in the US until there is a federal law grounded in human rights regulating its use. However, unlike its stance in 2020, the company is now also prohibiting the use of this technology by other law enforcement agencies globally, albeit only for real-time monitoring. It must also be noted that despite Microsoft’s stance on facial recognition, the company has reportedly sold its facial recognition software to at least one American prison in the past.

    Why it matters:

    While law enforcement agencies might consider facial recognition an effective way to curb crime, studies have shown that facial recognition only gives an 80 percent accuracy when matching faces. There have been several instances where this technology has wrongly identified individuals. For instance, in 2022, a Noida-based businessman travelling to Switzerland was wrongly detained by the UAE authorities in Abu Dhabi because the facial recognition software they were using ended up matching his face to that of a wanted criminal.

    The use of AI-powered facial recognition systems can exacerbate several issues and raise additional concerns beyond the general inaccuracies and biases associated with facial recognition systems. AI models have been known to act in a biased manner because of the training data used to develop them. A discussion conducted by UNESCO in July last year, discussed how AI models suffer from a “white guy problem”. The speakers in the discussion gave the example of AI-enabled drowsiness detection systems arguing that the data used to create them could wrongfully consider someone with drooping eyelids to be asleep at the wheel.

    Other key additions to the code of conduct:

    The code of conduct adds that Azure OpenAI service integration must not:

    • use subliminal techniques beyond a person’s consciousness;
    • use purposefully manipulative or deceptive techniques with the objective or effect of distorting the behaviour of a person by impairing their ability to make an informed decision
    • exploit any of the vulnerabilities of a person (e.g., age, disability, or socio-economic situation)
    • categorize people based on their biometric data to infer characteristics or affiliations about them such as race, political opinions, trade union membership, religious or philosophical beliefs, or sex life or sexual orientation

     


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    Also read:

    The post Microsoft restricts US police form using its Azure OpenAI Service for facial recognition appeared first on MediaNama.

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