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Microsoft facial recognition tool is no longer able to read emotions

Microsoft is shutting down a controversial facial recognition feature that claims to identify emotions in people’s faces from videos and photos.

As part of a review of its AI policy, the US tech giant is removing facial analytics capabilities that infer emotional states, such as surprise and anger, from Azure Face.

It also stops the technology platform’s ability to identify characteristics such as gender, age, smile, hair and makeup.

Microsoft’s Azure Face is a developer service that uses AI algorithms to detect, recognize, and analyze human faces in digital images.

It is used in scenarios such as identity verification, contactless access control and face blur for privacy.

Starting this week, Microsoft will discontinue Azure Face capabilities that 'distract emotional states', such as surprise and anger, based on facial expressions

Starting this week, Microsoft will discontinue Azure Face capabilities that ‘distract emotional states’, such as surprise and anger, based on facial expressions

WHAT IS AZURE FACE?

Microsoft’s Azure Face service for developers provides AI algorithms that detect, recognize, and analyze human faces in digital images.

Facial recognition software is important in many different applications, such as identity verification, contactless access control, and facial blurring for privacy.

According to Microsoft, Azure Face allows developers to embed facial recognition in apps “for a seamless and highly secure user experience.”

The company says: “Features include facial detection that detects facial features and attributes — such as a face mask, goggles or facial location — in an image, and identification of a person through an agreement with your private repository or through a photo ID.

“No machine learning expertise is required.”

In a blog postNatasha Crampton, Microsoft’s responsible AI officer, said the decision follows “heightened privacy concerns” about the technology.

“In order for AI systems to be reliable, they must be appropriate solutions to the problems they are designed to solve,” she said.

“We have decided that we will not provide open-ended API access to technology that can scan people’s faces and pretend to infer their emotional state based on their facial expressions or movements.

“Experts inside and outside the company have pointed to the lack of scientific consensus on the definition of ’emotions’.”

Crampton said inferring emotions from facial expressions alone can be too general across use cases, regions and demographics.

For example, a smile can infer sarcasm or indicate a greeting, rather than just inferring happiness.

A study 2019led by Professor Lisa Feldman Barrett, a psychologist at Northeastern University, pointed out that “how people communicate anger, disgust, fear, happiness, sadness, and surprise varies considerably across cultures, situations, and even between people within a single situation.”

So apps that rely on inferring emotions from faces can be inaccurate, impacting national security protocols, policy decisions, and even legal rulings depending on usage.

Microsoft's Azure Face service provides AI algorithms that detect, recognize, and analyze human faces in videos and images

Microsoft’s Azure Face service provides AI algorithms that detect, recognize, and analyze human faces in videos and images

Microsoft is not stopping Azure Face completely. But starting Tuesday (June 21), it will stop Azure Face capabilities that infer emotional states, such as surprise and anger, based on facial expressions.

As of Tuesday, emotional state detection and these other personal characteristics, such as gender and age, will no longer be available to new customers.

Existing customers have until June 30, 2023 to stop using these attributes on their platforms before the attributes are discontinued, the company said.

Azure Face keeps others facial recognition use cases for its developers, but new customers must request access.

The tech firm in Redmond, Washington detailed its Responsible AI Standard, a lengthy document guiding the development and implementation of AI products

The tech firm in Redmond, Washington detailed its Responsible AI Standard, a lengthy document guiding the development and implementation of AI products

Also, existing customers have one year to sign up and get approval for continued access to the facial recognition services, while explaining what they’re using it for.

So as of June 30 next year, these existing customers will not be able to access facial recognition capabilities if their application is not approved.

Some less controversial use cases available in Azure Face, such as detecting blurriness, remain widely available and require no application.

The changes are all part of a major overhaul of the company Responsible AI standardwhich it has just been shared publicly.

The lengthy document is a “framework” to guide the company in building better and more reliable AI systems.

“The standard describes concrete goals or outcomes that teams developing AI systems should strive for,” Crampton said.

‘These goals help break down a broad principle like ‘accountability’ into key factors such as impact assessments, data governance and human oversight.’

HOW DOES FACE RECOGNITION TECHNOLOGY WORK?

Facial recognition software works by matching images in real time with a previous photo of a person.

Each face has about 80 unique nodes across the eyes, nose, cheeks and mouth that distinguish one person from another.

A digital video camera measures the distance between various points on the human face, such as the width of the nose, depth of the eye sockets, distance between the eyes and shape of the jawline.

Another smart surveillance system (pictured) has been unveiled in China that can scan 2 billion faces in seconds.  The system connects to millions of CCTV cameras and uses artificial intelligence to select targets.  The military is working on applying a similar version of this with AI to track people across the country

Another smart surveillance system (pictured) has been unveiled in China that can scan 2 billion faces in seconds. The system connects to millions of CCTV cameras and uses artificial intelligence to select targets. The military is working on applying a similar version of this with AI to track people across the country

This produces a unique numerical code that can then be matched with a matching code from a previous photo.

A facial recognition system used by officials in China connects to millions of CCTV cameras and uses artificial intelligence to select targets.

Experts believe that facial recognition technology will soon overtake fingerprint technology as the most effective way to identify people.

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