Conservative women are more attractive than left-wing females, according to a European study of thousands of faces. Danish and Swedish researchers tested a deep-learning artificial intelligence, called a neural network, that can predict a person's political leanings the majority of the time, based solely on their headshot. It found that right wing women more were attractive, based on a publicly available scoring system. The group found no such link in men, but did determine that the left-leaning men showed more neutral, less happy faces, suggesting perhaps better skill at guarding their emotions. The true purpose of the researchers' study, however, was to show the alarming accuracy of off-the shelf AI, which can correctly guess a person's political views based on limited information, like a simple selfie, posted to social media everyday.

Microsoft is restricting access to its facial recognition tools, citing risks to society that the artificial intelligence systems could pose. The tech company released a 27-page "Responsible AI Standard" on Tuesday that details the company's goals toward equitable and trustworthy AI. To align with the standard, Microsoft is limiting access to facial recognition tools in Azure Face API, Computer Vision and Video Indexer. "We recognize that for AI systems to be trustworthy, they need to be appropriate solutions to the problems they are designed to solve," wrote Natasha Crampton, chief responsible AI officer at Microsoft, in a blog post. She added the company would retire its Azure services that infer "emotional states and identity attributes such as gender, age, smile, facial hair, hair, and makeup."

A core priority for the Cognitive Services team is to ensure its AI technology, including facial recognition, is developed and used responsibly. While we have adopted six essential principles to guide our work in AI more broadly, we recognized early on that the unique risks and opportunities posed by facial recognition technology necessitate its own set of guiding principles. To strengthen our commitment to these principles and set up a stronger foundation for the future, Microsoft is announcing meaningful updates to its Responsible AI Standard, the internal playbook that guides our AI product development and deployment. As part of aligning our products to this new Standard, we have updated our approach to facial recognition including adding a new Limited Access policy, removing AI classifiers of sensitive attributes, and bolstering our investments in fairness and transparency. We continue to provide consistent and clear guidance on the responsible deployment of facial recognition technology and advocate for laws to regulate it, but there is still more we must do.

In this quickstart, you will use the Azure Face REST API with Node.js to detect human faces in an image. You can get a free trial subscription key from Try Cognitive Services. Or, follow the instructions in Create a Cognitive Services account to subscribe to the Face API service and get your key. Go to the folder where you'd like to create your project and create a new file, facedetection.js. Then install the requests module to this project.

The service provides algorithms, exposed as REST-based web service calls, to detect, verify, identify, and analyze faces. The service can provide face matching, face attributes, and characteristic analysis. The API also has capabilities for Face identification and recognition. This service also provides face-specific: landmarks(nose, eyes) & attributes (skin color, age, gender). Face Detection API: The face detection API provides information about detected faces in an image but isn't designed to identify or recognize a specific face.

The Face API can detect human faces in an image and return the rectangle coordinates of their locations. Optionally, face detection can extract a series of face-related attributes such as pose, gender, age, head pose, facial hair, and glasses. The face detection feature is also available through the Computer Vision API, but if you wish to do further operations with face data, you should use the Face API (this service). You can get a free trial subscription key from Try Cognitive Services. Then add the following code inside the body element of the document.

The American Civil Liberties Union (ACLU) is pressing forward with a lawsuit involving the facial recognition software offered by Amazon and Microsoft to government clients. In a complaint filed in a Massachusetts federal court, the ACLU asked for a variety of different records from the government, including inquiries to companies, meetings about the piloting or testing of facial recognition, voice recognition, and gait recognition technology, requests for proposals, and licensing agreements. At the heart of the lawsuit are Amazon's Rekognition and Microsoft's Face API, both facial recognition products that are available for customers of the companies' cloud platforms. The ACLU has also asked for more details on the US government's use of voice recognition and gait recognition, which is the automated process of comparing images of the way a person walks in order to identify them. Police in Shanghai and Beijing are already using gait-analysis tools to identify people.

The Grey Matter Managed Services team are experts at managing Azure-related projects, including Cognitive Services. You can contact them on 44 (0)1364 654100 to discuss Azure and Visual Studio options and costs, or if you require technical advice.

Roundup Hello, here are a few bits of AI news for the weekend. You don't always need a ton of cash to buy a wad of GPUs to train your models super quickly. You can do it pretty cheaply on cloud platforms. There's also a robot that can play Where's Waldo (Wally in the UK), and Microsoft's computer that is trying to tell if you've found a joke funny. Public code for training ImageNet super quickly: A group of engineers have managed to train ImageNet to 93 per cent accuracy using hardware rented on public cloud platforms for just $40.

Microsoft Azure is a cloud computing service that has its own machine learning service, known as Cognitive Services. It is split into five categories: Vision, Speech, Language, Knowledge, and Search, with each category containing several tools, for a total of 26. Under Vision, there are six tools: Computer Vision, Content Moderator, Custom Vision Service, Emotion API, Face API, and Video Indexer. As the title suggests, the focus here is on the Face API tool. With Face Identification, you must first create a PersonGroup object.