Marketing Scoops: dimensional

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The last big breakthrough in aviation when it comes to boarding your flight came in the early 2000s, with the arrival of eTicketing. But a new proposed overhaul of how you get on planes could shake things up in a much larger way. The International Civil Aviation Organization (ICAO), a United Nations agency that oversees international airline policy, has revealed plans for a digital travel credential……Continue reading….

By: Chris Morris

Source: Fast Company

Critics:

A facial recognition system is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image.

Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics. Because computerized facial recognition involves the measurement of a human’s physiological characteristics, facial recognition systems are categorized as biometrics.

Although the accuracy of facial recognition systems as a biometric technology is lower than iris recognition, fingerprint image acquisition, palm recognition or voice recognition, it is widely adopted due to its contactless process. Facial recognition systems have been deployed in advanced human–computer interaction, video surveillance, law enforcement, passenger screening, decisions on employment and housing and automatic indexing of images.

Facial recognition systems are employed throughout the world today by governments and private companies. Their effectiveness varies, and some systems have previously been scrapped because of their ineffectiveness. The use of facial recognition systems has also raised controversy, with claims that the systems violate citizens’ privacy, commonly make incorrect identifications, encourage gender norms and racial profiling, and do not protect important biometric data.

The appearance of synthetic media such as deepfakes has also raised concerns about its security. These claims have led to the ban of facial recognition systems in several cities in the United States. Growing societal concerns led social networking company Meta Platforms to shut down its Facebook facial recognition system in 2021, deleting the face scan data of more than one billion users. The change represented one of the largest shifts in facial recognition usage in the technology’s history.

IBM also stopped offering facial recognition technology due to similar concerns.The emerging use of facial recognition is in the use of ID verification services. Many companies and others are working in the market now to provide these services to banks, ICOs, and other e-businesses. Face recognition has been leveraged as a form of biometric authentication for various computing platforms and devices; Android 4.0 “Ice Cream Sandwich” added facial recognition using a smartphone’s front camera as a means of unlocking devices.

While Microsoft introduced face recognition login to its Xbox 360 video game console through its Kinect accessory, as well as Windows 10 via its “Windows Hello” platform (which requires an infrared-illuminated camera). In 2017, Apple’s iPhone X smartphone introduced facial recognition to the product line with its “Face ID” platform, which uses an infrared illumination system. Face recognition is less effective if facial expressions vary. A big smile can render the system less effective.

For instance: Canada, in 2009, allowed only neutral facial expressions in passport photos. There is also inconstancy in the datasets used by researchers. Researchers may use anywhere from several subjects to scores of subjects and a few hundred images to thousands of images. Data sets may be diverse and inclusive or mainly contain images of white males. It is important for researchers to make available the datasets they used to each other, or have at least a standard or representative dataset.

Although high degrees of accuracy have been claimed for some facial recognition systems, these outcomes are not universal. The consistently worst accuracy rate is for those who are 18 to 30 years old, Black and female.^[5Civil rights organizations and privacy campaigners such as the Electronic Frontier Foundation, Big Brother Watch and the ACLU express concern that privacy is being compromised by the use of surveillance technologies.

Face recognition can be used not just to identify an individual, but also to unearth other personal data associated with an individual – such as other photos featuring the individual, blog posts, social media profiles, Internet behavior, and travel patterns. Concerns have been raised over who would have access to the knowledge of one’s whereabouts and people with them at any given time. Moreover, individuals have limited ability to avoid or thwart face recognition tracking unless they hide their faces.

This fundamentally changes the dynamic of day-to-day privacy by enabling any marketer, government agency, or random stranger to secretly collect the identities and associated personal information of any individual captured by the face recognition system. Consumers may not understand or be aware of what their data is being used for, which denies them the ability to consent to how their personal information gets shared.

In 2016, facial feature emotion recognition algorithms were among the new technologies, alongside high-definition CCTV, high resolution 3D face recognition and iris recognition, that found their way out of university research labs. In 2016, Facebook acquired FacioMetrics, a facial feature emotion recognition corporate spin-off by Carnegie Mellon University. In the same year Apple Inc. acquired the facial feature emotion recognition start-up Emotient.

By the end of 2016, commercial vendors of facial recognition systems offered to integrate and deploy emotion recognition algorithms for facial features. The MIT’s Media Lab spin-off Affectiva by late 2019 offered a facial expression emotion detection product that can recognize emotions in humans while driving.

Face Recognition based Smart Attendance System Using IoT”

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Facial Recognition Technology: Federal Law Enforcement Agencies Should Have Better Awareness of Systems Used By Employees”.

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Understanding bias in facial recognition technologies

Study warns deepfakes can fool facial recognition”.

IBM bows out of facial recognition market -“.

Facebook, Citing Societal Concerns, Plans to Shut Down Facial Recognition System”.

IBM will no longer offer, develop, or research facial recognition technology”.

The Quest for Artificial Intelligence.

Mugspot Can Find A Face In The Crowd – Face-Recognition Software Prepares To Go To Work In The Streets”.