How To Activate Face Id For Ocbc App

[Germaine Greenweig]

Facialrecognition is everywhere. What once started as an attribute specific to sci-fi movies is now a part of everyday life: we rely on facial recognition every time we unlock our phones or go through customs.

Along with gaining market volume, facial recognition algorithms are becoming more sophisticated. At the same time, they have been subject to numerous ethical concerns, amplified by reported uses of the technology for racial profiling and protester identification.

Detection refers to the process of locating a face in an input image. So, each face is placed into a bounding box. To complete this stage, the facial recognition algorithms are first trained to learn what a face looks like from various data entries.

Applications of facial recognition for patient tracking have high patient acceptance rates. Research published on Plos One states that almost 66% of patients find it acceptable for hospital systems to scan their faces for identity verification.

One example of such technology comes from ALCHERA, an AI-powered visual recognition firm. The company offers a facial recognition solution that helps hospitals streamline admission and discharge, identify unusual activities in patients, and control entry into the facilities while flagging unauthorized access.

Biometric technologies, including facial recognition, can also be used to verify the identities of surgical patients, identify patients who are unaccompanied by a medical worker, and track people entering and leaving the premises to prevent security threats.

And just recently, Apple reported that its Vision Pro augmented reality headset can be potentially used to detect and alleviate mental distress. The headset includes cameras and sensors that can detect various facial expressions and emotions. For instance, the device can identify post-traumatic stress disorder, depression, and some other stress variations. Afterwards, the headset can soothe the user by showing images and playing calming sounds.

Cali Group was one of the first US companies to roll out a facial recognition loyalty program. They equipped their restaurants with AI-powered self-service kiosks that identify registered customers and activate their loyalty accounts as soon as they approach the kiosk. The software powering the kiosk may prompt customers to order their favorite meals, and they can pay via facial recognition as well.

A similar approach is taken in this facial recognition application. For example, knowing how much time a particular customer spends in a store helps tailor future experiences to their preferences. And by analyzing their purchase history, retailers may nudge buyers with push notifications advertising products similar to those they have recently purchased.

While US universities are hesitant to deploy this technology, the Chinese educational system is willing to give it a try. Beijing Normal University mounted facial recognition equipment at the entrance to its student dorms. And several other universities and schools experimented with the technology in their classrooms.

Tracking attendance used to be a lengthy and tedious process that, despite a fair amount of time spent at the beginning of every class, leads to inevitable gaps and omissions when conducted manually. To fix that, educators are turning to AI-powered educational solutions. These facial recognition applications offer a faster and less disruptive way of tracking attendance.

Different universities are experimenting with this technology. For instance, a professor teaching Computer Technology Information Systems at Guilford College, North California, is working with his team to build a facial recognition system that can tell when students are confused or bored.

To give a few examples, the Bank of America uses a facial recognition solution from Samsung to allow customers to log into their banking mobile app. And the Orissa High Court in India is pushing for deploying facial recognition technology on ATMs to identify people involved in illegal withdrawals.

Enhanced security. AI-based facial recognition solutions help identify suspicious behaviors, pinpoint known criminals, and ensure safety in crowded venues. Beyond that, facial recognition technology adds convenience and safety to everyday experiences, like using banking services, receiving healthcare, or shopping.

Faster service. By replacing current customer authentication procedures with facial recognition, businesses can make it easier for their clients to use the available services. The technology can also facilitate the transition to digital-first experiences, eliminating the need for a customer to be physically present at a venue in order to access the services.

Superior customer experience. As a continuation of the previous point, facial recognition also helps increase the quality of customer service, especially in such domains as retail and healthcare. For example, by knowing who enters a store and tapping into their buying habits, retailers may adjust their offer on the go to better suit the needs of the customer. In healthcare settings, facial recognition can also help craft personalized care plans.

Improving accessibility for people with visual impairments. Facial recognition applications have found wide use among visually impaired people. Powering your business with facial recognition can help make your services more accessible as well. This way, for example, instead of going through authentication procedures like entering a PIN or filling out papers, a visually impaired customer participates in a face scan and proceeds to use a service.

The accuracy of recognition. The National Institute of Standards and Technology found out that as of April 2020, the best-performing facial identification algorithm showed an error rate of just 0.08%. Still, recognition accuracy is higher when facial recognition technology relies on clear, static images, like ID photos or mugshots. But that is rarely the case in reality.

Algorithmic bias. In its 2020 research, the US Government Accountability Office found that facial recognition algorithms powering commercial solutions are subject to inherent bias. They found that the accuracy of facial recognition depends much on the race, ethnicity, gender, and age of the person being recognized. While having no trouble accurately identifying white men, commercially available facial recognition systems show high false-positive rates when applied to the images of people of color, women, children, and the elderly.

If you consider rolling out an AI-based facial recognition solution, we strongly recommend committing to doing so ethically. Here are some aspects that you need to investigate before you start building your solution:

Decide how you will ask people for informed consent for collecting and storing biometric data. While some facial recognition systems can de-identify the information, biometric data can hardly be fully anonymized, so timely informing people is essential for maintaining trust and transparency.

Ensure your solution is explainable and involve human employees to resolve any issues. A user should understand why a system has come to a particular decision and revert it in case of false positives or false negatives. For example, when rolling out a facial recognition solution, National Australia Bank intentionally chose to refer all user verification requests that the system could not verify to a human operator rather than rejecting them. This approach reduced the error rate and increased customer satisfaction.

No matter what your line of business is, you are likely to discover exciting facial recognition applications that you can use in your sector. But even though the technology is maturing and getting more affordable, incomprehensive legislation still hinders its promising potential.

Amid public debate about the safety of facial recognition technology, businesses and tech vendors should prioritize building transparent and explainable solutions. As of now, the technology is not 100% accurate, and it can be fooled; a simple false mustache can trick some facial recognition systems, not to mention face spoofing and other more elaborate techniques. Depending on the implications of your facial recognition solution, you might want to add an extra verification layer, such as gait recognition or fingerprint scans.

Here at ITRex, we can analyze your business requirements and recommend an appropriate facial recognition model with a backup verification system, if needed. We are also experienced in explainable AI solutions and can implement a human-in-the-loop approach to assist with accuracy and transparency.

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