Chapter 11 Managing knowledged Artificial intelligence 431 INTERACTIVE SESSION TECHNOLOGY Do You Know Who Is Using Your Face? Facial recognition an artificial Intelligence applica- is of the images then being shared around the world, tion that can uniquely identify a penon by analy The databases are pulled together with images from ing patterns based on the person's facial textures social networks, photo wehsites dating services like and shape. Facial recognition systems can be used to OkCupid, and canteras placed in restaurants and on identify people in photos, video, or real-time. A fa college quincs. While there is no precise count of the cial recognition system uses biometrics to mapacial data sets, privacy activists have pinpointed reposito features from a photograph or video. It compares the ries that were built by Microsoft, Stanford University, information with a database of known faces to find a and others with one holding over 10 million im match The face recognition system uses computer al ages while another had more than two million gorithms to highlight specific, distinctive details about Georgetown University has estimated that phoxes of a person's face, such as the distance between the eyes nearly half of all us adults have been entered into or the shape of the chin (Some algorithms explicitly at least one face recognition database map the face, measuring the distances between the Tech gants like Facebook and Google are reputed eyes, nose, and mouth and so on. Others map the face to have amassed the largest facial data sets, which using more abstract features.) The system converts they do not distribute, according to research papers these details to a mathematical representation and But other companies and universities have widely compare them to data on other faces stored in a face shared their image troves with researchers, govern recognition database. This data but a particular Cements, and private enterprises in Australia, China, is called a face template, and it can be compared to India, Singapore and Switzerland for training artifi- other templates on file. Facial recognition technology cial intelligence, according to academics, activists learn how to identity people by analyzing as many and public papers digital pictures as possible tsing neural networks, Startup Clearview Al created a powerful facial ree which are complex mathematical systems that require ognition app that enables the user to take a picture of wast amounts of data to build pattern recognition a person, upload it, and be able to view public photos Face recognition tools are now frequently used of that person, along with links to where those pho- in routine policing Police compare mugshots of an tas appeared. The system uses a database of more restees to local state, and federal face recognition databases Law enforcement can query these mus , than three billion images that Clearview claims to have scraped from Facebook, YouTube, Venmo and shot databases to identify people in photos taken millions of other websites Federal and state law from social media, traffic cameras, and closed citeit enforcement officers have used the Clearview app television surveillance cameras in stores, parks, and to help solve shoplifting, identity theft credit card other places. There are systems to compare faces in fraud, murder and child sexual exploitation case real-time with hot lists of people suspected of il- Companies and labs have thered that images legal activity face recognition has also been used for more than a decade, and image databases are an in airports, border crossings and events such as the essential component of facial recognition technol- Olympic games The FRI spent more than a decade gy. But people often have no idea that their faces using such systems to compare driver's license and are in them. And although names are typically not visa photos against the faces of suspected criminals. attached to the photos, individuals can be recognized Facial recognition syatems can make products because each face is unique to a person. There is no safier and more secure. For example, face authentic oversight of these facial recognition data repositories tion can ensure that only the right person gets ac Privacy advocates worry that facial recogni cess to sensitive information meant just for them. It tion systems are being misused. A database called can also be used for social good, there are nonprofits Brainwash was created by Stanford University using facial recognition to combat trafficking of me researchers in 2014. The researchers captured nors. However these systems also have limitations over 10,000 images using a camera located in San that can do harm as well Francisco's Brainwash Cafe (now closed) It is un Dozens of databases of people's faces are being clear whether the patrons knew their images were compiled by companies and researchen with many being captured and used for research The Stanford 432 Part Three Key System Applications for the Digital Age researchers shared Brainwash with Chinese ac demics associated with the National University of Defense Technology and Megva, an Al company that provided surveillance technology for racial pratiting or Chiru's Uighur Muslim population Brainwash was removed from its original website in mid-2019 Using eight cameras an campus to collect images Duke University researchers gathered more than 2 million video frames with images of over 2.700 peo ple. The database, called Duke MTMC, was reported to have been used to train Al systems in the United Suites, Japan, China, and elsewhere. The cameras were identified with signs, which give a phone num her or email for people to opt out Momover, facial recognition systems are not erstinely accurate Face recognition systems have varying ability to identify people under challenging conditions such as poor lighting, low-quality image resolution, and saiboptimal angle of view, which might caur if a photograph was taken from above looking down on an unknown person Facial recognition software is poor at identifying African Americans and other ethnic minorities as well as women and young people. A 2012 study co authored by the FBI reported that accuracy rates were lower for Afro-Americans than for other demograph is. Although the Fat caims that its facial recognition system can find the correct candidate in the top 50 prostiles 85 percent of the time, that's only when the true candidate exists in its gallery. If the candidate is not in the gallery, the system may still come up with one or more potential matches, creating false positive results. Those identified could then be targeted as suspects for crimes they didn't commit. Face recognition becomes less accurate as the num her of people in the database increases. Many people around the world look alike. As the likelihood of simi Iar faces goes up, matching accuracy goes down Sade Hegnitio www.ceed Agila 2020 Kami Tempat Mah Enda w It's YouTuy 18,329 Cate Me Recognition Tech Is Groning Song Thonest Free Tort Time July 13 20 www.agogic.com, se il 21, 2020 CASE STUDY QUESTIONS I. Explain the key technologies used in facial reco nition systems 2. What are the benefits of using facial recognition systems? How do they help organizations improve operations and decision making? What problems can they help solve? 3. Identify and describe the disadvantages of using Facial recognition systems and facial databases