Ballooning AI-driven Facial Recognition Industry Sparks Concern Over Bias, Privacy: 'You Are Being Identified'
Experts weigh benefits, concerns surrounding AI-driven facial recognition technology
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A significant expansion in Artificial intelligence (AI) facial recognition technology is increasingly being deployed to catch criminals, but experts express concern about the impact on personal privacy and data.
According to the Allied Market Research data firm, the facial recognition industry, which was valued at $3.8 billion in 2020, will have grown to $16.7 billion by 2030.
Lisa Palmer, an AI strategist, said it is important to understand that an individual's data largely feeds what happens from an AI perspective, especially within a generative framework.
While there has been data recorded on citizens for decades, today's surveillance is different because of the quantity and quality of the data recorded as well as how it's being used, according to Palmer.
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© Smith Collection/Gado/Getty Images Output of an Artificial Intelligence system from Google Vision, performing Facial Recognition on a photograph of a man, with facial features identified and facial bounding boxes present, San Ramon, California, November 22, 2019. Smith Collection/Gado/Getty Images"When you go to the airport, you are being recorded, you are being videoed from the moment that you cross onto that property throughout your entire experience and until you leave on the other end of that, that is all happening from a video perspective," Palmer said. "It's also happening from an audio perspective, which people often are unaware that their conversations are actually being recorded in many situations as well."
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On the positive side of things, Palmer noted that this framework enables the government to identify criminals when they are traveling from one location to the next and preemptively coordinate that information across different policing bodies to mitigate harm.
"On the flip side of that, as an individual person, how comfortable are you that the government knows every move that you're making when you enter into any transportation arm in the United States? How comfortable are you with that? It's happening," Palmer added. "You are being identified. Your face is being stored. These things are very real. It's not something that's futuristic. It's happening today."
Palmer also noted that predictive policing is often a source of tremendous bias in facial recognition technology. In these instances, some AI systems tend to identify persons of color or people from underrepresented groups more frequently.
For example, a person could be walking where government-installed cameras watch and look for situations where crime may occur. As a result of that, they could misidentify somebody and send police to that location because they think it is a criminal with a warrant out for them.
POLICE ARE USING INVASIVE FACIAL RECOGNITION SOFTWARE TO PUT EVERY AMERICAN IN A PERPETUAL LINEUP
© Photo by Matthew Horwood/Getty Images A man in a mask attends a protest against the use of police facial recognition cameras at the Cardiff City Stadium for the Cardiff City v Swansea City Championship match on January 12, 2020 in Cardiff, Wales. Police are using the technology to identify those who have been issued with football banning orders in an attempt to prevent disorder. Photo by Matthew Horwood/Getty ImagesThe AI tech company Clearview AI, recently made headlines for its misuse of consumer data. It provides facial recognition software to law enforcement agencies, private companies and other organizations. Their software uses artificial intelligence algorithms to analyze images of faces and match them against a database of over 3 billion photos that have been scraped from various sources, including social media platforms like Facebook, Instagram and Twitter, all without the users' permission. The company has already been fined millions of dollars in Europe and Australia for such privacy breaches.
Despite being banned from selling its services to most U.S. Companies due to breaking privacy laws, Clearview AI has an exemption for the police. The company's CEO, Hoan Ton-That, says hundreds of police forces across the U.S. Use its software.
Critics of the company argue that the use of its software by police puts everyone into a "perpetual police lineup." Whenever the police have a photo of a suspect, they can compare it to your face, which many people find invasive. It also raises questions about civil liberties and civil rights and has falsely identified people despite a typical high accuracy rate.
"Biased artificial intelligence, particularly machine learning, often happens because the data that has been fed into it is either incomplete or unbalanced. So, if you have a data set that has a huge number of Caucasian faces, white faces in it, and it doesn't have those that have more that have darker skin tones in the data stores, then what happens is the artificial intelligence learns more effectively on the larger dataset. So, the smaller dataset gets gets less training, less learning," Palmer said.
To address imbalances in an AI dataset, Palmer said the potential use of synthetic data could balance the dataset and therefore reduce the inherent machine learning bias.
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Mike Davis compares Madison Square Garden's facial recognition to Chinese Communist social credit
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Synthetic data is information that is manufactured by an AI rather than real-world events. For example, an AI can create a clean data set, like images of non-existent people, from scratch. This data can then be plugged into the model and used to improve the existing algorithm, which may or may not already include data from real individuals.
But Palmer stressed that it is "extremely difficult" to remove all bias from training data because the data is created by humans, who all have an inherent bias.
One of the biggest challenges with AI training, according to Palmer, is trying to identify what is not there.
"Well, it's not very simple, but it's much simpler to identify data that is flawed than to identify data that is fully missing," Palmer said. "So, in order to do so, if you bring a diverse perspective of people, lots of different lived experiences in their background into conversations where those products are created, it's much easier to have all of those different viewpoints say, 'oh, you didn't even think about this, or you didn't think about that.' And that's how we make sure that we are using both technology and people together to come to make the best possible solutions."
Certified Information Privacy Professional Jodi Daniels agreed that profiling is a significant concern associated with facial recognition systems.
She highlighted how Flock Safety ALPR cameras are one of several systems that work with police departments, neighborhood watches and private customers to create "hot lists," which generate alarms that run all license plates against state law enforcement watch lists and the FBI criminal database.
SEE ALL THE POLICE SURVEILLANCE TOOLS USED IN YOUR CITY
© Niall Carson/PA Images via Getty Images An image of an automatic number-plate recognition surveillance camera. Niall Carson/PA Images via Getty Images"Let's just take a neighborhood. It's monitoring the license plate in and out of the neighborhood," Daniels said. "The person who set up the neighborhood now has access to that. Well, do I really want the neighborhood person knowing my in and out in every time that I'm coming and going? I don't want crime. So, I like the idea of that. But what are the controls in place so that they're not really monitoring every single thing that I'm doing and that they have full access to it?"
Daniels highlighted two pivotal instances that have sparked debate about facial recognition and helped cultivate biometric laws.
In the summer of 2020, law enforcement in San Diego combed through video of Black Lives Matter protests and riots and used it to profile various people.
San Francisco and Oklahoma have already banned the use of facial recognition by law enforcement. In Portland, Oregon, a citywide ban forbids the use of the tech by any group, whether private or public.
Just last month, it was revealed that between 2019 and 2022, several groups of Tesla employees privately shared videos and images recorded by customers' car cameras.
"This is to me, like I didn't say it was okay for you to video me everywhere I went or take a picture and match me up to everything over here. And that is why the laws that are coming into play for biometrics, every single one of them are all opt-in laws because it's considered so sensitive and so personal about me, and what happens if that is used in any kind of way to discriminate against me or used in incorrectly? You know, the systems aren't always perfect," Daniels said.
She added that the same basic concept of privacy extends across our physical movements, handheld devices, and biometric data.
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"So, if you think about just the idea of being tracked, it, most people don't love the idea of someone tracking you," Daniels said. "If we took this outside the digital world, and we were on the street, and you had someone following, taking a note at every single thing that you ever did and taking a picture of it all the time. After about five seconds, you probably turn around and say, What are you doing? No one likes that. People don't want someone tracking and stalking and notating every single thing about their life."
Similarly, a person would not want to hand all their online movements and actions on a cell phone or a computer over to another person.
Recently it was discovered that phone spyware had been sold to various governments throughout the world and is meant to be used to spy mainly on journalists, activists, and political opponents.
A report released from Citizen Lab reveals that the spyware, which has been given the name Reign, is being used to monitor the activities of targeted high-profile individuals. The Microsoft Threat Intelligence team was able to analyze the spyware and found that it was provided by the Israeli company QuaDream.
Although Reign has not yet been detected as a threat to the U.S. Government, and it doesn't seem to be targeting citizens with low-profile statuses, There have been at least five targeted spyware cases in North America, Central Asia, Southeast Asia, Europe, and the Middle East.
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According to Daniels, individuals would also not want their data being used from a biometric facial recognition standpoint near their place of residence. This is the reason why most people do not have cameras in their home (unless they have a babysitter, child or dog they need to watch) but rather outside.
But Daniels stressed that there is a difference in laws and applications between general video surveillance and facial recognition.
In the former, a company or agency uses certain points of data on a Face ID, takes images and extracts the data. A bank may garner biometric data through a fingerprint, or a system may do an ID scan to allow the person to pass through security.
"That is a very unique biometric that is special and unique to you. The video surveillance has sort of different notifications typically you're going to find a sign that says you're under video surveillance. And that's a notice kind of situation," Daniels said. "Video surveillance is typically not extracting the facial points out of you and building a facial profile to put in a database to match you up with somebody else."
Kurt Knuttson and CyberGuy report contributed to this article.
Facial Recognition Is Expanding Its Watchful Eye But Suffers From Notable Fails
The use of facial recognition technology, a form of biometric artificial intelligence, is growing across the U.S. As an efficient security system that can identify people based on measuring facial features, but has been hit with some notable criticisms.
Police departments, the health care industry, and companies looking to fight back against cyber fraud have rolled out the technology in recent years to bolster security measures. The tech is far from new, with its roots stretching back to the mid-1960s, when researchers in Palo Alto pioneered training computers to recognize faces, and has exploded in use since around 2010.
Today, machine learning algorithms - a subset of artificial intelligence that uses data and algorithms to mimic how humans learn - has fine-tuned the technology. The tech can measure and identify facial measurements in a photo or video, and cross-analyze whether two photos or videos show the same person, or even pick a person out in a crowd of people, Amazon Web Services explains.
"Machines use computer vision to identify people, places, and things in images with accuracy at or above human levels and with much greater speed and efficiency. Using complex artificial intelligence (AI) technology, computer vision automates extraction, analysis, classification, and understanding of useful information from image data," according to the Amazon subsidiary.
POLICE ARE USING INVASIVE FACIAL RECOGNITION SOFTWARE TO PUT EVERY AMERICAN IN A PERPETUAL LINEUP
Output of an Artificial Intelligence system from Google Vision, performing Facial Recognition on a photograph of a man, with facial features identified and facial bounding boxes present, San Ramon, California, Nov. 22, 2019. (Smith Collection/Gado/Getty Images)
The tech is being used to patrol for fraud, where some companies have users verify their identity with their face, to ATMs using the tech to authenticate customers or even for doctors accessing patient records. While a New York City supermarket rolled out the tech to patrol for shoplifters, and Madison Square Garden Entertainment has used the recognition software to identify and boot event-goers from venues such as Radio City or Madison Square Garden.
For police departments, the use of the tech is widespread, with the CEO of facial recognition firm Clearview AI telling the BBC last month that police departments in the U.S. Have used its software nearly 1 million times.
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A man uses an iris recognition scanner. (Ian Waldie/Getty Images)
"Clearview AI's technology only searches publicly available information from the internet, and complies with all standards of privacy and law where we operate," Hoan Ton-That, CEO of Clearview AI, told Fox News Digital.
"Clearview AI is also committed to the responsible use of its powerful technology and is used only for after-the-crime investigations to help identify criminal suspects. It is not intended to be used as a real time surveillance tool. Law enforcement investigators are expected to do follow-up research and not use facial recognition results as the sole source for an arrest," the tech CEO added.
Facial recognition technology, however, has come under scrutiny by some local leaders and civil liberties groups with accusations it violates people's privacy and civil liberties.
In Anchorage, Alaska just this week, local leaders passed a measure restricting the use of facial recognition in the city, citing privacy must be protected and to prevent the technology from being misused.
Police departments' use of the software has especially faced condemnation, as a handful of people across the country report they were mistakenly arrested due to the technology.
Robert Williams, for example, spent 30 hours in jail back in 2020 after Michigan police allegedly ran a blurry pic of a suspect who stole watches from a store and determined Williams was behind the crime.
"The day I was arrested, I had no idea it was facial recognition," Williams told Newsweek this month. "I was arrested for no reason."
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His case was ultimately dismissed, but he and the ACLU are suing the department over the arrest.
Such instances of mistaken identities and arrests have played out a handful of times, including in November when Georgia man Randall Reid was arrested on theft warrants in Louisiana, despite the man saying he had never visited that state before, Newsweek reported.
"Police reliance on flawed face recognition technology has resulted in repeated arrests of people for crimes they had absolutely nothing to do with. This technology makes us less secure, not more," Nathan Freed Wessler, deputy director of ACLU's Speech, Privacy, and Technology Project, told Fox News Digital of the tech.
"Local lawmakers from Maine to Alaska have already hit the brakes on this dangerous technology by putting it off limits to police. The time for additional cities and states to take action to prevent government abuse is now," Freed Wessler added.
Overseas, the European Parliament called for a ban in 2021 on facial recognition in public space by police departments, noting that the tech has the possibility of better keeping residents safe, but risked their rights to privacy and freedom of movement.
"AI applications may offer great opportunities in the field of law enforcement … thereby contributing to the safety and security of EU citizens, while at the same time they may entail significant risks for the fundamental rights of people," the European legislative body said.
FACIAL RECOGNITION APP CAN IDENTIFY YOUR PET'S FACE WITH 99% ACCURACY
A man in a mask attends a protest against the use of police facial recognition cameras at the Cardiff City Stadium for the Cardiff City v Swansea City Championship match on Jan. 12, 2020 in Cardiff, Wales. (Photo by Matthew Horwood/Getty Images)
Meanwhile, the artificial intelligence community has made strides in recent months on building more powerful systems across the board.
Large language models, a deep learning algorithm that's trained with copious amounts of text, have become wildly popular since OpenAI's release of ChatGPT last year. The chatbot system is able to mimic human conversation based on prompts it is given, and can execute various tasks such as writing short stories, composing emails, answering questions and even coming up with recipes.
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For facial recognition specifically, studies have found the use of the technology will likely increase in the future. A study published last month predicts that facial recognition market revenue will increase from $5.1 billion in 2022 to $19.3 billion in 2032, according to Markets.Us.
Artificial Intelligence-Emotion Recognition Market Complete Overview Till 2031
The MarketWatch News Department was not involved in the creation of this content.
Apr 28, 2023 (The Expresswire) -- The latest market research report on the Global "Artificial Intelligence-Emotion Recognition Market" is segmented by Regions, Country, Company and other Segments. The global Artificial Intelligence-Emotion Recognition market is dominated by key Players, such as [CrowdEmotion, Eyeris, Cloudwalk, Beyond Verbal, Softbank, Apple, Nviso, Affectiva, Realeyes, IBM, Kairos AR, IFlytek, INTRAface, Microsoft] these players have adopted various strategies to increase their market penetration and strengthen their position in the industry. Stake holders and other participants in the global Artificial Intelligence-Emotion Recognition market will be able to gain the upper hand by using the report as a powerful resource for their business needs.
What is the Artificial Intelligence-Emotion Recognition market growth?
Artificial Intelligence-Emotion Recognition Market Size is projected to Reach Multimillion USD by 2031, In comparison to 2023, at unexpected CAGR during the forecast Period 2023-2031.
Browse Detailed TOC, Tables and Figures with Charts which is spread across 121 Pages that provides exclusive data, information, vital statistics, trends, and competitive landscape details in this niche sector.
Client Focus
1. Does this report consider the impact of COVID-19 and the Russia-Ukraine war on the Artificial Intelligence-Emotion Recognition market?
Yes. As the COVID-19 and the Russia-Ukraine war are profoundly affecting the global supply chain relationship and raw material price system, we have definitely taken them into consideration throughout the research, and in Chapters, we elaborate at full length on the impact of the pandemic and the war on the Artificial Intelligence-Emotion Recognition Industry
Final Report will add the analysis of the impact of Russia-Ukraine War and COVID-19 on this Artificial Intelligence-Emotion Recognition Industry.
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This research report is the result of an extensive primary and secondary research effort into the Artificial Intelligence-Emotion Recognition market. It provides a thorough overview of the market's current and future objectives, along with a competitive analysis of the industry, broken down by application, type and regional trends. It also provides a dashboard overview of the past and present performance of leading companies. A variety of methodologies and analyses are used in the research to ensure accurate and comprehensive information about the Artificial Intelligence-Emotion Recognition Market.
Which are the driving factors of the Artificial Intelligence-Emotion Recognition market?
Growing demand for [Education, Medical Care, Wisdom Center, Others] around the world has had a direct impact on the growth of the Artificial Intelligence-Emotion Recognition
The Artificial Intelligence-Emotion Recognition segments and sub-section of the market are illuminated below:
Based on Product Types the Market is categorized into [Facial Emotion Recognition, Speech Emotion Recognition, Others] that held the largest Artificial Intelligence-Emotion Recognition market share In 2022.
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Artificial Intelligence-Emotion Recognition Market - Competitive and Segmentation Analysis:
2.How do you determine the list of the key players included in the report?
With the aim of clearly revealing the competitive situation of the industry, we concretely analyze not only the leading enterprises that have a voice on a global scale, but also the regional small and medium-sized companies that play key roles and have plenty of potential growth.
Short Description About Artificial Intelligence-Emotion Recognition Market:
The Global Artificial Intelligence-Emotion Recognition market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2031. In 2021, the market is growing at a steady rate and with the rising adoption of strategies by key players, the market is expected to rise over the projected horizon.
The global Artificial Intelligence-Emotion Recognition market size was valued at USD 745.68 million in 2021 and is expected to expand at a CAGR of 18.16% during the forecast period, reaching USD 2029.39 million by 2027.
Emotion recognition is the process of identifying human emotion, most typically from facial expressions as well as from verbal expressions. This process leverages techniques from multiple areas, such as signal processing, machine learning, and computer vision.
The report combines extensive quantitative analysis and exhaustive qualitative analysis, ranges from a macro overview of the total market size, industry chain, and market dynamics to micro details of segment markets by type, application and region, and, as a result, provides a holistic view of, as well as a deep insight into the Artificial Intelligence-Emotion Recognition market covering all its essential aspects.
For the competitive landscape, the report also introduces players in the industry from the perspective of the market share, concentration ratio, etc., and describes the leading companies in detail, with which the readers can get a better idea of their competitors and acquire an in-depth understanding of the competitive situation. Further, mergers and acquisitions, emerging market trends, the impact of COVID-19, and regional conflicts will all be considered.
In a nutshell, this report is a must-read for industry players, investors, researchers, consultants, business strategists, and all those who have any kind of stake or are planning to foray into the market in any manner.
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3.What are your main data sources?
Both Primary and Secondary data sources are being used while compiling the report.
Primary sources include extensive interviews of key opinion leaders and industry experts (such as experienced front-line staff, directors, CEOs, and marketing executives), downstream distributors, as well as end-users. Secondary sources include the research of the annual and financial reports of the top companies, public files, new journals, etc. We also cooperate with some third-party databases.
Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historical data and forecast (2017-2027) of the following regions are covered in Chapters:
● North America (United States, Canada and Mexico) ● Europe (Germany, UK, France, Italy, Russia and Turkey etc.) ● Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam) ● South America (Brazil, Argentina, Columbia etc.) ● Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)This Artificial Intelligence-Emotion Recognition Market Research/Analysis Report Contains Answers to your following Questions
● What are the global trends in the Artificial Intelligence-Emotion Recognition market? Would the market witness an increase or decline in the demand in the coming years? ● What is the estimated demand for different types of products in Artificial Intelligence-Emotion Recognition? What are the upcoming industry applications and trends for Artificial Intelligence-Emotion Recognition market? ● What Are Projections of Global Artificial Intelligence-Emotion Recognition Industry Considering Capacity, Production and Production Value? What Will Be the Estimation of Cost and Profit? What Will Be Market Share, Supply and Consumption? What about Import and Export? ● Where will the strategic developments take the industry in the mid to long-term? ● What are the factors contributing to the final price of Artificial Intelligence-Emotion Recognition? What are the raw materials used for Artificial Intelligence-Emotion Recognition manufacturing? ● How big is the opportunity for the Artificial Intelligence-Emotion Recognition market? How will the increasing adoption of Artificial Intelligence-Emotion Recognition for mining impact the growth rate of the overall market? ● How much is the global Artificial Intelligence-Emotion Recognition market worth? What was the value of the market In 2020? ● Who are the major players operating in the Artificial Intelligence-Emotion Recognition market? Which companies are the front runners? ● Which are the recent industry trends that can be implemented to generate additional revenue streams? ● What Should Be Entry Strategies, Countermeasures to Economic Impact, and Marketing Channels for Artificial Intelligence-Emotion Recognition Industry?Customization of the Report
Can I modify the scope of the report and customize it to suit my requirements?
Yes. Customized requirements of multi-dimensional, deep-level and high-quality can help our customers precisely grasp market opportunities, effortlessly confront market challenges, properly formulate market strategies and act promptly, thus to win them sufficient time and space for market competition.
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Detailed TOC of Global Artificial Intelligence-Emotion Recognition Market Insights and Forecast to 2031
Major Points from Table of Contents
Global Artificial Intelligence-Emotion Recognition Market Research Report 2023-2031, by Manufacturers, Regions, Types and Applications
1 Introduction1.1 Objective of the Study1.2 Definition of the Market1.3 Market Scope1.3.1 Market Segment by Type, Application and Marketing Channel1.3.2 Major Regions Covered (North America, Europe, Asia Pacific, Mid East and Africa)1.4 Years Considered for the Study (2015-2031)1.5 Currency Considered (U.S. Dollar)1.6 Stakeholders
2 Key Findings of the Study
3 Market Dynamics3.1 Driving Factors for this Market3.2 Factors Challenging the Market3.3 Opportunities of the Global Artificial Intelligence-Emotion Recognition Market (Regions, Growing/Emerging Downstream Market Analysis)3.4 Technological and Market Developments in the Artificial Intelligence-Emotion Recognition Market3.5 Industry News by Region3.6 Regulatory Scenario by Region/Country3.7 Market Investment Scenario Strategic Recommendations Analysis
4 Value Chain of the Artificial Intelligence-Emotion Recognition Market
4.1 Value Chain Status4.2 Upstream Raw Material Analysis4.3 Midstream Major Company Analysis (by Manufacturing Base, by Product Type)4.4 Distributors/Traders4.5 Downstream Major Customer Analysis (by Region)
5 Global Artificial Intelligence-Emotion Recognition Market-Segmentation by Type6 Global Artificial Intelligence-Emotion Recognition Market-Segmentation by Application
7 Global Artificial Intelligence-Emotion Recognition Market-Segmentation by Marketing Channel7.1 Traditional Marketing Channel (Offline)7.2 Online Channel
8 Competitive Intelligence Company Profiles
9 Global Artificial Intelligence-Emotion Recognition Market-Segmentation by Geography
9.1 North America9.2 Europe9.3 Asia-Pacific9.4 Latin America
9.5 Middle East and Africa
10 Future Forecast of the Global Artificial Intelligence-Emotion Recognition Market from 2023-2031
10.1 Future Forecast of the Global Artificial Intelligence-Emotion Recognition Market from 2023-2031 Segment by Region10.2 Global Artificial Intelligence-Emotion Recognition Production and Growth Rate Forecast by Type (2023-2031)10.3 Global Artificial Intelligence-Emotion Recognition Consumption and Growth Rate Forecast by Application (2023-2031)
11 Appendix11.1 Methodology12.2 Research Data Source
Continued….
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