The committee on homeland to get he will come t to order. Let me set the outset number of our members are still en route from the Prayer Breakfast this morning. They will join us accordingly. The Ranking Member being one of them. The committee is meeting today to receive testimony on the department of Homeland Security use of facial recognition and other biometric technologies. Without objection the chair is authorized to declare a committee in recess at any point. Good morning. The committee is meeting today to continue examining the department of Homeland Security is use of facial Recognition Technology. The Committee Held part one of this hearing in july of last year, after news that thet department was expanding its use of facial recognition forth varying purposes, such as confirming the identities of travelers, including u. S. Citizens. As facial Recognition Technology has advanced, it has become the chosen form of Biometric Technology used by the government and industry. I want to reiterate that i am not wholly opposed to the use of facial Recognition Technology, as i recognize that it can be valuable to Homeland Security and serve as a facilitation tool for the departments varying missions. But i remain deeply concerneded about privacy, transparency, data security, and the accuracy of this technology and want to ensure these concerns are addressed before the department deploys it further. Last july, i along with other members of this committee, shared these concerns at our hearing and left this room with more questions than answers. In december 2019, the National Institute for standards and Technology Published a report that confirmed age, gender, and racial bias in some facial recognition algorithms. Nist, for example, found that depending on the algorithm,io africanamerican and asianamerican faces were misidentified 10 to 100 times more than white faces. Although cbp touts that the match rate for its facial Recognition Systems is over 98 , it is my understanding that nist did not test cbps current algorithm for its december 2019 report. Moreover, cbps figure does not account for images of travelers who could not be captured due a variety of factors such as lighting or skin tone, likely making the actual match rate significantly lower. These findings continue to suggest that some of this technology is not ready for prime time and requires further testing before widespreadme deployment. Misidentifying even a relatively small percentage of the traveling public could affectoy thousands of passengers annually, and likely would haveu a disproportionate effect on certain individuals. This is unacceptable. Data security also remains an important concern. Last year, a cbp subcontractor experienced a significant data breach, which included traveler images being stolen. We look forward to hearing more about the lessons cbp learned from this incident and the steps that it has taken to ensure that biometric data is kept safe. Transparency continues to be key. The American People deserve to know how the department is collecting facial recognition data, and whether the department is in fact safeguarding their rights when deploying such technology. That is why we are here seven months later to continue our oversight. I am pleased that we again have witnesses from cbp and nist before us to provide us with an update and answer our questions. We will also have testimony from dhss office for civil rightsn and Civil Liberties. This office is charged with ensuring the protection of our civil rights and Civil Liberties as it relates to the departments activities, no easy task, especially these days. Be assured that under my leadership, this committee will continue to hold the department accountable for treating all americans equitably and ensuring that our rights are protected. I look forward to a robust Discussion Forum all the witnesses at a thank the members for joining us today. I welcome our panel of witnesses here our first witness, john wagner, currently serves as te deputy executive assistant commissioner for the office of field operations, u. S. Customs and Border Protection. In his current role he oversees nearly 30,000 federal employees and manages programs related to immigration, custom, and commercial trade related to cbp missions. Mr. Peter minute is a deputy officer for program and compliance at the office of civil rights and Civil Liberties here he previously served as chief of the labor and employmentpr law division for u. Immigration and customs enforcement. Dr. Charles romine is the director of Information Technology laboratories at the National Institute of standards and technology. In this position he oversees a Research Program that focuses on testing and interoperability, security, usability, and reliability of information systems. Without objection, the witnesses full statement will be inserted in the record did i not ask eah witness to summarize his statement a for five minutes beginning with mr. Wagner. Good morning. Chairman thompson, Ranking Member rogers, members of the committee, thank you for the opportunity to testify before you today on behalf of u. S. Customs and Border Protection. I am looking for to the opportunity to discuss the recent nist report with you. Since cbp is using an algorithm for one of the highest performing vendors identified in the report, we are confident our results are corroborate with the findings of this report. More specifically the report indicates while theres wide range of performance of the 189 differentfo algorithms that nist reviewed, the highest performing algorithms had minimal to undetectable levels of demographicbased error rates. The report also highlights some of the operational variables that impact their rate the chess gala precise, photo page, photo quality, numbers of voters of each subject in the gallery, camera quality, lighting, Human Behavior factors, all influence the accuracy of an algorithm. Thats why cbp is carefully constructed operational variables in the deployment of the technology to ensure we cant attain the highest levels of match rates which remain in the night seven98 range. One Important Note is nist did not test the specific cbp operational construct to measure the additional effect these fables may have which is why weve entered into an m. O. U. With nist three by which are specific data. As we build out the congressionally mandated biometricbased entryexit system, we are creating a system that not only meets the security mandate but also inly a way that is cost effective, feasible and facilitated for international travelers. Identity requirements are not new when crossing the border or taking international flight. Several existing laws and regulations require travelers to establish their identity and citizenship whenla entering and departing the trendy pick cbp employs biographic and biometric these procedures to inspect the travel documents to verify the authenticity of the document and determine if it belongs to the actual person presenting it. Again these are not new requirements. The use of facial Comparison Technology center automates the process that is often done manually today. Passport, it makes sense that the Technology May be useful in determination of the d rightful document holder. Its more difficult today to forge a legitimate passport insecurity features are much stronger than they were ten 15 years ago but we are stuck vulnerable to a person using legitimate documents that is real and belongs to someone else. Using facial Comparison Technology to date, we identified 252 imposters to include people using 75 genuine u. S. Travel documents. Privacy continues to be our mission. Its compliant with the terms of privacy act of 1974 as amendment, the 2062 departmental policies and government collection and maintenance. Personally identifiable information. Cbp recently published updates and the privacy Impact Assessment covering this program. Systems of record notice system publish on the database in storing the information. Weve met three times with representatives of the community as well as discussions with privacy liberties Oversight Board and privately privacy committee. The office of management and budget, a rulemaking that would solicit Public Comments on the regulatory updates and amendments to the federal regulations. One final note, our private sector partners, the airlines and airports must agree that documented specific business requirements they are submitting to photographs as part of this process. These requirements include a provision the images must be deleted and transmitted to cbp and may not be retained by the private stakeholder. After the attacks of september 11, we as a nation asked how we can make sure it never happens again. Part of the answer, the report commended the dhs should complete as quickly as possible a biometric entry exit screening system and it was an essential investment in National Security. Gbp is internet volunteering at the duty by strengthening biometric efforts verifying that people are who they say they are. Thank you for the opportunity to appear today and look forwardtio your questions. Thank you. I recognize you to summarize your statements for five minutes. Good morning. Thank you for the opportunity to appear before your directors discuss the home and security use of facial Recognition Technology. Commitment to not determination and activities remain important cornerstone of our daily work. Id like to make three points in my testimony today. Ra first, the civil rights and liberties has been and continues to be engaged with dhs operational components to ensure use of facial Recognition Technology consistent with civil rights and liberties. Law and policy. Second from operators researchers and civil rights policymakers must Work Together to prevent algorithms from leading to biases and facial Recognition Technology. Third, facial Recognition Technology can serve as an important tool to increase the effectiveness of the Department Mission as well as a facilitation of travel but it is vital that these programs utilize technology in a way that safeguards are rights and values. To achieve these, one, influenced vhs policies and programs throughout the cycle. Engage with components in the development of new policies in the program to assure protection of civil rights and so forth liberties are fully integrated into the foundation. Three, monitor operational execution and engage with stakeholders to provide feedback regarding consequences of policies and programs. Ce fourth, we investigate complaints and make recommendations to the components, including allegations of racial profiling or other visible bias. They recognize the potential risk for bias and algorithms. They support rigorous testing and evaluation of algorithms used in the system to identify and mitigate visible bias. They will continue to support the relationship between the institute of standards and technology, the director, dhs office of biometric and components including Border Protection. In carrying out the mission, they advise the components of the offices by participating in enterprise level groups working on facial recognition pictures. Further, we are directly engaged with the components read for example, they regularly engage them on implementation on the facial Recognition Technology. They advise on policy for appropriate accommodations for individuals with their objection of being photographed and for individuals who may have visible injuries, prevent charges. The facial Recognition Program, they will collaborate directly with them to address potential civil rights and liberties impact. Further, to engage communities to both inform the public regarding facial Recognition Program and address potential concerns. Finally, we will continue to evaluate any potential violation of civils rights and liberties o further inform our policy advice and strengthen the Recognition Program. Successful appropriate facial Recognition Technology requires ongoing oversight and quality assurance. Initial validation and regular revalidation and relationship between users and oversight office, this way it can be developed to work properly and without bias, achieved operating capability and continuing throughout the lifecycle. At the same time, we need to work with the operational components to ensure practices from the human part of the equation, users are focused on the technology, working in a manner that prevents bias, engaging in the activity. Again, thank you for the opportunity to appear before you today and i look forward to answering your questions. Thank you for your testimony. I recognize you to summarize your remarks. Thank you. I am chuck, the director of the laboratory of the standard technology. Nist. Thank you for the opportunity to before you today for standard of testing of facial Recognition Technology. This has been working with public and private sectors since the 1960s. Biometric Technology Provides a mean to establish or verify the identity of humans based upon one or more physical or behavioral characteristic. For self recognition Current Technology compares facial features for verification or identification purposes. This work improves the quality, usability, and consistency ofus systems and ensures that u. S. Interests are represented in the international arena. This research has provided stateoftheart technology benchmarks and guidance to the industry and u. S. Government agencies that depend upon biometrics recognition technologies. The face recognition Testing Program provides technical guidance and scientific support for analysis and recommendations for utilization of face recognition technologies to various Law Enforcement agencies including the fbi, vhs, and i are both. This report released in december 2019 quantify the accuracy of face recognition algorithms or demographic groups defined by sex, age and race or controversy or both want one and one too many identifications algorithms. They found evidence for the existence of demographic facial recognition algorithm that nist evaluated. It is temperatures between false positive and negative errors and note the impact of errors are application dependent. Nist conducted test to quantify the differences for 189 face recognition algorithms from 99 Developers Using four collections of photographs with 18. 27 million images of 8. 49 Million People. These images came from operational databases provided by the statete department, department of Homeland Security and fbi. I will firstan address 11 verification application. False positive differentials are much smarter than those related to false negatives. They exist acrossch many of the algorithms tested. False positives might present our concern to the owner as they may allow access to imposters. Other findings of false positives are higher in women than men and higher in the elderly and young compared to middleaged adults. Regarding race, we major higher false positives in asian and a African Americans relative to those caucasians. The ohio false positive native americans, american indians, alaskan indians and pacific. These effective apply to those developed europe and United States but it was algorithms developed in Asian Countries. There is no such dramatic differences in false positives and one to one faction between asian and caucasian faces or the algorithms developed in asia. While the study did not explore the relationship between cause and effect from one possible connection area for research is the relationship between algorithms performance and for data used to train the algorithm itself. How comments on one too many algorithms. False positives in one too many search are particularly important because the consequences could include false accusations. For most algorithms, the study measured higher false positives in women, African Americans in particular africanamerican women. Some algorithms gave similar false positives across these demographics. It was accurate algorithms fell into this group. This underscores one overall message of the report. Different algorithms perform differently. Indeed, all of our reports note variations in recognition across algorithms and important results from a demographic study is a demographic effects are smaller with more accurate algorithms. This is the positive impact its had in the last 60 years inve te evolution of biometric capabilities with nist extensive experience and expertise in laboratories and successful collaborations in the