U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON : 

For sale by the Superintendent of Documents, U.S. Government Printing Office

Internet: bookstore.gpo.gov Phone: toll free (866) 512–1800; DC area (202) 512–1800

Fax: (202) 512–2104 Mail: Stop IDCC, Washington, DC 20402–0001

86–599 PDF 2012

S. HRG. 112–851 

WHAT FACIAL RECOGNITION TECHNOLOGY 

MEANS FOR PRIVACY AND CIVIL LIBERTIES 

HEARING 

BEFORE THE

SUBCOMMITTEE ON PRIVACY 

TECHNOLOGY AND THE LAW 

OF THE

COMMITTEE ON THE JUDICIARY 

UNITED STATES SENATE 

ONE HUNDRED TWELFTH CONGRESS 

SECOND SESSION 

JULY 18, 2012 

Serial No. J–112–87 

Printed for the use of the Committee on the Judiciary 

( 
(II) 

COMMITTEE ON THE JUDICIARY 

PATRICK J. LEAHY, Vermont, Chairman 

HERB KOHL, Wisconsin 

DIANNE FEINSTEIN, California 

CHUCK SCHUMER, New York 

DICK DURBIN, Illinois 

SHELDON WHITEHOUSE, Rhode Island 

AMY KLOBUCHAR, Minnesota 

AL FRANKEN, Minnesota 

CHRISTOPHER A. COONS, Delaware 

RICHARD BLUMENTHAL, Connecticut 

CHUCK GRASSLEY, Iowa 

ORRIN G. HATCH, Utah 

JON KYL, Arizona 

JEFF SESSIONS, Alabama 

LINDSEY GRAHAM, South Carolina 

JOHN CORNYN, Texas 

MICHAEL S. LEE, Utah 

TOM COBURN, Oklahoma 

BRUCE A. COHEN, Chief Counsel and Staff Director 

KOLAN DAVIS, Republican Chief Counsel and Staff Director 

SUBCOMMITTEE ON PRIVACY, TECHNOLOGY AND THE LAW

AL FRANKEN, Minnesota, Chairman 

CHUCK SCHUMER, New York 

SHELDON WHITEHOUSE, Rhode Island 

RICHARD BLUMENTHAL, Connecticut 

TOM COBURN, Oklahoma 

ORRIN G. HATCH, Utah 

LINDSEY GRAHAM, South Carolina 

ALVARO BEDOYA, Democratic Chief Counsel 

ELIZABETH HAYS, Republican General Counsel 
(III) 

C O N T E N T S 

STATEMENTS OF COMMITTEE MEMBERS 

Page 

Franken, Hon. Al, a U.S. Senator from the State of Minnesota .......................... 1 

prepared statement .......................................................................................... 123 

Sessions, Hon. Jeff, a U.S. Senator from the State of Alabama .......................... 4 

WITNESSES 

Witness List ............................................................................................................. 37 

Pender, Jerome, M., Deputy Assistant Director, Criminal Justice Information 

Services Division, Federal Bureau of Investigation, U.S. Department of 

Justice, Clarksburg, West Virginia ..................................................................... 6 

prepared statement .......................................................................................... 39 

Mithal, Maneesha, Associate Director, Division of Privacy and Identity Protection, Federal Trade Commission, Washington, DC ........................................... 8 

prepared statement .......................................................................................... 44 

Martin, Brian, Director of Biometric Research, MorphoTrust USA, Jersey 

City, New Jersey .................................................................................................. 14 

prepared statement .......................................................................................... 57 

Acquisti, Alessandro, Associate Professor, Heinz College ad CyLab, Carnegie 

Mellon University, Pittsburgh, Pennsylvania .................................................... 16 

prepared statement .......................................................................................... 63 

Amerson, Larry, Sheriff, Calhoun County, Alabama, Anniston, Alabama, on 

Behalf of the National Sheriffs’ Association ...................................................... 18 

prepared statement .......................................................................................... 75 

Farahany, Nita A., Professor of Law, Duke Law School, and Professor of 

Genome Sciences & Policy, Institute for Genome Sciences & Policy, Duke 

University, Durham, North Carolina ................................................................. 19 

prepared statement .......................................................................................... 81 

Sherman, Rob, Manager of Privacy and Public Policy, Facebook, Washington, 

DC .......................................................................................................................... 22

prepared statement .......................................................................................... 92 

Lynch, Jennifer, Staff Attorney, Electronic Frontier Foundation, San Francisco, California .................................................................................................... 23 

prepared statement .......................................................................................... 100 

QUESTIONS 

Questions submitted by Hon. Al Franken for Jerome Pender, Maneesha 

Mithal, Brian Martin, Alessandro Acquisti, Rob Sherman, and Jennifer 

Lynch ..................................................................................................................... 127 

QUESTIONS AND ANSWERS 

Responses of Jerome Pender to questions submitted by Senator Franken ........ 134 

Responses of Maneesha Mithal to questions submitted by Senator Franken .... 137 

Responses of Brian Martin to questions submitted by Senator Franken ........... 139 

Responses of Alessandro Acquisti to questions submitted by Senator Franken 141 

Responses of Rob Sherman to questions submitted by Senator Franken ........... 145 

Responses of Jennifer Lynch to questions submitted by Senator Franken ........ 147 
Page

IV 

MISCELLANEOUS SUBMISSIONS FOR THE RECORD 

Face Book, Facebook.com: 

Approving and Removing Tag, instructions ................................................... 149 

Detroit, Michigan, Code of Ordinance, City code .................................................. 150 

Electronic Privacy Information Center (EPIC), Marc Rotenberg, Executive 

Director, Ginger P. McCall, Director, Open Government Program, and 

David Jacobs, Consumer Protection Fellow, July 18, 2012, joint letter .......... 155 

Federal Bureau of Investigation, Richard W. Vorder Bruegge, Quantico, Virginia, report .......................................................................................................... 156 

Westlaw, Thomson Teuters: 

Federal Anti-Protest law, Public Law—112–98, March 8, 2012 ................... 174 

Hawaii Anti-Protest law, Title 38, Chapter 852, HRS §852–1 ..................... 176 

Illinois Anti-Protest law, Chapter 740, Act 14 ............................................... 179 

Maryland Anti-Protest law, Maryland Code, Criminal Law, § 10–201 ....... 185 

Michigan law allowing anti-protest ordinance ............................................... 202 

Security Industry Association (SIA), Don Erickson, Chief Executive Officer, 

Alexandria, Virginia, January 31, 2012, letter .................................................. 266 

Tag Suggestions, instructions: Windows Photo Viewer ................................. 268 

Texas Anti-Protest law, V.T.C.A, Business & Commerce § 503.001 ............ 269 

ADDITIONAL SUBMISSIONS FOR THE RECORD 

Submissions for the record not printed due to voluminous nature, previously 

printed by an agency of the Federal Government, or other criteria determined by the Committee, list: ............................................................................. 273 

EPIC Comments—January 31, 2012.: http://www.ftc.gov/os/comments/ 

facialrecognitiontechnology/00083-0982624.pdf. ............................................... 273 

National Institute of Justice (NIJ), William A. Ford, Director, State of Research, Development and Evaluation.: T3https://www.eff.org/sites/default/ 

files/ford-State-of-Research-Development-and-Evaluation-atNIJ.pdf#page=17. ................................................................................................. 274 

Farahany, Nita A., Testimony Attachment—Pennsylvania Law Review: 

http://www.pennumbra.com/issues/pdfs/160-5/Farahany.pdf. .................... 273 
(1) 

WHAT FACIAL RECOGNITION TECHNOLOGY 

MEANS FOR PRIVACY AND CIVIL LIBERTIES 

WEDNESDAY, JULY 18, 2012 

U.S. SENATE, SUBCOMMITTEE ON PRIVACY, TECHNOLOGY, AND THE LAW, COMMITTEE ON THE JUDICIARY, Washington, DC. 

The Subcommittee met, pursuant to notice, at 2:36 p.m., in Room 

SD–226, Dirksen Senate Office Building, Hon. Al Franken, Chairman of the Subcommittee, presiding. 

Present: Senators Franken, Whitehouse, and Blumenthal. 

Also present. Senator Sessions. 

OPENING STATEMENT OF HON. AL FRANKEN, A U.S. SENATOR 

FROM THE STATE OF MINNESOTA 

Chairman FRANKEN. This hearing will be called to order. Welcome to the fourth hearing of the Subcommittee on Privacy, Technology, and the Law. Today’s hearing will examine the use of facial 

recognition technology by the Government and the private sector 

and what that means for privacy and civil liberties. 

I want to be clear: There is nothing inherently right or wrong 

with facial recognition technology. Just like any other new and 

powerful technology, it is a tool that can be used for great good. 

But if we do not stop and carefully consider the way we use this 

technology, it could also be abused in ways that could threaten 

basic aspects of our privacy and civil liberties. I called this hearing 

so we can just start this conversation. 

I believe that we have a fundamental right to control our private 

information, and biometric information is already among the most 

sensitive of our private information, mainly because it is both 

unique and permanent. You can change your password. You can 

get a new credit card. But you cannot change your fingerprint, and 

you cannot change your face—unless, I guess, you go to a great 

deal of trouble. 

Indeed, the dimensions of our faces are unique to each of us— 

just like our fingerprints. And just like fingerprint analysis, facial 

recognition technology allows others to identify you with what is 

called a ‘‘faceprint’’—a unique file describing your face. 

But facial recognition creates acute privacy concerns that fingerprints do not. Once someone has your fingerprint, they can dust 

your house or your surroundings to figure out what you have 

touched. 

Once someone has your faceprint, they can get your name, they 

can find your social networking account, and they can find and 
2 

track you in the street, in the stores that you visit, the Government 

buildings you enter, and the photos your friends post online. Your 

face is a conduit to an incredible amount of information about you, 

and facial recognition technology can allow others to access all of 

that information from a distance, without your knowledge, and in 

about as much time as it takes to snap a photo. 

People think of facial recognition as something out of a science 

fiction novel. In reality, facial recognition technology is in broad 

use today. If you have a driver’s license, if you have a passport, if 

you are a member of a social network, chances are good that you 

are part of a facial recognition data base. 

There are countless uses of this technology, and many of them 

are innovative and quite useful. The State Department uses facial 

recognition technology to identify and stop passport fraud—preventing people from getting multiple passports under different 

names. Using facial recognition technology, Sheriff Larry Amerson 

of Calhoun County, Alabama, who is with us here today, can make 

sure that a prisoner being released from the Calhoun County jail 

is actually the same prisoner that is supposed to be released. That 

is useful. Similarly, some of the latest smartphones can be unlocked by the owner by just looking at the phone and blinking. 

But there are uses of this technology that should give us pause. 

In 2010, Facebook, the largest social network, began signing up 

all of its then 800 million users in a program called Tag Suggestions. Tag Suggestions made it easier to tag close friends in photos, 

and that is a good thing. 

But the feature did this by creating a unique faceprint for every 

one of those friends. And in doing so, Facebook may have created 

the world’s largest privately held data base of faceprints—without 

the explicit consent of its users. To date, Tag Suggestions is an optout program. Unless you have taken the time to turn it off, it may 

have already been used to generate your faceprint. 

Separately, last year, the FBI rolled out a Facial Recognition 

Pilot program in Maryland, Michigan, and Hawaii that will soon 

expand to three more States. This pilot lets officers in the field 

take a photo of someone and compare it to a Federal data base of 

criminal mug shots. The pilot can also help ID a suspect in a photo 

from an actual crime. Already, several other States are setting up 

their own facial recognition systems independently of the FBI. 

These efforts will catch criminals. In fact, they already have. 

Now, many of you may be thinking that that is an excellent 

thing, and I agree. But unless law enforcement facial recognition 

programs are deployed in a very careful manner, I fear that these 

gains could eventually come at a high cost to our civil liberties. 

I fear that the FBI pilot could be abused to not only identify protesters at political events and rallies, but to target them for selective jailing and prosecution, stifling their First Amendment rights. 

Curiously enough, a lot of the presentations on this technology by 

the Department of Justice show it being used on people attending 

political events or other public gatherings. 

I also fear that without further protections, facial recognition 

technology could be used on unsuspecting civilians innocent of any 

crime, invading their privacy and exposing them to potential false 

identifications. 
3 

Since 2010, the National Institute of Justice, which is a part of DOJ, has spent $1.4 million to develop facial recognition-enhanced 

binoculars that can be used to identify people at a distance and in 

crowds. It seems easy to envision facial recognition technology 

being used on innocent civilians when all an officer has to do is 

look at them through his binoculars or her binoculars. 

But facial recognition technology has reached a point where it is 

not limited to law enforcement and multi-billion-dollar companies. 

It can also be used by private citizens. Last year, Professor 

Alessandro Acquisti of Carnegie Mellon University, who is testifying today, used a consumer-grade digital camera and off-the-shelf 

facial recognition software to identify one out of three students 

walking across a campus. 

I called this hearing to raise awareness about the fact that facial 

recognition already exists right here, today, and we need to think 

about what that means for our society. I also called this hearing 

to call attention to the fact that our Federal privacy laws are almost totally unprepared to deal with this technology. 

Unlike what we have in place for wiretaps and other surveillance 

devices, there is no law regulating law enforcement use of facial 

recognition technology. And current Fourth Amendment case law 

generally says that we have no reasonable expectation of privacy 

in what we voluntarily expose to the public; yet we can hardly 

leave our houses in the morning without exposing our faces to the 

public. So law enforcement does not need a warrant to use this 

technology on someone. It might not even need to have a reasonable suspicion that the subject has been involved in a crime. 

The situation for the private sector is similar. Federal law provides some protection against true bad actors that promise one 

thing yet do another. But that is pretty much as far as the law 

goes. If a store wants to take a photo of your face when you walk 

in and generate a faceprint—without your permission—they can do 

that. They might even be able to sell it to third parties. 

Thankfully, we have a little time to do better. While this technology will in a matter of time be at a place where it can be used 

quickly and reliably to identify a stranger, it is not there quite just 

yet. And so I have called the FBI and Facebook here today to challenge them to use their position as leaders in their fields to set an 

example for others before this technology is used pervasively. 

The FBI already has some privacy safeguards in place. But I still 

think that they could do more to prevent this technology from 

being used to identify and target people engaging in political protests or other free speech. I think the FBI could do more to make 

sure that officers use this technology only when they have good 

reason to think that someone is involved in a crime. I also think 

that if the FBI did these things, law enforcement agencies around 

the country would follow. 

For their part, Facebook allows people to use Tag Suggestions 

only on their close friends. But I think Facebook could still do more 

to explain to its users how it uses facial recognition and to give 

them better choices about whether or not to participate in Tag Suggestions. I think that Facebook could make clear to its users just 

how much data it has and how it will and will not use its large 

and growing data base of faceprints. And I think that if Facebook 
4 

did these things, they would establish a best practice against which 

other social networks would be measured. 

My understanding is that for the past few months, Facebook Tag 

Suggestions has been temporarily disabled to allow for some technical maintenance. It seems to me that Facebook has the perfect 

opportunity to make changes to its facial recognition program when 

it brings Tag Suggestions back online. 

I am also calling the Federal Trade Commission to testify because they are in the process of actually writing best practices for 

the use of this technology in industry. I urge the Commission to 

use this as an opportunity to guarantee consumers the information 

and choices they need to make informed decisions about their privacy. 

In the end, though, I also think that Congress may need to act, 

and it would not be the first time it did. In the era of J. Edgar Hoover, wiretaps were used freely with little regard to privacy. Under 

some Supreme Court precedents of that era, as long as the wiretapping device did not actually penetrate the person’s home or 

property, it was deemed constitutionally sound—even without a 

warrant. And so in 1968, Congress passed the Wiretap Act. Thanks 

to that law, wiretaps are still used to stop violent and serious 

crimes. But police need a warrant before they get a wiretap. And 

you cannot wiretap someone just because they are a few days late 

on their taxes. Wiretaps can be used only for certain categories of 

serious crimes. 

I think that we need to ask ourselves whether Congress is in a 

similar position today as it was 50 or 60 years ago before the passage of the Wiretap Act. I hope the witnesses today will help us 

consider this and all of the different questions raised by this technology. 

I was going to turn it over to my friend and Ranking Member, 

Senator Coburn, but I do not think he would have a lot to say at 

this moment. 

[Laughter.] 

Chairman FRANKEN. I am sure he will have some great questions. 

What I would like to do is introduce our first panel of witnesses. 

But before I do, I would like to give my esteemed colleague, Senator Sessions, the opportunity to make an introduction of the sheriff, who is going to be on the second panel from your own State. 

STATEMENT OF HON. JEFF SESSIONS, A U.S. SENATOR FROM 

THE STATE OF ALABAMA 

Senator SESSIONS. That would be wonderful. Thank you, Mr. 

Chairman. Those are remarks that we need to think about as we 

go forward with new technologies, and it takes some effort to get 

to the bottom of it. 

I am honored to take a few moments to introduce my friend, 

Sheriff Larry Amerson, who has served for 18 years as sheriff in 

Calhoun County, Alabama, and Anniston. He is a graduate of Jacksonville State University, one of my superb universities, with a 

B.A. in law enforcement, finally becoming sheriff. He served for 14 

years as deputy sheriff in Calhoun County. He currently serves as 

the 71st president of the National Sheriffs’ Association and is also 
5 

the chairman of the National Sheriffs’ Institute Education and 

Training Committee and vice chair of the Court Security Committee. He is a certified jail manager and past member of the FBI 

Criminal Justice Information System’s Southern Working Group, 

and that Criminal Justice Information System is a lot of what we 

will be talking about today, how that system works. 

Sheriff, it is great to see you. Thank you for coming, and I am 

pleased to have this opportunity to introduce you. 

Mr. Chairman, could I just say a couple of things? 

Chairman FRANKEN. Absolutely. 

Senator SESSIONS. I would like to come back if you would allow 

me, but I might not be able to. 

Chairman FRANKEN. I understand. 

Senator SESSIONS. We need to look at facial recognition and see 

how it works and where it can be beneficial consistent with our 

constitutional rights and privileges that we value in our country. 

But it is a matter that I have dealt with for a long time, and there 

are a lot of people who would like to see a major enhancement of 

the facial identification system used at airports for security and 

that sort of thing. And there are some fundamental weaknesses at 

this point with that as a practical matter. 

The fingerprint has been in use for 50 years, I guess. Virtually 

every criminal in America has had his fingerprint placed in records 

that can be ascertained by even a local police officer at his police 

car. He can have people put their hands on a machine, and it will 

read that to see if the ID he presented may be false and he may 

be somebody else, maybe a fugitive from justice. So the fingerprint 

system is really, really proven. And you have the criminal histories 

that are available to law officers when they produce that. 

So if we start with the facial recognition—and maybe it is time 

to start with some of that. But if we start with it, we do not have 

many people in it. There are not that many people who have been 

identified who have had their visage imprinted and can be drawn. 

And terrorists around the world, presumably we do not have their 

facial things, where we may have been collecting their fingerprints 

for years. 

Secretary Ridge, when he was Homeland Security Secretary, 

tried to figure a way to deal with the situation at the airports. A 

lot of people wanted to use facial recognition, Mr. Chairman, because they thought it would be quicker, people would just go right 

on through the system. But, you know, I would ask a simple question: If there is no bank of visages, what good is it? And why 

couldn’t you use a fingerprint situation where you put your fingerprint in, the computer reads it, even if you check through and you 

go down and wait to get on the plane, if a minute, five minutes, 

three minutes later, it comes back this is a terrorist, you can go 

down and get the man. 

When he left, I would say I was kind of pleased. I had not talked 

to him for some time about it. He said, ‘‘Well, I have one bit of advice for my successor: Emphasize the fingerprint.’’ So I felt like he 

had concluded that is a suggestion. 

So I do not know how far you can go with utilizing the face system effectively. I was a Federal prosecutor for 15 years. Knowing 

how the system works today, I know it would take many years to 
6 

get it to compete with the fingerprint system for basic law enforcement work. But, Mr. Chairman, there could be certain things, like 

in a jail. You suggested that. There are other things that could 

work right now. 

So thank you for giving me the opportunity to share those 

thoughts. You have got a great panel of witnesses. I salute you for 

investing the time and effort to wrestle with these important 

issues. 

Chairman FRANKEN. Well, thank you for your very well-made 

comments, and these are questions that we are starting to deal 

with in today’s hearing, so thank you. 

Senator SESSIONS. If I come back, I would like to ask some of 

those. If not, I will try to submit it for the record, if you do not 

mind. 

Chairman FRANKEN. Absolutely. 

Senator SESSIONS. Thank you. 

Chairman FRANKEN. Maybe we should call it, after listening to 

you, ‘‘visage recognition technology.’’ 

[Laughter.] 

Chairman FRANKEN. Just to confuse people, I would like to do 

that. 

Chairman FRANKEN. Now I would like to introduce our first 

panel of witnesses. 

Jerome Pender is the Deputy Assistant Director of the Operations Branch at the FBI’s Criminal Justice Information Division. 

He manages information technology for many of the FBI’s biometric systems and helps oversee the deployment of a pilot facial recognition program as part of the FBI’s Next Generation Identification Initiative. Prior to joining the FBI, Mr. Pender served as the 

executive director of Information Technology for UBS Warburg. He 

holds a master’s degree in computer science from Johns Hopkins 

and is a graduate of the United States Air Force Academy. Thank 

you for being here. 

Maneesha Mithal is the Associate Director of the Federal Trade 

Commission’s Division of Privacy and Identity Protection. She oversees work on commercial privacy, data security, and credit reporting, and works to ensure companies comply with the FTC Act’s unfair or deceptive practices provision. Before joining the FTC, Ms. 

Mithal was an attorney at the Washington office of Covington & 

Burling. She earned her undergraduate and law degrees from 

Georgetown University. 

Thank you again, both of you, for being here today. I really hope 

that your presence here will mark the start of a productive dialogue about this technology going forward. Your complete written 

testimony will be made a part of the record. You each have about 

5 minutes for opening remarks that you would like to make. 

Mr. Pender, would you like to begin? 

STATEMENT OF JEROME M. PENDER, DEPUTY ASSISTANT DIRECTOR, CRIMINAL JUSTICE INFORMATION SERVICES DIVISION, FEDERAL BUREAU OF INVESTIGATION, U.S. DEPARTMENT OF JUSTICE, CLARKSBURG, WEST VIRGINIA 

Mr. PENDER. Certainly. Thank you. Mr. Chairman, I would like 

to thank the Subcommittee for the opportunity to discuss the FBI’s 
7 

Next Generation Identification Program, NGI. The FBI is committed to ensuring appropriate privacy protections are in place as 

we deploy NGI technologies, including facial recognition, and that 

the capabilities are implemented and operated with transparency 

and full disclosure. 

The FBI began collecting criminal history on a national level in 

1924. From 1924 until 1999, fingerprints and associated criminal 

history information, including mug shot photographs, were received 

in the U.S. mail and processed manually. In 1999, with the launching of the Integrated Automated Fingerprint Identification System, 

fingerprints were searched, processed, and stored using automation. 

The NGI Program, which is on scope, on schedule, and on cost, 

and 60 percent deployed, is enabling the FBI to meet its criminal 

justice mission. It will use facial recognition to automate for the 

first time the processing of mug shots. 

NGI is being deployed in seven separate increments. Increment 

four includes the facial recognition system. It was deployed as a 

pilot in February 2012 and is scheduled for full operational capability in the summer of 2014. The objective of the pilot is to conduct 

image-based facial recognition searches of the FBI’s national repository and provide investigative candidate lists to agencies submitting queries. 

The goals of the pilot are to test the facial recognition processes, 

resolve policy and processing issues, solidify privacy protection procedures, and address user concerns. 

The pilot provides a search of the national repository of photos 

consisting of criminal mug shots, which were taken at the time of 

a criminal booking. Only criminal mug shot photos are used to populate the national repository. Query photos and photos obtained 

from social networking sites, surveillance cameras, and similar 

sources are not used to populate the national repository. It contains 

approximately 12.8 million photos. 

The Facial Recognition Pilot permits authorized law enforcement 

agencies to submit queries for a facial recognition search of the national repository. It can be queried by authorized criminal justice 

agencies for criminal justice purposes. 

Access is subject to all rules regarding access to FBI CJIS systems information and subject to dissemination rules for authorized 

criminal justice agencies. The investigative response provided to a 

submitting agency will include the number of candidates requested, 

in ranked order, along with a caveat noting that the response 

should only be used as an investigative lead. 

In accordance with Section 208 of the E-Government Act of 2002, 

facial recognition was initially addressed by the FBI’s June 9, 2008, 

Interstate Photo System Privacy Impact Assessment, or PIA. In coordination with the FBI’s Office of the General Counsel, the 2008 

PIA is currently in the process of being renewed by way of Privacy 

Threshold Analysis, with an emphasis on facial recognition. An updated PIA is planned and will address all evolutionary changes 

since the preparation of the 2008 PIA. 

Each participating pilot State or agency is required to execute a 

Memorandum of Understanding, MOU, that details the purpose, 

authority, scope, disclosure, and use of information, and the secu-
8 

rity rules and procedures associated with piloting. Pilot participants are advised that all information is treated as ‘‘law enforcement sensitive’’ and protected from unauthorized disclosure. 

Information derived from the pilot search requests and resulting 

responses are to be used only as an investigative lead. Results are 

not to be considered as positive identifications. 

In February 2012, the State of Michigan successfully completed 

an end-to-end Facial Recognition Pilot transaction and is currently 

submitting facial recognition searches to CJIS. MOUs have also 

been executed with Hawaii and Maryland; South Carolina, Ohio, 

and New Mexico are engaged in the MOU review process for Facial 

Recognition Pilot participation. 

In summary, the FBI’s Next Generation Identification Program 

is on scope, on schedule, on cost, and 60 percent deployed. The Facial Recognition Pilot which began operation in February 2012 

searches criminal mug shots and provides investigative leads. The 

Facial Recognition Pilot is evaluating and solidifying policies, procedures, and privacy protections. Full operational capability for facial recognition is scheduled for the summer of 2014. 

Thank you. 

[The prepared statement of Mr. Pender appears as a submission 

for the record.] 

Chairman FRANKEN. Thank you, Mr. Pender. 

Ms. Mithal. 

STATEMENT OF MANEESHA MITHAL, ASSOCIATE DIRECTOR, 

DIVISION OF PRIVACY AND IDENTITY PROTECTION, FEDERAL TRADE COMMISSION, WASHINGTON, D.C. 

Ms. MITHAL. Thank you, Chairman Franken. I am Maneesha 

Mithal with the Federal Trade Commission. I appreciate the opportunity to present the Commission’s testimony on the commercial 

uses of facial recognition technology, the potential benefits, and privacy implications. 

Imagine a world where you are walking down the street and a 

stranger takes a picture of you with their smartphone. The stranger is then able to pull up not only your name but where you live, 

how much you paid for your house, and who your close friends are. 

Imagine another scenario where you walk into a store and a digital sign scans your face, links you with a loyalty card, and greets 

you with a message: ‘‘Jane Doe, I see you have bought Slimfast before. Here is a coupon for $1 off your next purchase.’’ 

These scenarios are not far from becoming a reality. Some consumers might think they are innovative and they want to participate in them. Others may find them invasive. Today facial recognition is being used commercially for a variety of purposes, many of 

them beneficial to consumers. For example, as you mentioned, companies are using the technology to allow consumers to unlock their 

smartphones using their faces rather than their passwords, to 

allow consumers to upload their faces to a website to try on make 

up hair styles and eyeglasses, and to help consumers manage and 

organize photos. 

In December 2011, the Commission hosted a workshop to examine these current and future uses of facial recognition, as well as 

the privacy implications they raise. In my statement today, I would 
9 

like to discuss four themes that emerged from the workshop and 

conclude by setting forth our next steps in this area. 

First, many workshop participants highlighted the recent growth 

in the commercial use of facial recognition technologies. Until recently, because of high costs and limited accuracy, companies did 

not widely use these technologies. However, several recent developments have brought steady improvements. For example, better 

quality digital cameras and lenses create higher-quality images 

from which biometric data can be more easily extracted. Recent 

technological advances have been accompanied by a rapid growth 

in the availability of online photos. For example, approximately 2.5 

billion photos are uploaded to Facebook each month. As a result, 

companies do not need to purchase proprietary sets of identified 

images, thereby lowering costs and making facial recognition technologies commercially viable for a broad range of entities. 

Second, we learned about current applications of facial recognition technologies. In one application, the technology can simply be 

used for pure facial detection—that is, to determine that a photo 

has a face in it. Current uses include refining search engine results 

to include only those results that contain a face, locating faces in 

images in order to blur them, or ensuring that the frame for a 

video chat feed actually includes a face. 

In another application, the technology allows companies to assess 

characteristics of facial images. For instance, companies can identify moods or emotions from facial expressions to determine a player’s engagement with a video game or a viewer’s excitement during 

a movie. 

Companies can also determine demographic characteristics of a 

face such as age and gender to deliver targeted ads in real time in 

retail spaces. 

The use of facial recognition technology that potentially raises 

the most privacy concerns is the use to identify anonymous individuals in images. One of the most prevalent current uses of this application is to enable semiautomated photo tagging or photo organization on social networks and in photo management applications. 

Third, in addition to these current uses, panelists discussed the 

ways in which facial recognition could be implemented in the future. For example, will it become feasible to use facial recognition 

to identify previously anonymous individuals in public places or in 

previously unidentified photos online? In a 2011 study, which we 

will be hearing about, Carnegie Mellon researchers were able to 

identify individuals in previously unidentified photos from a dating 

site by using facial recognition technology to match them to their 

Facebook profile photos. 

Finally, panelists discussed the privacy concerns associated with 

facial recognition. For example, a mobile app that could, in realtime, identify previously anonymous individuals on the street or in 

a bar and correlate a name with a person’s physical address could 

raise serious physical safety concerns. 

Following the workshop, Commission staff has been developing a 

report that builds on the principles that the Commission outlined 

in its March 2012 privacy report. Those principles are: privacy by 

design, simplified choice, and improved transparency. The report 

discusses the application of these principles to the realm of facial 
10 

recognition, and we should be issuing a report in the coming 

months. 

Thank you for the opportunity to provide the Commission’s 

views, and we look forward to working with Congress on this important issue. 

[The prepared statement of Ms. Mithal appears as a submission 

for the record.] 

Chairman FRANKEN. Thank you, Ms. Mithal. 

Mr. Pender, the FBI allows searches of its facial recognition data 

base. They are done only for criminal justice purposes, and that is 

a good thing. But the term ‘‘criminal justice purpose’’ is kind of 

broad, so I am concerned that this system allows law enforcement 

to identify and target people marching in a rally or protesting in 

front of a courthouse because in all three States where the pilot is 

operating, it is technically a crime to block a sidewalk or obstruct 

the entrance to a building. 

Mr. Pender, has the FBI issued a rule prohibiting or discouraging jurisdictions from using facial recognition technology in a 

way that could stifle free speech? And if not, will the FBI consider 

doing this? 

Mr. PENDER. Certainly as we are deploying the NGI system, we 

are extremely concerned to make sure that we have appropriate 

protections in it to ensure there is not any invasion of privacy or 

those sorts of things. 

The definition of ‘‘criminal justice purpose’’ is defined in 28 CFR 

Section 20.3(b), and it has nine particular activities that are part 

of the administration of criminal justice. In the scenario that you 

mentioned about the protesters and potentially blocking the sidewalk, I think you are implying that an officer is taking a photo of 

someone for blocking the sidewalk on the pretext of putting them 

into some type of data base. So I can say a few things about that. 

First of all, the only photos that will go into the data base are 

the criminal mug shot photos, so the probe photos that are being 

searched through the system do not ever go into the data base. 

Then as regards to whether or not the particular person blocking 

the sidewalk could even be searched, the officer would have to 

clearly articulate which of those administration of criminal justice 

functions that they are trying to perform, and the way you have 

let out the scenario there, you are implying that they are not really 

interested in blocking the sidewalk. They are using it as a pretext 

for something else, and that would not be a valid use of the system 

under the current rules. 

Again, we take this very seriously, so that is certainly the reason 

that we are deploying the system slowly in a pilot phase to work 

out any details, make sure that there is appropriate training and 

guidance in place, and so that is an important part of our process. 

One of the things that the MOUs that we sign with the agencies 

that are going to access the system require is an audit process, so 

the local agencies are required to audit the use of the system on 

an annual basis to detect any type of misuse. And then, in addition 

to that, within our FBI CJIS Division we have an audit unit that 

goes out and does triennial audits of the same agencies, and that 

is done as a little bit of a safety net, a double-check on the audits, 
11 

as well as to be sure that the audit processes are in place and 

being done effectively. 

In those audits, if any misuse is detected, there is a full range 

of options that is defined in the sanctions process, and that could 

range from administrative letters, that sort of thing, to removal of 

access from the system, either on an individual or an agency basis, 

if the controls are not effective, up to and including criminal prosecution for misuse. 

Chairman FRANKEN. OK. How do you define ‘‘misuse’’ ? First of 

all, have any audits been produced yet? 

Mr. PENDER. The audit process that I am talking about is with 

regards to access to criminal history in general. It has been longstanding for the last many decades. The photos are part of that 

criminal history data base, so all of those same standards apply. 

At this point, we have not done any audits specific to the use of 

facial recognition. That is what we are in the process of developing 

through the pilot. 

Chairman FRANKEN. OK. So is there anything that explicitly in 

your pilot discourages the use of this technology at a rally or a political event? 

Mr. PENDER. I cannot think of something that says you should 

not use this at a political event. I think it is defined in the terms 

of the positive where it is allowed to be used, and that would be 

outside of what is permitted. But certainly we are—that is the purpose of doing the slow deployment, is to identify if there are particular gray areas that need to be trained—— 

Chairman FRANKEN. Part of the reason I bring this up is that the 

FBI’s own presentations of this technology—I do not know if we 

have a blow-up of this, but it shows it being used to identify people 

at a political rally. That is what the FBI did. So that is—you know, 

I mean, this is done by the Obama administration. It is at an 

Obama rally. One of them is. And one is at a Hillary rally, and, 

you know, they have made up. 

[Laughter.] 

Chairman FRANKEN. She is a great Secretary of State. But they 

might be sending the wrong message, don’t you think? 

Mr. PENDER. I am not familiar with that particular presentation. 

I am not familiar with the photos, but certainly if there are photos 

of a political rally, what we are—the NGI system that we are deploying and what we are doing, we absolutely have no intention of 

going out. It absolutely will be limited to the mug shot photos and 

the criminal history data base. 

Chairman FRANKEN. OK. In a similar vein, will the FBI consider 

telling States in its facial recognition program that they should use 

the technology to identify someone only if they have a probable 

cause that they have been involved in a criminal activity? 

Mr. PENDER. The mug shot photos are part of the criminal history data base, and so this is an issue that we have been working 

with for many years on when is it appropriate to distribute information out of the criminal history data base. And so in April 2001, 

there were some questions about that, and we sent out what we 

call a contributor letter that clarifies when it is appropriate to use 

the system or not. And the language in that particular letter says 

that the officer must clearly articulate one of the administration of 
12 

criminal justice purposes that they are administering, and if they 

are basing it on the detection or apprehension function, they have 

to have an articulable suspicion or a reasonable basis for the 

search. 

So, again, that was in the context of criminal history, but mug 

shots are part of that. And certainly as we are deploying the system—— 

Chairman FRANKEN. Well, I understand that the mug shots are 

the data base from which they are looking. I am wondering who 

they choose to search, I mean, who they choose to take a picture 

of, say, to see if they match the data base. That is what I am asking. 

Mr. PENDER. Right. The probe photos are photos that they are 

searching against the data base. They have to be able to have that 

articulable suspicion or reasonable basis for performing the search. 

And certainly, again, that is the reason for going slowly. We have 

a series of working groups that we are working with, our State and 

local partners from the Advisory Policy Board, as Senator Sessions 

was talking about, that were working on it and making sure that 

the policies are clear, that we have appropriate training programs 

in place as well. Prior to accessing our NCIC system, for example, 

an individual is required to have training and a certification test 

that is repeated every two years to maintain the current certification. And we require annual training on security practices as 

well. 

So if there are appropriate enhancements that we need to make 

specific to facial recognition, we are very open to doing that. 

Chairman FRANKEN. OK. Thank you. 

Ms. Mithal, my understanding is that the Commission is in the 

process of proposing best practices for the commercial use of facial 

recognition. I want to urge you to make a very simple rule one of 

your best practices; that is, if a company wants to create a unique 

faceprint for someone to identify them, they need to get their permission first. Will the Commission do that? 

Ms. MITHAL. Thank you. As I mentioned, the Commission is considering best practices, and I am certainly sure that that is one of 

the issues that they are considering, and I will take it back to them 

that you have requested us to consider this. 

The other thing I would note is that in our March 2012 privacy 

report, we talked about the importance of providing consumers 

with meaningful choice when their information is collected. At a 

minimum, what we think that means is that a disclosure has to be 

provided very clearly outside the privacy policy so that consumers 

can make informed decisions about their data. 

Chairman FRANKEN. That does not sound like a yes. I do not 

think this is a heavy lift, frankly. While Federal law says nothing 

about this, two States—Illinois and Texas—both require a company 

to get a customer’s consent before they create a biometric for them. 

So, at least in theory, this is already the standard that national 

companies have to meet, and without objection, I would like to 

enter these laws into the record. 

[The information appears as a submission for the record.] 

Chairman FRANKEN. Could you pass this on to the Commission? 

I will give it to you. 
13 

Ms. MITHAL. We will take a look, and I will pass it on, yes. 

Thank you. 

Chairman FRANKEN. Thank you. Thank you very much. 

Ms. Mithal, when a social network or an app company is creating 

a faceprint to identify someone in a photo, what is the Commission’s position on the kind of notice they need to provide their 

users? Is the best practice to tell their users, you know, ‘‘We are 

going to create a unique faceprint for you’’ ? Or is it something less 

than that? 

Ms. MITHAL. Sir, again, this is exactly the type of issue the Commission is currently considering, and I cannot get in front of my 

Commission on this. They are really considering these issues. But 

if you look at what the Commission has said publicly in terms of 

our privacy report, we have called for transparency. And what that 

means is clear, simple, concise notices, not in legalese. 

Chairman FRANKEN. OK. Clear, simple, and precise. 

Ms. MITHAL. Concise. 

Chairman FRANKEN. Concise. Oh, I am sorry. 

Ms. MITHAL. Precise would be good, too. 

Chairman FRANKEN. Thank you for that validation. 

[Laughter.] 

Chairman FRANKEN. OK. Well, I want to thank you both for your 

testimony and call the second panel. Thank you, Ms. Mithal and 

Mr. Pender. 

Ms. MITHAL. Thank you. 

Mr. PENDER. Thank you. 

Chairman FRANKEN. We have now our second panel, and let me 

introduce them while they take their seats. 

We have Mr. Brian Martin, who is director of Biometric Research 

for MorphoTrust USA, a leading biometrics company that supplies 

facial recognition technology to the Federal Government and many 

State governments. Mr. Martin has over 15 years of experience in 

the biometrics and has helped develop numerous biometric technologies involving iris, fingerprint, and facial recognition. He 

earned his Ph.D. in physics from the University of Pittsburgh. I 

called Mr. Martin to be our star technical witness who can begin 

our second panel by explaining how the technology actually works. 

Alessandro Acquisti is an associate professor of information technology and public policy at Carnegie Mellon University where his 

research focuses on the economics of privacy. Professor Acquisti is 

at the helm of not just one but several pioneering studies evaluating the privacy implications of facial recognition technology. He 

has received numerous awards for his research and expertise on 

privacy issues. Professor Acquisti earned a master’s and Ph.D. in 

information systems from UC-Berkeley and received a master’s in 

economics from Trinity College, Dublin, and from the London 

School of Economics. 

Sheriff Larry Amerson, whom Senator Sessions introduced earlier, is the president of the National Sheriffs’ Association and is 

also serving in his 18th year as sheriff of Calhoun County, Alabama, and that is in Anniston as the county seat? 

Mr. AMERSON. Yes, sir. 

Chairman FRANKEN. As part of his mission to modernize police 

operations, Sheriff Amerson is overseeing the implementation of 
14 

iris and facial recognition in Calhoun County jails and in the field. 

Sheriff Amerson has had a long, successful career in law enforcement. Sheriff Amerson earned his bachelor’s degree in law enforcement from Jacksonville State University. 

Nita Farahany is an associate professor of law at the Duke University School of Law and is a leading scholar on the ethical, legal, 

and social implications of emerging technologies. She was appointed in 2010 by President Obama to serve on the Presidential 

Commission on the Study of Bioethical Issues. Professor Farahany 

has written on the application of the Fourth Amendment to emerging technology. She received her bachelor’s degree from Dartmouth 

College and a J.D. and Ph.D. in philosophy from Duke University. 

Rob Sherman is the manager of privacy and public policy at 

Facebook. He manages policy matters involving privacy, security, 

and online trust. Prior to joining Facebook, Mr. Sherman was an 

attorney at Covington & Burling, where he focused his practice on 

issues relating to privacy and online security. Mr. Sherman received his law degree from the University of Michigan and his undergraduate degree from the University of Maryland. 

Jennifer Lynch is a staff attorney at the Electronic Frontier 

Foundation, where she focuses on Government transparency and 

privacy issues. Ms. Lynch has written and spoken on biometrics 

collection, including the Government’s use of facial recognition 

technology. Before joining EFF, she served as a clinical teaching 

fellow with the Samuelson Law, Technology, and Public Policy 

Clinic at the UC-Berkeley School of Law and clerked for Judge A. 

Howard Matz in the Central District of California. She received 

both her undergraduate and law degrees from UC-Berkeley. 

Thank you all for joining us, and your complete written testimonies will be made part of the record. You each have approximately five minutes for any opening remarks that you would like 

to make. Mr. Martin, please start us off. 

STATEMENT OF BRIAN MARTIN, PH.D., DIRECTOR OF BIOMETRIC RESEARCH, MORPHOTRUST USA, JERSEY CITY, NEW 

JERSEY 

Mr. MARTIN. Thank you. Good afternoon, Chairman Franken. 

Thank you for asking MorphoTrust to testify on the capabilities of 

face recognition. 

As the director of Biometric Research for MorphoTrust, my team 

is responsible for the biometric technologies used by the U.S. Department of State, the Department of Defense, the FBI, and numerous motor vehicle/driver’s license systems. I am here today to 

testify on the state-of-the-art of face recognition. 

First, I would like to briefly explain how face recognition works. 

Now, face recognition is not new. The idea has been around for almost half a century. But only in the late 1990s did these ideas become commercialized. The different approaches are varied. They 

can be 2–D, a regular image; they can be 3–D from a special 3– 

D scanner. Face recognition can look at the shape of the face, or 

it can even look at microscopic features like your pores and wrinkles on your skin. 

In all cases, though, modern face recognition approaches are 

vastly more complicated than commonly perceived, where people 
15 

say, oh, they are just measuring, you know, the distance between 

the eyes and the nose or something. 

While there are several different approaches to face recognition, 

there are some general steps to face recognition. The first is what 

is called face detection, and this is exactly what your camera is 

doing when it tries to focus on the face. It is just trying to see if 

there is a face in the image. 

Another step is called feature registration and extraction, and 

this is maybe the more interesting case because this is where the 

individualized features of the face are extracted from an image and 

stored into a binary format which you have called a ‘‘faceprint’’ or 

‘‘facial template.’’ 

Now, these faceprints are vendor-specific, meaning they are not 

very useful outside of the face recognition system. They contain no 

more information than what was in the original image. They do not 

contain meta data or identity data about the person. They are just 

a different representation of what was already in the image. And 

they cannot be reverse engineered, so you cannot regenerate the 

image from the faceprint. 

After you have two or more faceprints, then you can perform facial matching, and facial matching, in the state of the art, can be 

as fast as tens of millions of matches per second on a modern computer. Typically, the faster you match, the less accurate the match 

is. This accuracy has been benchmarked by the U.S. Government 

since the early 1990s, and in a recent report from the National Institute of Standards and Technology in 2010, they said that the 

best face recognition algorithms are over 100 times better than 

they were a decade ago. So this means essentially from their report 

that an algorithm can determine if two faces belong to the same 

person 99.7 percent of the time, while only making a mistake about 

one in 1,000 times. In fact, face recognition is as good is as good 

as a human if the human is not a trained expert. 

Now, these accuracy numbers are for a staged or controlled setting. When you have variable lighting, when the person is not looking directly at the camera, or when it is a low-resolution image, 

then the accuracy does decrease, and that is an active area of research. 

Furthermore, when I quoted this 99 percent number, this is for 

verification when you are trying to determine if you are who you 

say you are, say, for instance, unlock your phone. Much more demanding is the application of identification where you are trying to 

determine an unknown identity from a gallery of individuals. So 

this would be where you are trying to generate an investigative 

lead from a mug shot data base. 

Identification is more complicated because it is essentially like 

performing many verifications. So if you had to perform a million 

verifications, then you are going to have a higher false positive rate 

because you have more chances to make a mistake. And that is 

why with identification applications, there is almost always a 

human in the loop, and this is even the case when you have a 

photo-tagging feature and you have to sit there and you actually 

have to tell that algorithm, ‘‘Did you make a mistake or not? ’’ ‘‘Yes, 

this is who the photo-tagging algorithm thinks it is.’’ 
16 

So to summarize, and maybe speculate on the future a little bit, 

I do not think that the accuracy of face recognition for good-quality 

images will continue to improve at the rate that it has in the last 

10 years. However, for the uncontrolled cases, where you are not 

looking at the camera, I do think that over the next couple decades, 

there will be a substantial improvement in accuracy to help these 

forensic type of face cases. 

Thank you for the opportunity to address the Subcommittee. I 

look forward to answering any of your questions. 

[The prepared statement of Mr. Martin appears as a submission 

for the record.] 

Chairman FRANKEN. Thank you, Mr. Martin. 

Mr. Acquisti. 

STATEMENT OF ALESSANDRO ACQUISTI, ASSOCIATE PROFESSOR, HEINZ COLLEGE AND CYLAB, CARNEGIE MELLON 

UNIVERSITY, PITTSBURGH, PENNSYLVANIA 

Mr. ACQUISTI. Thank you, Chairman Franken. It is an honor to 

appear before you today. I will discuss four findings from research 

on privacy and face recognition. 

The first finding is that while early computer algorithms vastly 

underperform humans in detecting and recognizing faces, modern 

ones have progressed to a point that they can outperform humans 

in certain tasks and can be found in consumer applications. Later 

on, billboards predicted the age of pedestrians, cameras estimated 

generation of crowds in a bar, online social networks identified people and tagged their names in photos. 

The second finding is that the convergence of face recognition, 

online social networks, and data mining will make it possible to 

identify people online and offline and infer sensitive information 

about them, starting from anonymous faces, and using only public 

data. 

In one experiment we completed last year, we took anonymous 

photos from a popular dating site where people used pseudonyms 

to protect their privacy, compared them using face recognition to 

public but identified photos from Facebook, and identified about 10 

percent of the anonymous members of the dating site. 

In another experiment, we identified about one-third of the participants, students on a college campus, simply taking photos of 

them on a webcam and comparing these photos in real time to images from Facebook. 

In a final experiment, we predicted the interests and Social Security numbers for some of the participants of the second experiment, 

combining face recognition with the algorithms we had developed 

in 2009 to predict SSNs from public data. We also developed a 

phone application which completes the process I just described on 

the mobile device in real time showing on the device screen the 

predicted sensitive information of the target subject overlaid on 

their face, and this is a screen shot of the application there. 

Social Security numbers are just an example of many sensitive 

data it is possible to infer, starting from an anonymous face and 

using public data. The results we obtained are not yet scalable to 

the entire American population due to computational costs, false 

positives, availability of facial images. But each of these hurdles is 
17 

being overcome by software and hardware improvements. In fact, 

some entities already have access to more powerful computational 

tools and larger and more accurate repositories of data than we do. 

In particular, online social networks are accumulating the largest 

known data bases of facial images, often tagged or linked to identified profiles, providing a public connection between a person’s facial 

biometrics and their real names. 

The third finding is that the process through which face recognition can undermine our notions of privacy and anonymity has already started, and its consequences will be nuanced and complex. 

Your phone, we will remind you of the name of someone at a party. 

However, it will also tell a stalker in a bar where you live. The 

hotel will greet you as you arrive in the lobby. However, also such 

person may infer your credit score the moment you enter the dealership and also predict in real time based on your online posts a 

psychological profile for you, and, therefore, nudge you to accept 

the steepest price for a car. An agency will be able to find missing 

children in an online data base; however, another agency could 

chill free speech by identifying via remote, high-definition cameras 

all the thousands of participants in a peaceful protest. 

The fourth finding is that, depending on which goals Congress intends to achieve in this area, different approaches may be considered: price of technologies, more commercial applications, legislation. However, if privacy and civil liberties are the concern here, 

it is not a given, not guaranteed that industry self-regulatory approaches will suffice. I say this for two reasons. One reason is that 

facial biometric data is particularly valuable. It provides a permanent, ubiquitous, and invisible means for identification and tracking online and offline. 

First to control the base facial biometrics will be able to provide 

valuable identity recognition services to others. Hence, competition 

for control over the data will be fierce and will likely come at the 

cost of individuals’ privacy. 

The second reason is that recent history in the markets for personal data suggest that firms will engage in progressively more 

invasive applications of face recognition over time. Current users of 

face recognition are limited not just by computational costs but by 

fear of consumer backlash. These initial applications that we see, 

however, could be considered as ‘‘bridgeheads.’’ In a way, they are 

designed to habituate us into accepting progressively more expansive services. Consider the frequency in which companies such as 

Facebook have engaged in changes to settings and defaults associated with users’ privacy so as to nudge users into disclosing and 

sharing more. Why? Because information is power. In the 21st century, the wealth of data accumulated about individuals and the 

staggering progress of behavioral research in using the data to influence individual behavior make it so that control over personal 

information implies power over the person. As control is tilting 

from data subjects to data holders, it is the balance of power within 

different entities which is at stake. 

Thank you. 

[The prepared statement of Mr. Acquisti appears as a submission 

for the record.] 

Chairman FRANKEN. Thank you, Mr. Acquisti. 
18 

Sheriff Amerson, please. 

STATEMENT OF LARRY AMERSON, SHERIFF, CALHOUN COUNTY, ALABAMA, ANNISTON, ALABAMA, ON BEHALF OF THE NATIONAL SHERIFFS’ ASSOCIATION 

Mr. AMERSON. Mr. Chairman, thank you for inviting me today to 

testify today on behalf of the National Sheriffs’ Association. Chartered in 1940, the National Sheriffs’ Association is a professional 

association dedicated to serving the Office of Sheriff and its affiliates throughout law enforcement with education, training, and information resources. NSA represents thousands of sheriffs, their 

deputies, and other law enforcement professionals, and concerned 

citizens nationwide. 

I applaud the Subcommittee for holding this important hearing 

on the implications of facial recognition for privacy and civil liberties. These are critical concerns that rightfully need to be debated 

and the rights of innocent citizens protected from unwarranted interference in their privacy and everyday lives. 

On the other hand, new technologies, especially facial recognition, already implemented in law enforcement, national defense, 

and the fight against terrorism, are a critical tool in protecting the 

rights of citizens, in ensuring the accurate identification of suspects, prisoners, and potential terrorists while it is protecting the 

safety of our citizens and law enforcement officers. 

There is a critical balance between protecting the rights of lawabiding citizens and providing law enforcement agencies with the 

most advanced tools to combat crime, properly identify suspects, 

catalogue those incarcerated in prisons and jails, and defending 

America from acts of terrorism. 

Most importantly, advances in facial recognition technology over 

the last 10 years will result in the end of the total reliance on 

fingerprinting, where it can take hours and even days to identify 

a suspect, fugitive, or person being booked into a jail, to the immediate identification of those known to have criminal records or who 

are wanted by law enforcement. It will surprise many in the room 

today to know that there is no national data base of those incarcerated in America’s jails at any one time. The use of facial recognition to provide instant identification of those incarcerated or under 

arrest will eliminate many problems while protecting innocent civilians and law enforcement officers. 

For instance, utilizing facial recognition in law enforcement 

would: 

• Interconnect law enforcement and intel organizations to instantly share vital information with accurate identification results; 

• Establish a national data base of those incarcerated, past and 

present, wanted fugitives, felons, and persons of interest 

among all law enforcement agencies; 

• Allow officers to quickly determine who they are encountering 

and provide notification if a suspect is wanted or a convicted 

felon; 

• A simple, cost-effective, software-based solution delivered in 

Windows-based computers with inexpensive, non- proprietary, 

off-the-shelf cameras will provide a huge cost savings; 
19 

• Demonstrate new capabilities in alias detection, fugitive apprehension, and the speed of suspect recognition; • Ensure correct identification of prisoners being released and 

reduce costs associated with administrative procedures; • Establish a complete national data base of incarcerated persons for the first time in U.S. history; no longer could wanted 

criminals escape detection and arrest due to inefficient processes. 

While fingerprints take hours and days for analysis, some advanced facial recognition in use today by U.S. law enforcement is 

as accurate as fingerprints, but results are obtained in seconds, not 

hours, in identifying criminals and perpetrators attempting to use 

false identities and aliases. 

It is also important to point out that facial recognition comes in 

two general forms, two-dimensional and three-dimensional. Only 

All-aspect 3–D Facial systems can protect the privacy of participants who agree to be enrolled, except for in law enforcement or 

Homeland Security applications. All-aspect 3–D cannot search on 

2–D facial photographs and cannot be invasive of privacy by design. All-aspect 3–D facial recognition systems remove skin color 

and facial hair and, therefore, have no profiling capability. 

Currently, the National Sheriffs’ Association, the Bureau of Prisons, and the United States Marshals Service are all in support of 

utilizing this new three-dimensional, holographic imaging technology to eliminate errors in identification; detecting false identities; and immediately identifying dangerous suspects, fugitives, or 

terrorists rather than learning who they are after they are released 

on traffic offenses or let go without suspicion because immediate 

identification is not possible. 

Accidental releases, sometimes of dangerous felons, could also be 

eliminated. This technology has been in use for over eight years in 

Georgia detention facilities with data bases of approximately five 

million inmates without a single erroneous release. 

And just last year, a dangerous murderer was released from the 

District of Columbia jail by switching a wrist band with another inmate. This cannot happen with facial recognition. 

In closing, the proper utilization of facial recognition for intelligence or law enforcement uses can protect civil liberties, save millions of dollars, and instantly identify fugitives, felons, and dangerous suspects while saving lives. 

Thank you, Mr. Chairman. I will be glad to answer any questions 

you may have. 

[The prepared statement of Mr. Amerson appears as a submission for the record.] 

Chairman FRANKEN. Thank you, Sheriff. 

Ms. Farahany. 

STATEMENT OF NITA A. FARAHANY, PROFESSOR OF LAW, 

DUKE LAW SCHOOL, AND PROFESSOR OF GENOME 

SCIENCES& POLICY, INSTITUTE FOR GENOME SCIENCES & 

POLICY, DUKE UNIVERSITY, DURHAM, NORTH CAROLINA 

Ms. FARAHANY. Thank you. Chairman Franken and distinguished 

Members of the Subcommittee, thank you for the opportunity to ex-
20 

press my views about facial recognition technology and its implications for privacy and civil liberties. 

My fellow witnesses today have canvassed the science behind facial recognition technology and the myriad of privacy concerns 

about its use. Rather than repeat what has already been said, I 

will focus my comments on why I believe that law enforcement use 

of these technologies is not, in itself, a Fourth Amendment search, 

let alone an unreasonable one. Although the Supreme Court has 

not yet addressed this issue, as Senator Franken acknowledged 

earlier, the doctrine in analogous cases supports this view. 

A novel feature of facial recognition technology is that the first 

step of the investigative process—scanning a face of interest—can 

be done from a distance and without the awareness of the individual being scanned. No physical contact, proximity, or detention 

of an individual is necessary for law enforcement to obtain a 

faceprint. 

A faceprint is a form of identifying information that is the bread 

and butter of law enforcement: information about the physical likeness and other descriptive features of a suspect, which is routine 

practice for investigators to collect. Except in extraordinary circumstances, individuals have received only minimal constitutional 

protection against law enforcement collection of their personally 

identifying information. 

The Fourth Amendment guarantees the right of the people to be 

secure in their person, houses, papers, and effects against unreasonable searches and seizures. A Fourth Amendment search only 

occurs when the Government intrudes upon a legally cognizable interest of an individual. This technology may be used in different 

ways which may require different Fourth Amendment analyses. It 

may be used from afar without a subject’s awareness or during a 

brief investigative stop based on reasonable suspicion. Under either 

approach, I believe that the facial scanning itself is neither a 

search nor an unreasonable one. 

If the police use facial recognition from afar without an individual’s awareness, then no Fourth Amendment search has occurred. 

Neither his person nor his effects has been disturbed, and he lacks 

any legal source to support a reasonable expectation of hiding his 

facial features from Government view. He has chosen to present his 

face to the world, and he must expect that the world, including the 

police, may be watching. 

Cameras and machines may now be doing the scanning, but for 

constitutional purposes, this is no different from a police officer 

scanning faces in public places. This has never been thought to be 

a Fourth Amendment search. But even if the use of this technology 

did constitute a search, it would likely be a constitutionally reasonable one, consistent with the Fourth Amendment. 

Since the Court primarily uses property rights to inform Fourth 

Amendment privacy interests, it measures the reasonableness of a 

search based on the physical intrusiveness of the search rather 

than the personal indignity that one may have endured by having 

their personal information revealed. Mere observation without any 

physical intrusion is not tantamount to a search, and certainly not 

to an unreasonable one. 
21 

The police might instead choose to use facial scanning technology 

during a brief investigative stop, which requires a slightly different 

constitutional analysis. Beginning with Terry v. Ohio, the Court 

has held that if a police officer has a reasonable suspicion that 

somebody has committed, is committing, or is about to commit a 

crime, the police may detain the individual without a warrant. A 

facial recognition scan to achieve the same is not constitutionally 

distinguishable. Such stops are Fourth Amendment searches, and 

a person is seized while they are detained. But using facial scanning during the stop is unlikely to change the Fourth Amendment 

reasonableness. The individual privacy interest that the Court recognizes during stop-and-frisk detentions is the personal security of 

that individual and the interest against interference with his free 

movement, not the secrecy of his personal identity. In other words, 

the Court has not included secrecy of personally identifying information as a relevant privacy concern to determine the reasonableness of a stop. 

The second step of the process, which is probing a data base for 

an identity match, is now a commonplace practice by law enforcement in other contexts. They regularly check local and national 

data bases to find the identity of individuals by using their license 

plates, Social Security numbers, fingerprints, or DNA, and all of 

this is nothing more than an automated version of what police have 

done for centuries: compare information acquired in the world with 

information held at police headquarters looking for a match. 

Ultimately, the privacy concern advanced in most debates regarding facial recognition technology is whether an individual has 

a right to secrecy of their personal information. The Court has 

never recognized a Fourth Amendment privacy interest in the mere 

secrecy of identifying information. This is likely because intrusions 

upon possession and privacy are the core individual interests protected by the Fourth Amendment. And so from the beginning, the 

Court has turned to property law to inform Fourth Amendment interests. 

Indeed, when the Court first encountered the modern investigative technique of wiretapping, which, like facial recognition, enables investigators to obtain evidence without physical interference, 

the Court found no search had occurred. 

Now, to be sure, the Court has subsequently extended the Fourth 

Amendment beyond property. The Court has held that the Fourth 

Amendment applies to tangible and intangible interests such as 

private conversations. But even with this expanded view of individual interests, an individual who is facially scanned in public 

cannot reasonably claim that the police have searched or seized 

something that he has sought to seclude from public view. Instead, 

he must argue that he has a reasonable expectation of privacy in 

his personal identity associated with his facial features. Under current doctrine, courts would properly reject such a claim. 

Most recently, in the United States v. Jones, the Court revisited 

this analysis. But what remains after Jones is an incomplete picture of which individual interest beyond real property interest, if 

any, the Fourth Amendment protects. The Jones majority emphasized that trespassed upon property and the Katz expectation-ofprivacy framework co-exist under Fourth Amendment jurispru-
22 

dence. But under either analysis, without trespass upon real property or upon information that a person has sought to hide, there 

is no legitimate source of law upon which a reasonable expectation 

of privacy could be founded. 

Again, I thank you for the opportunity to appear before you 

today, and I look forward to your questions. 

[The prepared statement of Ms. Farahany appears as a submission for the record.] 

Chairman FRANKEN. Thank you, Doctor. 

Mr. Sherman. 

STATEMENT OF ROB SHERMAN, MANAGER OF PRIVACY AND 

PUBLIC POLICY, FACEBOOK, WASHINGTON, D.C. 

Mr. SHERMAN. Chairman Franken, Members of the Subcommittee, my name is Robert Sherman. I am the manager of privacy and public policy at Facebook. 

Facebook is committed to building innovative tools that enhance 

people’s online experiences while giving them control over their 

personal information. We appreciate the opportunity to share our 

views on what the use of facial recognition technology means for 

our users. 

Today I will describe how we use facial recognition technology as 

a part of our photo-sharing product, the important controls that we 

offer, and how Facebook safeguards the data that we use. 

At the outset, I want to provide some background on why we 

offer photo-sharing features on Facebook. We learned early on how 

important photo sharing was to our users when we realized that 

people were frequently changing their profile photos to show 

friends recent snapshots. In response, we built tools that allowed 

people to upload and share photos, and we continue to build on 

those tools today. 

One component of our photo sharing on Facebook is tagging, 

which is the 21st century version of handwriting captions on the 

backs of photos to label important events like birthdays or reunions 

and the people who participated. Tags promote transparency and 

control on Facebook because Facebook lets a person know when she 

is tagged. This allows the person included in the photo to interact 

with the user who uploaded it or to take action if she does not like 

the photo, for example, removing the tag or requesting that the 

photo be deleted. 

Our Tag Suggestion tool uses facial recognition technology to 

automate the process of identifying and, if the user chooses, tagging her friends in the photo she uploads. Tag Suggestions work 

by identified similarities among photos in which a person has been 

tagged. We use this information to create a template that allows 

us to offer recommendations about whom a user should tag when 

she uploads a photo. The user can then accept or reject that recommendation. 

Use of our photo-sharing tools continues to grow. In fact, as you 

noted, Mr. Chairman, a few months ago we took our Tag Suggestion feature down to improve its efficiency, and we plan to restore 

it soon. 

Individual control is the hallmark of Facebook’s Tag Suggestion 

feature. It includes four important protections. 
23 

First, we are transparent about the use of the technology. Across 

our site, we describe Tag Suggestions and the controls that we 

offer. This included providing information in our data use policy, on 

our Help Center, on our Privacy Settings page, and on our 

Facebook blog. 

Secondly, Tag Suggestions only use data people have voluntarily 

provided to Facebook and derives information from that data to 

automate the process of future tagging. We do not collect any new 

information as a part of this process. 

Third, Facebook’s technology only uses a person’s friends and 

does not enable people to identify random strangers. 

Fourth, through an easy-to-use privacy setting, Facebook enables 

people to prevent the user of their images and tag suggestions. If 

a user makes that selection, Facebook will not include her name 

when suggesting tags for uploaded photos. And we will delete the 

template in which we stored the user’s facial recognition data if one 

was previously created. 

In addition to these controls, we protect facial recognition data 

from unauthorized disclosure to third parties, including to law enforcement. Two aspects of our technology significantly limit its use 

to third parties. First, our templates are encrypted, and they work 

only with our proprietary software, so they would be useless to a 

third party. Second, our software is designed to search only a limited set of potential matches, namely, an individual user’s friends, 

and is not used to identify strangers. 

Last, we share our users’ private information with law enforcement only in very limited circumstances and consistent with our 

terms of service and applicable law. A dedicated team of professionals scrutinizes each request for legal sufficiency and compliance 

with Facebook’s internal requirements. We are one of the handful 

of major Internet companies that promotes transparency in this 

process by publishing our law enforcement guidelines on our 

website. 

I hope that my testimony has helped the Members of this Subcommittee understand how Facebook uses facial recognition technology and, more importantly, the privacy and security protections 

that define our implementation. We look forward to continuing our 

discussion with Members of Congress about the important issues 

raised in today’s hearing. 

Thank you again for the opportunity to testify, and I look forward to answering any questions that you have. 

[The prepared statement of Mr. Sherman appears as a submission for the record.] 

Chairman FRANKEN. Well, thank you, Mr. Sherman. 

Ms. Lynch. 

STATEMENT OF JENNIFER LYNCH, STAFF ATTORNEY, ELECTRONIC FRONTIER FOUNDATION, SAN FRANCISCO, CALIFORNIA 

Ms. LYNCH. Mr. Chairman, thank you very much for the invitation to testify on the important topic of facial recognition today. My 

name is Jennifer Lynch, and I am an attorney with the Electronic 

Frontier Foundation in San Francisco. We are a nonprofit, and for 
24 

over 20 years, we have been focused on protecting privacy and defending civil liberties in new technology. 

Today, and in my written testimony, I would like to address the 

implications of government and private sector use of facial recognition on privacy and civil liberties and on the laws that do or do not 

apply. 

The collection of biometrics, including facial recognition, may 

seem like science fiction or something out of a movie like ‘‘Minority 

Report,’’ but it is already a well-established part of our lives in the 

United States. The FBI and the DHS have the largest biometrics 

data bases in the world, with over 100 million records each, and 

DHS alone collects 300,000 fingerprints every day. Both of these 

and other agencies in the Federal Government are working quickly 

to add extensive facial recognition capabilities to these data bases. 

The scope of Government-driven biometrics data collection is well 

matched by private sector collection. Facebook, for example, uses 

facial recognition by default to scan all images uploaded to its site, 

and its 900 million members upload 300,000 photos every day. 

Face.com, which is the company that developed Facebook’s facial 

recognition system and was recently acquired by Facebook, stated 

in March that it had indexed 31 billion face images. Other companies, from Google and Apple to smartphone app developers, also 

provide facial recognition services to their customers, and biometrics are used by private companies to track employee time, to 

prevent unauthorized access to computers or facilities or even the 

gym. And private companies, like Morpho, represented on the panel 

here today, and other companies, are building out large facial recognition systems for governments and agencies around the world. 

For example, Morpho has developed a facial recognition technology at 41 of the 50 DMVs in the United States and for the FBI. 

And companies like this often retain access to the data that is collected. 

So facial recognition is here to stay, and yet at the same time 

many Americans do not even realize that they are already in a facial recognition data base. 

Facial recognition technology, like other biometrics programs 

that collect, store, share, and combine sensitive and unique data 

poses critical threats to privacy and to civil liberties. Biometrics in 

general are immutable, readily accessible, individuating, and can 

be highly prejudicial. And facial recognition takes the risks inherent in other biometrics to a new level. Americans cannot take precautions to prevent the collection of their image. We walk around 

in public. Our image is always exposed to the public. Facial recognition allows for covert, remote, and mass capture and identification of images, and the photos that may end up in a data base include not just a person’s face but also what she is wearing, what 

she might be carrying, and who she is associated with. This creates 

threats to free expression and to freedom of association that are 

not evident in other biometrics. 

Americans should also be concerned about the extensive sharing 

of biometric data that is already occurring at the government- and 

private-sector level. Data accumulation and sharing can be good for 

identifying people, for verifying identities, and for solving crimes. 

But it can also create social stigma when people end up in criminal 
25 

data bases and their image is searched constantly. And it can perpetuate racial and ethnic profiling and inaccuracies throughout the 

system. It can also allow for Government tracking and surveillance 

on a level that has not before been possible. 

Americans cannot participate in society today without exposing 

their faces to public view. And, similarly, connecting with friends, 

family, and the broader world through social media has quickly become a daily—and many would say necessary—experience for 

Americans of all ages. Though face recognition implicates important First and Fourth Amendment values, it is unclear whether the 

Constitution would protect against the challenges it presents. 

Without legal protections in place, it could be relatively easy for 

the government or private companies to amass a data base of images on all Americans. This presents opportunities for Congress to 

develop legislation to protect Americans. The Constitution creates 

a baseline, but Congress can and has legislated significant additional privacy protections. As I discuss in more detail in my written 

testimony, Congress could use statutes like the Wiretap Act or the 

Video Privacy Protection Act as models for this legislation. 

Given that facial recognition and the accompanying privacy concerns are not going away, it is imperative that Congress and the 

rest of the United States act now to limit unnecessary biometrics 

collection, to instill proper protections on data collection, transfer, 

and search, to ensure accountability, to mandate independent oversight, to require appropriate legal process before government collection, and define clear rules for data sharing at all levels. All of 

these are necessary to preserve the democratic and constitutional 

values that are bedrock to American society. 

Thank you once again for the invitation to testify today. I look 

forward to your questions. 

[The prepared statement of Ms. Lynch appears as a submission 

for the record.] 

Chairman FRANKEN. Thank you all for your testimony. 

Just for the sake of the record, I want to clarify that Facebook 

users upload 300 million photos to the site a day, not 300,000. I 

will add a document to the record to that effect. I would not want 

to underestimate the power of Facebook. 

[The information appears as a submission for the record.] 

Chairman FRANKEN. Professor Acquisti, one of the things I think 

is so special about your work is that it really shows us how a face 

can be a real conduit between your online world and your offline 

world in a way that other biometrics are not. Can you tell us why 

facial recognition technology is so sensitive and how it compares to 

taking someone’s fingerprint and analyzing that? 

Mr. ACQUISTI. Senator, I believe facial biometrics are a more 

powerful and sensitive biometrics than fingerprints. Not only they 

are permanent, starting with childhood your face changes, but computers are learning to be able to predict these changes, and your 

face can be changed, as you mentioned earlier, only at very great 

cost. Also, this biometric can be captured remotely. In fact, we have 

a gigapixels camera, very remotely shot can be sufficient to make 

a good, effective faceprint of someone’s face. Remote capturing 

means that this is happening without the person’s consent or even 

knowledge. 
26 

Also, the technology to capture facial images and do matching is 

becoming ubiquitous. Your phone probably can do it, my phone, 

iPad, and so forth. 

Also, unlike fingerprints, which are not usually publicly available 

online, facial data is, as our experiment showed and studies by others have shown, plenty available online. 

And, finally, as you mentioned, a face is truly the conduit between your different personas, who you are on the street, in real 

life, and who you are online, who you are online may be on a dating site, and who you are on a social network. And the face, therefore, allows these different sides of your life that you wanted to 

keep, perhaps, compartmentalized to be connected. Plus there is 

also the issue of the sensitive inferences one can make starting 

from a face, which is perhaps another story, but it is related to this 

topic as well. 

Chairman FRANKEN. Thank you. 

Mr. Sherman, you have heard from almost everyone else at this 

hearing that facial recognition technology is extremely powerful 

and extremely sensitive. Why doesn’t Facebook turn its facial recognition feature off by default and give its users the choice to turn 

it on? 

Mr. SHERMAN. Well, Senator, I think you are right to say that, 

like all of the other information that we store about our users, it 

is important that we take appropriate steps to protect information. 

We take that responsibility very seriously. And in terms of implementing choice throughout our site, and we do that in a lot of 

ways, we use a number of different mechanisms to do it. 

As you point out, with regard to the tag suggestion feature specifically, it is turned on by default, and we give people the opportunity to go in and disable it if they do not want to use it. 

The reason for that in part is we think that is the appropriate 

choice because Facebook itself is an opt-in experience. People 

choose to be on Facebook because they want to share with each 

other. Beyond that, tag suggestions are only used in the context of 

an opt-in friend relationship on Facebook, which means that you 

would not be suggested to somebody as a potential tag for a photo 

unless both parties to the relationship had already decided to communicate with one another on Facebook, had already seen each 

other’s photos. So we are actually not exposing any additional information to anybody as a part of this process. 

And so given those things and the fact that we do a lot to be 

transparent and to let people know about the feature, we think 

that it is the right choice to let people who are uncomfortable with 

it decide to opt out. 

Chairman FRANKEN. I understand what you are saying. We are 

just going to have to disagree on this a little bit. I just think that 

this information is so sensitive that it is the kind of thing that 

users should have to consciously opt themselves into. I will note 

that Facebook’s competitor Google leaves their facial recognition 

feature off by default on its social network and then lets users opt 

into it. But I am worried about how Facebook handles the choices 

that it does give its users about this technology. 

Mr. Sherman, on page six of your written testimony, you write 

that, ‘‘Through an easy-to-use privacy setting, people can choose 
27 

whether we will use our facial recognition technology to suggest 

that their friends tag them in photos.’’ 

This is the screen that Facebook users get when they go to their 

privacy settings to find out about tag suggestions. Nowhere on this 

screen or on the screen that you get when you click ‘‘Learn More’’ 

do you see the words ‘‘facial recognition’’ or anything that describes 

facial recognition. Those words are elsewhere in your Help Center, 

but right now you have to go through six different screens to get 

there. I am not sure that is easy to use. 

How can users make an informed decision about facial recognition in their privacy settings if you do not actually tell them in 

their privacy settings that you are using facial recognition? 

Mr. SHERMAN. Well, the screen shot that you have displayed does 

not use the words ‘‘facial recognition.’’ I believe that the ‘‘Learn 

More’’ link at the bottom leads to the page in our Help Center. We 

have a series of frequently asked questions that we provide to 

users that explains in detail how—— 

Chairman FRANKEN. This is the page that it links to. 

[Laughter.] 

Chairman FRANKEN. And nowhere does it talk about a facial recognition page, right? 

Mr. SHERMAN. I have not done that, so I do not know that—— 

Chairman FRANKEN. You have not done that? 

Mr. SHERMAN. I have done that. I did not create the visual, so 

I do not know that, but I can tell you that—— 

Chairman FRANKEN. What haven’t you done? 

Mr. SHERMAN. I am sorry. I just have not seen the visual. I think 

the page that you are looking at is one of the pages in our Help 

Center that provides information about how tagging works on 

Facebook. The Help Center content that you are talking about, 

which I think is available from that page, does describe facial recognition, uses the words ‘‘facial recognition’’ specifically, and provides some detail about the way in which the templates that we 

use, the files that include the facial recognition data are stored. 

Chairman FRANKEN. It is my understanding, am I right, that 

that is six clicks away? 

Mr. SHERMAN. I am not sure about the number. I do not think 

that is right, but I am not sure. 

Chairman FRANKEN. OK. You are head of this at Facebook? 

Mr. SHERMAN. I am one of many people who work on privacy at 

Facebook. 

Chairman FRANKEN. What is your title? 

Mr. SHERMAN. I am the manager of privacy and public policy. 

Chairman FRANKEN. Thank you, Mr. Sherman. 

Mr. SHERMAN. Thank you. 

Chairman FRANKEN. Ms. Lynch, you are a privacy and civil liberties lawyer. It is your job to interpret the law in a way that protects privacy and civil liberties. Can you summarize for us in a few 

sentences what concrete legal protections there are with respect to 

the use of facial recognition technology by the government and by 

the private sector? 

Ms. LYNCH. Well, I think at the Federal level it is pretty clear 

that there are no specific laws that regulate facial recognition or 
28 

that regulate the collection of images to be put into a facial recognition data base, whether from the government or the private sector. 

That said, the Constitution creates a baseline. I think we have 

seen in the U.S. v. Jones case that was decided in January that 

the Supreme Court and several other courts are concerned about 

collection of information on us when we are in public. And, also, 

the FTC, of course, has some ability to regulate companies that are 

engaged in deceptive or unfair trade practices. And then there are 

two State laws, which you mentioned earlier, in Illinois and Texas, 

that would govern the collection of biometrics on citizens within 

those States. 

Chairman FRANKEN. Thank you. 

Right now, I know Senator Blumenthal has been here for a 

while. Since I am chairing this, I am going to be here. I want to 

be conscious of your time, so why don’t I turn the questioning over 

to you, Senator? 

Senator BLUMENTHAL. Thank you, Mr. Chairman. 

Mr. Sherman, let me first thank Facebook for being so cooperative in the Password Protection Act that I proposed, with the support of a number of other Members of the Judiciary Committee, 

that prohibits employers from compelling passwords and other such 

information that provides access to private personal accounts to 

being divulged in the course of employment, whether it is applications for employment or prospective employment or existing employment. 

Why does Facebook not require or not permit the kind of opt-in 

procedure that Senator Franken mentioned? 

Mr. SHERMAN. Well, we do not provide—we have implemented 

tag suggestions in a way that does not require people to opt in for 

a number of reasons, including the fact that, as I mentioned, 

Facebook is an opt-in service and the fact that we provide tag suggestions only in the context of existing friendships. 

I think we also work very hard to be transparent with people 

about how the feature works. We provide information about the 

tool on a lot of different places on the site. And we also think that 

there are benefits both in terms of social engagement and also in 

terms of privacy associated with photo tagging. And we think that 

making it easier for people to tag people on Facebook, again, people 

that they already know and already are in relationships with, promotes those benefits. It gives people the ability to know that they 

are in photos that have been posted on Facebook and to exercise 

control over them if they want to do so. 

Senator BLUMENTHAL. Does Facebook share facial recognition 

data with any third parties? 

Mr. SHERMAN. We do not. 

Senator BLUMENTHAL. Is there anything in your guidelines or 

company practices that precludes it? 

Mr. SHERMAN. As I mentioned, we publish on our website our 

law enforcement guidelines, which I think may be the circumstance 

that you are talking about, and with regard to that information, 

first, we—as far as I know, we have never received a request from 

law enforcement from the information that you are talking about. 

I think that reflects the fact that the templates that we have would 

not be useful outside of our service. They just cannot be used by 
29 

law enforcement. I think there are other technologies that law enforcement might use. And I think beyond that there is a very rigorous standard that we describe in our policies under which we 

would provide any non-public personal information to law enforcement. 

Senator BLUMENTHAL. And what about going beyond law enforcement? Is there anything in your guidelines or practices that precludes sharing with non-law enforcement? 

Mr. SHERMAN. I do not know whether we have said specifically 

with regard to facial recognition information, but we have a data 

use policy which we publish on our website which provides significant detail about the restrictions, and the general standard is that 

we do not disclose personal information to third parties without our 

users’ consent. 

Senator BLUMENTHAL. Does Facebook allow third-party apps to 

collect facial recognition data from users? 

Mr. SHERMAN. Just to make sure I understand your question, 

Senator, the facial recognition data that is in our data bases, the 

templates? 

Senator BLUMENTHAL. Correct. 

Mr. SHERMAN. No, we do not provide those to any apps. 

Senator BLUMENTHAL. And just assume that someone signs up 

for Facebook—you mentioned that it is, obviously, voluntary—and 

he or she does not want to have facial data stored, collected, used 

by Facebook. What are the options available to that person? 

Mr. SHERMAN. So if a person signs up for Facebook and does not 

want facial recognition data to be collected or used about that person, the person can go to their Privacy Center, click on Tagging, 

and then the option to turn off the tag suggestion feature is there. 

If they do that, two things will happen: one, we will not suggest 

them to any of their friends when their friends upload photos; and, 

two, if a facial recognition template was created, it will be deleted. 

In the circumstance that I think you are describing, we probably 

would not have a facial recognition template in the first instance. 

If a user wanted to allow the use of the feature but to exercise 

other kinds of control, we offer that as well. For example, the user 

can be notified when he or she is tagged, can remove the tag from 

the photo. If he or she does that, then that removes that from the 

template that we use to power our tag suggestions feature. 

And, finally, the user can choose to exercise control before any 

photo in which he or she is tagged shows up on her timeline. 

Senator BLUMENTHAL. Now that Facebook is considering allowing 

children under 13 to sign up for Facebook accounts, which obviously implicates a number of privacy concerns of a different nature 

and magnitude, does Facebook have any new policies or plans to 

develop new policies and what will those policies be regarding facial recognition technology on pictures of children who use 

Facebook? 

Mr. SHERMAN. Well, Senator, as you know, our current policy is 

that children under 13 are not allowed on Facebook, and we have 

a number of technical and procedural measures that we put in 

place to try to prevent children under 13 from gaining access to our 

service in violation of that policy. 
30 

There have been some studies that have come out recently that 

have suggested that children, despite our efforts, are gaining access 

to Facebook, and in many cases with the assistance of their parents. And so one of the things that has been suggested is that we 

provide tools for parents to manage their children’s access of 

Facebook if they do get on. 

We are in the process of thinking about those. Those are really 

important issues, and protecting children and all of our uses is a 

high priority at Facebook. And we are thinking through the right 

way to manage those questions. So we have not made any final decision about what we would do, if anything, about changing our 

under-13 policy. 

What I can tell you is we do implement the tag suggestion feature in a slightly different way for children who are over—for teenagers, excuse me, who are over 13 but under 17. In those cases, the 

tag suggestion feature is off by default, and the teenagers can turn 

it on if they want to do so, but it is not on by default. 

Senator BLUMENTHAL. Wouldn’t it make sense to simply preclude 

those images for children under 13 to be in any way collected or 

stored? 

Mr. SHERMAN. Well, I mean, I think certainly there are difficult 

questions, and the one that you raise is one of a large number of 

questions that we would have to confront if we decided to allow 

children under 13. It is something certainly that we would consider 

actively, but until we make a decision about changing our policy, 

I think it is premature to say exactly how we would implement it. 

Senator BLUMENTHAL. Well, I am going to ask that Facebook 

commit to not collecting or storing those facial recognition data for 

anyone under 13 if you decide to go ahead. I think it is a matter 

of public policy and public safety that Facebook adopt that kind of 

policy if you decide to go ahead. 

Mr. SHERMAN. OK, thank you. We absolutely appreciate the feedback, and if we go in that direction, that is something we will certainly consider. 

Senator BLUMENTHAL. Thank you. 

Thank you, Mr. Chairman. 

Chairman FRANKEN. Thank you, Senator Blumenthal. 

I just want to also correct the record that MorphoTrust has 32 

driver’s license contracts that include facial recognition, not 40. 

Professor Acquisti, a month or two ago, a company called 

Face.com released an iPhone app that allowed you to point your 

iPhone at someone and have a little box pop up above that person’s 

face on your screen that told you their name. The app was only 

supposed to work on your friends, but soon after the release of this 

app, a well-respected security researcher who has testified before 

this Subcommittee, Ashkan Soltani, revealed that the app could 

easily be hacked in a way that would appear to allow it to identify 

strangers. 

Facebook has since purchased Face.com and shut down this app. 

But were you familiar with this app and the vulnerability that it 

created or had? What did it tell you about the state of privacy 

when it comes to facial recognition technology? Is this something 

we should be thinking about? 
31 

Mr. ACQUISTI. Senator, yes, I have been following the news and 

the research about Klik, this app. I will make a few points. 

One is that this app shows that the studies we presented last 

year are not just theoretical experiments. They happen in reality. 

The reality of face mobile, real-time face recognition is coming 

much faster than what some people may have believed. 

A second point is that the vulnerability Ashkan Soltani found 

shows that there are inherent risks in this technology in that they 

cluster and aggregate very sensitive information which becomes a 

desirable target for hackers and third parties. Soltani was able, 

through the vulnerability he discovered, to get access to non-public 

photos of individuals as well as to private data of other users, 

which means that conceivably he could have used these additional 

photos for face recognition not just of his own friends but friends 

of friends and many other people in the network. 

Which leads me to the third point. Currently, the limitations in 

this app come mostly from two directions. One is computational 

cost. In experiments we did, we were working on data bases of hundreds of thousands of images; therefore, we could do a match in 

real time. If we had tried to do it against 300 million Americans 

or, in fact, 90 billion photos, it would take hours and hours and 

hours. However, this limit is transient; it is not systemic in the 

sense that cloud computing clusters are getting faster and faster. 

Therefore, we cannot guarantee that what is not possible to do 

now, extrapolating our results to nationwide to the entire population, will not be possible five years out. 

The second limitation is, like I mentioned in my testimony, there 

is a sort of a self-restraint in the providers of the services which 

can be found in statements such as, ‘‘Don’t worry. This only works 

with your friends. Only your friends will be able to tag you.’’ Well, 

this is now. There is no guarantee that a few years from now it 

will be friends of friends or some years later it will be anyone in 

the network. In fact, the history of social media and online social 

networks in general shows that there is this progressive nudging 

of users toward more and more disclosure. So this is to me one of 

the concerns we have in this area. 

Chairman FRANKEN. Well, then, I will turn to Mr. Martin. I am 

going to try to get everybody in here. We are really talking about 

how fast this technology is improving, and that is sort of what I 

was just asking Mr. Acquisti. What are we approaching? What kind 

of world are we approaching in terms of how quickly and reliably 

this technology can identify unknown individuals walking down a 

city street? I know we are not quite there yet, but tell me how fast 

this technology is improving and how far we are from that world. 

Mr. MARTIN. There is not a black-and-white answer to this. So 

certainly, today, if you have a small data base of individuals, a few 

thousand or even tens of thousands, and you had a controlled situation where somebody was walking through a metal detector but 

still they did not know the camera was on them, then you could 

reliably do identification on that small data base, say if you had 

a watchlist of criminals or terrorists or something. 

In the case where you now expand the data base to the size of 

multiple millions and you are just shooting a camera outside the 

window down the street, you cannot reliably do that for a large 
32 

data base. What you could do is, for instance, have some humans 

that look at the results, and if you only were looking for a few people, not millions of people, then you could shoot something out the 

window and probably try to find a suspect. But certainly the technology is not there to do that on a large scale with 300 million people or a billion people. And even if you have more processors and 

it is faster, I do not think you are going to be there in the next 

several years. 

Chairman FRANKEN. What about the scenario of going into—a 

guy goes into a bar, takes a picture of a woman, wants to stalk her, 

can find out where she lives? 

Mr. MARTIN. Some of the arguments here was that that is a concern that you can do something like that, and I think the only way 

it would be viable today is that you would need some additional information. Like you would have to know that she is a friend of 

somebody on Facebook and you are a friend with that person and 

you have access to see who their friends are. Then potentially you 

could look at images off of the Internet and link up that extra 

metadata that is on her profile with that picture and find out that 

information. 

But even just from the science side of it, taking a picture in the 

bar where it is dark and the person is not looking at your camera 

unless you ask them for a good picture, it is technically very hard 

even to do the face recognition matching, despite the other part 

that you need to have all this linking information to get it to work. 

So it is not easy. 

Chairman FRANKEN. Sometimes you would say, ‘‘Hey’’—— 

Mr. MARTIN. ‘‘Can I get a picture of you? ’’ Right. 

Chairman FRANKEN. A flash, and there it is. 

Mr. MARTIN. Right. So if you did that, though, then the question 

is: What is the data base that you are going to search against? 

Chairman FRANKEN. I just want to ask this with Mr. Acquisti 

and Mr. Sherman. Mr. Acquisti said that the social networks—the 

privacy policy has sort of loosened in a way. What did you mean 

by that in terms of—let us just get a little dialogue maybe between 

the two of you just on this. Has Facebook done that? Have they 

loosened their privacy policies? You are nodding, Ms. Farahany, 

so—I just go to whoever is nodding. That is my role as Chairman. 

[Laughter.] 

Chairman FRANKEN. If you want to get called on, nod. 

Ms. FARAHANY. I am happy to nod and be called on. I think 

Facebook and other social media sites are changing our expectations of privacy. So I think part of the reason why the Fourth 

Amendment analysis is useful here is that it is tied to what does 

society expect to be able to keep private. And in today’s world, we 

are moving toward much greater transparency. As I have been listening to the conversation, it does not seem like it is facial recognition itself that anybody is afraid of. It is linking it to other information that people are frightened by. And I think that is right, which 

is, there is nothing inherently frightening about having your face 

seen. We have it seen in public all the time. We do not try to hide 

it from view. It is the aggregation of data that frightens people. 

And so what is it, if anything, we should be doing about aggregation of data? Well, Congress has already taken a number of initia-
33 

tives to keep some types of personal information private, like your 

health information, financial transactions, your genetic information 

for certain types of uses through the Genetic Information Nondiscrimination Act. But we do not stop the flow of information. We 

say there are certain applications of the information which are limited or impermissible. And I think there is nothing about for me 

personally—and this may be because, you know, I am a user of 

Facebook and somebody who is comfortable with greater transparency. There is nothing frightening to me about somebody having 

a photograph taken of me or even going into every store or every 

place on the street and having a photograph taken of me. It is the 

ability to make a complete dossier about me and know a lot of 

other information. 

And so if there is something about the use and application that 

we are frightened about, I think that is an appropriate place for 

Congress to focus very targeted interest, but it may not be facial 

recognition technology it should be focusing on then. It is the act 

of data aggregation itself and who can aggregate data, for what 

purpose, and to whom they can package and sell it. 

Chairman FRANKEN. OK. Now, you are nodding, so that means 

you are going to be called on. 

Mr. ACQUISTI. I was nodding, Senator. In my written testimony, 

I made a short list of examples where Facebook indeed changed 

something—settings, defaults—to unilaterally create more disclosure or more sharing. The examples include Facebook News in 

2006, Tagging in 2009; changes in privacy settings in early 2010; 

changing of the cache time limits in 2010—that refers to how long 

third-party developers can keep your data; the introduction of 

Facebook Places in 2010, which allows others to tag you when you 

go in a certain location; the switch to the ‘‘Timeline’’ in early 2012, 

initially voluntary, then compulsory; more recent the switching of 

users to using Facebook emails rather than other parties’ emails. 

So there is an extensive list of examples showing this trend. 

Chairman FRANKEN. How do you respond to that? 

Mr. SHERMAN. Well, I think the examples that Professor Acquisti 

is offering are examples of ways in which we have changed our 

service, and I think you would want Facebook to innovate, you 

would want Facebook to continue to offer new and better products 

to our users, and that is something that we try to do every day. 

Anytime we make any change to our service, including the changes 

that Professor Acquisti referred to, we have a robust privacy process that includes professionals from all across our organization who 

review those changes to make sure that they are consistent with 

the commitments that we have made to our users and that they 

will help us maintain the trust of our users, because, after all, if 

people do not trust us, then they will not use our service, and that 

is something we very much want people to do. And I think if we 

did make a change of any sort—and I think in the instances that 

he has described—we let our users know about that and give them 

the ability to make choices about them. 

Chairman FRANKEN. OK. And did it involve information retrospectively? In other words, did it involve loosening the privacy on 

information they had already put in there that they did not know 

would—I am saying this out of ignorance here. I am just asking. 
34 

Mr. SHERMAN. There may be instances where we would change 

a default, so for new people who come onto the site, things might 

work in a slightly different way, and we would be very clear with 

them about how that works. But we have committed to the FTC 

that when we have information that we already have that is covered by a privacy setting, we will not disclose it in a way that materially exceeds the privacy setting after that has been done. 

Chairman FRANKEN. OK. Thank you. 

I want to go to Ms. Lynch in kind of a final question, but I have 

not talked to the sheriff yet, and I want to thank you for being with 

us. I know that right now Calhoun County is about to roll out a 

facial recognition system for the field. If your deputy pulls someone 

over and that person refuses to identify him- or herself, this system 

will allow you to see if they are a wanted criminal or someone with 

an arrest record. 

Now, I know that the data base of photos you are using for this 

field system is still going to be a data base of mug shots from arrests. 

Mr. AMERSON. Right. 

Chairman FRANKEN. It is not going to be the data base from the 

Department of Motor Vehicles. Can you tell us why you decided to 

stick with the criminal data base and not use a bigger data base 

like the DMV’s? 

Mr. AMERSON. I think the key is for us to focus on the people 

that are of interest to us. Ordinary, honest people going about their 

daily business are not of interest to us. Our interests are people 

who are committing crimes, people who are wanted for questioning 

about crimes. It would have to be a very certain degree of information allowed—available for us to do that. But, again, the key to us 

is locating wanted criminals so that we can locate and arrest them 

and take them off the street. 

Chairman FRANKEN. Thank you. 

Ms. Lynch, if Congress were to pass a law governing law enforcement use of facial recognition technology, what are the two or three 

protections you think need to be included? 

Ms. LYNCH. Well, I think first we have to look at how law enforcement is getting the data. So law enforcement is currently getting data in general in two different ways. One is directly, so let 

us say they are bringing a suspected criminal into a police department and fingerprint them, or they are collecting an image on the 

street. And then the second way that law enforcement gets data is 

from a private company or a third party—bank records or data 

from Facebook, submitting a warrant to Facebook. And I think in 

both of those situations, we would like to see a warrant based on 

probable cause to get access to the data. 

Facial recognition data and faceprints and photographs are pretty sensitive data, and everyone though we do share our faces with 

the public and we share our images with third parties, there has 

been a lot of significant research done to show that people still 

have an expectation of privacy in this information. Even though we 

are sharing it with our friends and our family and our networks, 

we are not necessarily expecting that that data should be shared 

with the Government. And I think based on that, we do have a rea-
35 

sonable expectation of privacy in the data that would warrant a 

warrant standard. So that is the first thing. 

I think the second thing that I would like to see is that there 

would be some data minimization requirements put in place. This 

could be minimization of how much data the gvernment collects, so 

instead of getting 10 pictures of a person or crowd photos of a person—that include a person, it is limited to mug shots like the sheriff said. So that is one way of minimizing the data collection. Another is if the government is collecting crowd photo data for an individual investigation, that that crowd photo be deleted once the 

investigation is concluded, or that other faces in the crowd be 

scrubbed so that they are not identifiable. So that is the second. 

And then I think the third thing that I would like to see is that 

data that is gathered for one purpose is not combined with data 

gathered for another. So, for example, right now the FBI has two 

separate parts to its fingerprint data base. It has the records collected for civil purposes, like employment. If you are Federal employee, if you are a lawyer in California, if you are applying for a 

job to work with children, your fingerprints are collected and put 

in the FBI’s civil fingerprint data base. And that is kept separate 

from the criminal data base where all of the fingerprints of anybody arrested in the United States go. And, currently, although 

those are kept separate, the FBI is planning to incorporate a master name system that would allow searching of both data bases at 

the same time, and I think this raises a lot of implications for privacy and civil liberties that we have not discussed. And even 

though we are talking about fingerprints here, when the FBI includes facial recognition into its data base—and it is supposed to 

do that by 2014—they will be searching facial recognition-ready 

photographs as well. 

Chairman FRANKEN. Thank you. 

I have a note here that Professor Farahany has a plane to catch. 

Is that correct? 

Ms. FARAHANY. My flight is at seven. 

Chairman FRANKEN. I am sorry? 

Ms. FARAHANY. I said my flight is at seven. 

Chairman FRANKEN. Let us see. It is rush hour. Is it National 

or Dulles? Dulles. 

[Laughter.] 

Chairman FRANKEN. Are you checking any bags? 

[Laughter.] 

Chairman FRANKEN. OK. Well, I will ask my last question, and 

then you can get out of here. 

Mr. Sherman, once you generate a faceprint for somebody, even 

though you might not do it now, you can use it down the road in 

countless ways. You could. I would like for you to tell us on the 

record how Facebook will and will not use its faceprints going forward. We did have the matter of some changes in policy. For example, can you assure us that Facebook will share or sell users’ 

faceprints along with the software needed to use them to third parties—will not do that? Can you assure us that they will not do 

that? 

Mr. SHERMAN. Well, Senator Franken, I think it is difficult to 

know in the future what Facebook will look like five or 10 years 
36 

down the road, and so it is hard to respond to that hypothetical. 

What I can tell you is that we have a robust process, as I have described, to vet any changes that we would make along those lines. 

We also have relationships with the Federal Trade Commission, 

the Irish Data Protection Commissioner which regulates our Irish 

affiliate, and consumer groups like the Electronic Frontier Foundation. We talk with them regularly about changes that we are making or are planning to make. I think if we would make a change 

that would be concerning, those are certainly groups that would express concern, and we obviously would be transparent with any 

change with our users. 

Chairman FRANKEN. Well, I think that is a fair answer. Your 

company has every right not to lock itself into future business decisions and to keep your options open. But perhaps that is why Congress should be looking at this and considering whether we need 

to put in place protections so that users’ faceprints are never 

shared or sold without their explicit permission, for example. 

Well, I want to thank you all for joining us. Ms. Farahany, you— 

you are all permitted to bolt. 

[Laughter.] 

Chairman FRANKEN. But I want to thank you and, again, your 

complete written testimonies will be made part of the record. 

In closing, I want to thank Ranking Member Coburn, and I want 

to thank each of the witnesses who appeared with us today. I will 

add a statement from EPIC to the record. 

[The statement appears as a submission for the record.] 

Chairman FRANKEN. We are adjourned. Thank you. Thank you 

all. 

[Whereupon, at 4:35 p.m., the Subcommittee was adjourned.] 

[Questions and answers and submissions for the record follow.] 
(37) 

A P P E N D I X 

ADDITIONAL MATERIAL SUBMITTED FOR THE RECORD

WITNESS LIST
38 
39 

PREPARED STATEMENTS OF WITNESSES
40 
41 
42 
43 
44 
45 
46 
47 
48 
49 
50 
51 
52 
53 
54 
55 
56 
57 
58 
59 
60 
61 
62 
63 
64 
65 
66 
67 
68 
69 
70 
71 
72 
73 
74 
75 
76 
77 
78 
79 
80 
81 
82 
83 
84 
85 
86 
87 
88 
89 
90 
91 
92 
93 
94 
95 
96 
97 
98 
99 
100 
101 
102 
103 
104 
105 
106 
107 
108 
109 
110 
111 
112 
113 
114 
115 
116 
117 
118 
119 
120 
121 
122 
123 

SUBCOMMITTEE CHAIRMAN PREPARED STATEMENT
124 
125 
126 
127 

QUESTIONS FOR WITNESSES FROM SENATOR AL FRANKEN
128 
129 
130 
131 
132 
133 

QUESTIONS AND ANSWERS
134 
135 
136 
137 
138 
139 
140 
141 
142 
143 
144 
145 
146 
147 
148 
149 

MISCELLANEOUS SUBMISSIONS FOR THE RECORD
150 
151 
152 
153 
154 
155 
156 
157 
158 
159 
160 
161 
162 
163 
164 
165 
166 
167 
168 
169 
170 
171 
172 
173 
174 
175 
176 
177 
178 
179 
180 
181 
182 
183 
184 
185 
186 
187 
188 
189 
190 
191 
192 
193 
194 
195 
196 
197 
198 
199 
200 
201 
202 
203 
204 
205 
206 
207 
208 
209 
210 
211 
212 
213 
214 
215 
216 
217 
218 
219 
220 
221 
222 
223 
224 
225 
226 
227 
228 
229 
230 
231 
232 
233 
234 
235 
236 
237 
238 
239 
240 
241 
242 
243 
244 
245 
246 
247 
248 
249 
250 
251 
252 
253 
254 
255 
256 
257 
258 
259 
260 
261 
262 
263 
264 
265 
266 
267 
268 
269 
270 
271 
272 
273 

SUBMISSIONS FOR THE RECORD NOT PRINTED DUE TO VOLUMINOUS NATURE, PREVIOUSLY PRINTED BY AN AGENCY OF THE FEDERAL GOVERNMENT, OR OTHER CRITERIA DETERMINED BY THE COMMITTEE, LIST OF MATERIAL AND LINKS CAN BE

FOUND BELOW: 

EPIC Comments—January 31, 2012.: 

http://www.ftc.gov/os/comments/ 

facialrecognitiontechnology/00083-0982624.pdf 

National Institute of Justice (NIJ), William A. Ford, Director, 

State of Research, Development and Evaluation.: 

https://www.eff.org/sites/default/files/ford-State-of-Research-Development-and-Evaluation-at-NIJ.pdf#page=17 

Farahany, Nita A., Testimony Attachment—Pennsylvania Law 

Review: 

http://www.pennumbra.com/issues/pdfs/160-5/ 

Farahany.pdf 
274 

Æ