Facial Recognition Can Reduce Racial Profiling and False Arrests
[Editor's Note: This essay is in response to our current Big Question, which we posed to experts with different perspectives: "Do you think the use of facial recognition technology by the police or government should be banned? If so, why? If not, what limits, if any, should be placed on its use?"]
Opposing facial recognition technology has become an article of faith for civil libertarians. Many who supported the bans in cities like San Francisco and Oakland have declared the technology to be inherently racist and abusive.
The greatest danger would be to categorically oppose this technology and pretend that it will simply go away.
I have spent my career as a criminal defense attorney and a civil libertarian -- and I do not fear it. Indeed, I see it as positive so long as it is appropriately regulated and controlled.
We are living in the beginning of a biometric age, where technology uses our physical or biological characteristics for a variety of products and services. It holds great promises as well as great risks. The greatest danger, however, would be to categorically oppose this technology and pretend that it will simply go away.
This is an age driven as much by consumer as it is government demand. Living in denial may be emotionally appealing, but it will only hasten the creation of post-privacy world. If we do not address this emerging technology, movements in public will increasingly result in instant recognition and even tracking. It is the type of fish-bowl society that strips away any expectation of privacy in our interactions and associations.
The biometrics field is expanding exponentially, largely due to the popularity of consumer products using facial recognition technology (FRT) -- from the iPhone program to shopping ones that recognize customers.
But the privacy community is losing this battle because it is using the privacy rationales and doctrines forged in the earlier electronic surveillance periods. Just as generals are often accused of planning to fight the last war, civil libertarians can sometimes cling to past models despite their decreasing relevance in the current world.
I see FRT as having positive implications that are worth pursuing. When properly used, biometrics can actually enhance privacy interests and even reduce racial profiling by reducing false arrests and the warrantless "patdowns" allowed by the Supreme Court. Bans not only deny police a technology widely used by businesses, but return police to the highly flawed default of "eye balling" suspects -- a system with a considerably higher error rate than top FRT programs.
Officers are often wrong and stop a great number of suspects in the hopes of finding a wanted felon.
A study in Australia showed that passport officers who had taken photographs of subjects in ideal conditions nonetheless experienced high error rates when identifying them shortly afterward, including 14 percent false acceptance rates. Currently, officers stop suspects based on their memory from seeing a photograph days or weeks earlier. They are often wrong and stop a great number of suspects in the hopes of finding a wanted felon. The best FRT programs achieve an astonishing accuracy rate, though real-world implementation has challenges that must be addressed.
One legitimate concern raised in early studies showed higher error rates in recognitions for certain groups, particularly African American women. An MIT study finding that error rate prompted major improvements in the algorithms as well as training changes to greatly reduce the frequency of errors. The issue remains a concern, but there is nothing inherently racist in algorithms. These are a set of computer instructions that isolate and process with the parameters and conditions set by creators.
To be sure, there is room for improvement in some algorithms. Tests performed by the American Civil Liberties Union (ACLU) reportedly showed only an 80 percent accuracy rate in comparing mug shots to pictures of members of Congress when using Amazon's "Rekognition" system. It recently showed the same 80 percent rate in doing the same comparison to members of the California legislators.
However, different algorithms are available with differing levels of performance. Moreover, these products can be set with a lower discrimination level. The fact is that the top algorithms tested by the National Institute of Standards and Technology showed that their accuracy rate is greater than 99 percent.
The greatest threat of biometric technologies is to democratic values.
Assuming a top-performing algorithm is used, the result could be highly beneficial for civil liberties as opposed to the alternative of "eye balling" suspects. Consider the Boston Bombing where police declared a "containment zone" and forced families into the street with their hands in the air.
The suspect, Dzhokhar Tsarnaev, moved around Boston and was ultimately found outside the "containment zone" once authorities abandoned near martial law. He was caught on some surveillance systems but not identified. FRT can help law enforcement avoid time-consuming area searches and the questionable practice of forcing people out of their homes to physically examine them.
If we are to avoid a post-privacy world, we will have to redefine what we are trying to protect and reconceive how we hope to protect it. In my view, the greatest threat of biometric technologies is to democratic values. Authoritarian nations like China have made huge investments into FRT precisely because they know that the threat of recognition in public deters citizens from associating or interacting with protesters or dissidents. Recognition changes conduct. That chilling effect is what we have the worry about the most.
Conventional privacy doctrines do not offer much protection. The very concept of "public privacy" is treated as something of an oxymoron by courts. Public acts and associations are treated as lacking any reasonable expectation of privacy. In the same vein, the right to anonymity is not a strong avenue for protection. We are not living in an anonymous world anymore.
Consumers want products like FaceFind, which link their images with others across social media. They like "frictionless" transactions and authentications using faceprints. Despite the hyperbole in places like San Francisco, civil libertarians will not succeed in getting that cat to walk backwards.
The basis for biometric privacy protection should not be focused on anonymity, but rather obscurity. You will be increasingly subject to transparency-forcing technology, but we can legislatively mandate ways of obscuring that information. That is the objective of the Biometric Privacy Act that I have proposed in recent research. However, no such comprehensive legislation has passed through Congress.
The ability to spot fraudulent entries at airports or recognizing a felon in flight has obvious benefits for all citizens.
We also need to recognize that FRT has many beneficial uses. Biometric guns can reduce accidents and criminals' conduct. New authentications using FRT and other biometric programs could reduce identity theft.
And, yes, FRT could help protect against unnecessary police stops or false arrests. Finally, and not insignificantly, this technology could stop serious crimes, from terrorist attacks to the capturing of dangerous felons. The ability to spot fraudulent entries at airports or recognizing a felon in flight has obvious benefits for all citizens.
We can live and thrive in a biometric era. However, we will need to bring together civil libertarians with business and government experts if we are going to control this technology rather than have it control us.
[Editor's Note: Read the opposite perspective here.]
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.