Who Qualifies as an “Expert” And How Can We Decide Who Is Trustworthy?
Discerning a real expert from a charlatan is crucial during the COVID-19 pandemic and beyond.
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Expertise is a slippery concept. Who has it, who claims it, and who attributes or yields it to whom is a culturally specific, sociological process. During the COVID-19 pandemic, we have witnessed a remarkable emergence of legitimate and not-so-legitimate scientists publicly claiming or being attributed to have academic expertise in precisely my field: infectious disease epidemiology. From any vantage point, it is clear that charlatans abound out there, garnering TV coverage and hundreds of thousands of Twitter followers based on loud opinions despite flimsy credentials. What is more interesting as an insider is the gradient of expertise beyond these obvious fakers.
A person's expertise is not a fixed attribute; it is a hierarchical trait defined relative to others. Despite my protestations, I am the go-to expert on every aspect of the pandemic to my family. To a reporter, I might do my best to answer a question about the immune response to SARS-CoV-2, noting that I'm not an immunologist. Among other academic scientists, my expertise is more well-defined as a subfield of epidemiology, and within that as a particular area within infectious disease epidemiology. There's a fractal quality to it; as you zoom in on a particular subject, a differentiation of expertise emerges among scientists who, from farther out, appear to be interchangeable.
We all have our scientific domain and are less knowledgeable outside it, of course, and we are often asked to comment on a broad range of topics. But many scientists without a track record in the field have become favorites among university administrators, senior faculty in unrelated fields, policymakers, and science journalists, using institutional prestige or social connections to promote themselves. This phenomenon leads to a distorted representation of science—and of academic scientists—in the public realm.
Trustworthy experts will direct you to others in their field who know more about particular topics, and will tend to be honest about what is and what isn't "in their lane."
Predictably, white male voices have been disproportionately amplified, and men are certainly over-represented in the category of those who use their connections to inappropriately claim expertise. Generally speaking, we are missing women, racial minorities, and global perspectives. This is not only important because it misrepresents who scientists are and reinforces outdated stereotypes that place white men in the Global North at the top of a credibility hierarchy. It also matters because it can promote bad science, and it passes over scientists who can lend nuance to the scientific discourse and give global perspectives on this quintessentially global crisis.
Also at work, in my opinion, are two biases within academia: the conflation of institutional prestige with individual expertise, and the bizarre hierarchy among scientists that attributes greater credibility to those in quantitative fields like physics. Regardless of mathematical expertise or institutional affiliation, lack of experience working with epidemiological data can lead to over-confidence in the deceptively simple mathematical models that we use to understand epidemics, as well as the inappropriate use of uncertain data to inform them. Prominent and vocal scientists from different quantitative fields have misapplied the methods of infectious disease epidemiology during the COVID-19 pandemic so far, creating enormous confusion among policymakers and the public. Early forecasts that predicted the epidemic would be over by now, for example, led to a sense that epidemiological models were all unreliable.
Meanwhile, legitimate scientific uncertainties and differences of opinion, as well as fundamentally different epidemic dynamics arising in diverse global contexts and in different demographic groups, appear in the press as an indistinguishable part of this general chaos. This leads many people to question whether the field has anything worthwhile to contribute, and muddies the facts about COVID-19 policies for reducing transmission that most experts agree on, like wearing masks and avoiding large indoor gatherings.
So how do we distinguish an expert from a charlatan? I believe a willingness to say "I don't know" and to openly describe uncertainties, nuances, and limitations of science are all good signs. Thoughtful engagement with questions and new ideas is also an indication of expertise, as opposed to arrogant bluster or a bullish insistence on a particular policy strategy regardless of context (which is almost always an attempt to hide a lack of depth of understanding). Trustworthy experts will direct you to others in their field who know more about particular topics, and will tend to be honest about what is and what isn't "in their lane." For example, some expertise is quite specific to a given subfield: epidemiologists who study non-infectious conditions or nutrition, for example, use different methods from those of infectious disease experts, because they generally don't need to account for the exponential growth that is inherent to a contagion process.
Academic scientists have a specific, technical contribution to make in containing the COVID-19 pandemic and in communicating research findings as they emerge. But the liminal space between scientists and the public is subject to the same undercurrents of sexism, racism, and opportunism that society and the academy have always suffered from. Although none of the proxies for expertise described above are fool-proof, they are at least indicative of integrity and humility—two traits the world is in dire need of at this moment in history.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
Facial Recognition Can Reduce Racial Profiling and False Arrests
The use of face recognition technology is expanding exponentially right now.
[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.]
The Case for an Outright Ban on Facial Recognition Technology
Some experts worry that facial recognition technology is a dangerous enough threat to our basic rights that it should be entirely banned from police and government use.
[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?"]
In a surprise appearance at the tail end of Amazon's much-hyped annual product event last month, CEO Jeff Bezos casually told reporters that his company is writing its own facial recognition legislation.
The use of computer algorithms to analyze massive databases of footage and photographs could render human privacy extinct.
It seems that when you're the wealthiest human alive, there's nothing strange about your company––the largest in the world profiting from the spread of face surveillance technology––writing the rules that govern it.
But if lawmakers and advocates fall into Silicon Valley's trap of "regulating" facial recognition and other forms of invasive biometric surveillance, that's exactly what will happen.
Industry-friendly regulations won't fix the dangers inherent in widespread use of face scanning software, whether it's deployed by governments or for commercial purposes. The use of this technology in public places and for surveillance purposes should be banned outright, and its use by private companies and individuals should be severely restricted. As artificial intelligence expert Luke Stark wrote, it's dangerous enough that it should be outlawed for "almost all practical purposes."
Like biological or nuclear weapons, facial recognition poses such a profound threat to the future of humanity and our basic rights that any potential benefits are far outweighed by the inevitable harms.
We live in cities and towns with an exponentially growing number of always-on cameras, installed in everything from cars to children's toys to Amazon's police-friendly doorbells. The use of computer algorithms to analyze massive databases of footage and photographs could render human privacy extinct. It's a world where nearly everything we do, everywhere we go, everyone we associate with, and everything we buy — or look at and even think of buying — is recorded and can be tracked and analyzed at a mass scale for unimaginably awful purposes.
Biometric tracking enables the automated and pervasive monitoring of an entire population. There's ample evidence that this type of dragnet mass data collection and analysis is not useful for public safety, but it's perfect for oppression and social control.
Law enforcement defenders of facial recognition often state that the technology simply lets them do what they would be doing anyway: compare footage or photos against mug shots, drivers licenses, or other databases, but faster. And they're not wrong. But the speed and automation enabled by artificial intelligence-powered surveillance fundamentally changes the impact of that surveillance on our society. Being able to do something exponentially faster, and using significantly less human and financial resources, alters the nature of that thing. The Fourth Amendment becomes meaningless in a world where private companies record everything we do and provide governments with easy tools to request and analyze footage from a growing, privately owned, panopticon.
Tech giants like Microsoft and Amazon insist that facial recognition will be a lucrative boon for humanity, as long as there are proper safeguards in place. This disingenuous call for regulation is straight out of the same lobbying playbook that telecom companies have used to attack net neutrality and Silicon Valley has used to scuttle meaningful data privacy legislation. Companies are calling for regulation because they want their corporate lawyers and lobbyists to help write the rules of the road, to ensure those rules are friendly to their business models. They're trying to skip the debate about what role, if any, technology this uniquely dangerous should play in a free and open society. They want to rush ahead to the discussion about how we roll it out.
We need spaces that are free from government and societal intrusion in order to advance as a civilization.
Facial recognition is spreading very quickly. But backlash is growing too. Several cities have already banned government entities, including police and schools, from using biometric surveillance. Others have local ordinances in the works, and there's state legislation brewing in Michigan, Massachusetts, Utah, and California. Meanwhile, there is growing bipartisan agreement in U.S. Congress to rein in government use of facial recognition. We've also seen significant backlash to facial recognition growing in the U.K., within the European Parliament, and in Sweden, which recently banned its use in schools following a fine under the General Data Protection Regulation (GDPR).
At least two frontrunners in the 2020 presidential campaign have backed a ban on law enforcement use of facial recognition. Many of the largest music festivals in the world responded to Fight for the Future's campaign and committed to not use facial recognition technology on music fans.
There has been widespread reporting on the fact that existing facial recognition algorithms exhibit systemic racial and gender bias, and are more likely to misidentify people with darker skin, or who are not perceived by a computer to be a white man. Critics are right to highlight this algorithmic bias. Facial recognition is being used by law enforcement in cities like Detroit right now, and the racial bias baked into that software is doing harm. It's exacerbating existing forms of racial profiling and discrimination in everything from public housing to the criminal justice system.
But the companies that make facial recognition assure us this bias is a bug, not a feature, and that they can fix it. And they might be right. Face scanning algorithms for many purposes will improve over time. But facial recognition becoming more accurate doesn't make it less of a threat to human rights. This technology is dangerous when it's broken, but at a mass scale, it's even more dangerous when it works. And it will still disproportionately harm our society's most vulnerable members.
Persistent monitoring and policing of our behavior breeds conformity, benefits tyrants, and enriches elites.
We need spaces that are free from government and societal intrusion in order to advance as a civilization. If technology makes it so that laws can be enforced 100 percent of the time, there is no room to test whether those laws are just. If the U.S. government had ubiquitous facial recognition surveillance 50 years ago when homosexuality was still criminalized, would the LGBTQ rights movement ever have formed? In a world where private spaces don't exist, would people have felt safe enough to leave the closet and gather, build community, and form a movement? Freedom from surveillance is necessary for deviation from social norms as well as to dissent from authority, without which societal progress halts.
Persistent monitoring and policing of our behavior breeds conformity, benefits tyrants, and enriches elites. Drawing a line in the sand around tech-enhanced surveillance is the fundamental fight of this generation. Lining up to get our faces scanned to participate in society doesn't just threaten our privacy, it threatens our humanity, and our ability to be ourselves.
[Editor's Note: Read the opposite perspective here.]