Don’t fear AI, fear power-hungry humans
Story by Big Think
We live in strange times, when the technology we depend on the most is also that which we fear the most. We celebrate cutting-edge achievements even as we recoil in fear at how they could be used to hurt us. From genetic engineering and AI to nuclear technology and nanobots, the list of awe-inspiring, fast-developing technologies is long.
However, this fear of the machine is not as new as it may seem. Technology has a longstanding alliance with power and the state. The dark side of human history can be told as a series of wars whose victors are often those with the most advanced technology. (There are exceptions, of course.) Science, and its technological offspring, follows the money.
This fear of the machine seems to be misplaced. The machine has no intent: only its maker does. The fear of the machine is, in essence, the fear we have of each other — of what we are capable of doing to one another.
How AI changes things
Sure, you would reply, but AI changes everything. With artificial intelligence, the machine itself will develop some sort of autonomy, however ill-defined. It will have a will of its own. And this will, if it reflects anything that seems human, will not be benevolent. With AI, the claim goes, the machine will somehow know what it must do to get rid of us. It will threaten us as a species.
Well, this fear is also not new. Mary Shelley wrote Frankenstein in 1818 to warn us of what science could do if it served the wrong calling. In the case of her novel, Dr. Frankenstein’s call was to win the battle against death — to reverse the course of nature. Granted, any cure of an illness interferes with the normal workings of nature, yet we are justly proud of having developed cures for our ailments, prolonging life and increasing its quality. Science can achieve nothing more noble. What messes things up is when the pursuit of good is confused with that of power. In this distorted scale, the more powerful the better. The ultimate goal is to be as powerful as gods — masters of time, of life and death.
Should countries create a World Mind Organization that controls the technologies that develop AI?
Back to AI, there is no doubt the technology will help us tremendously. We will have better medical diagnostics, better traffic control, better bridge designs, and better pedagogical animations to teach in the classroom and virtually. But we will also have better winnings in the stock market, better war strategies, and better soldiers and remote ways of killing. This grants real power to those who control the best technologies. It increases the take of the winners of wars — those fought with weapons, and those fought with money.
A story as old as civilization
The question is how to move forward. This is where things get interesting and complicated. We hear over and over again that there is an urgent need for safeguards, for controls and legislation to deal with the AI revolution. Great. But if these machines are essentially functioning in a semi-black box of self-teaching neural nets, how exactly are we going to make safeguards that are sure to remain effective? How are we to ensure that the AI, with its unlimited ability to gather data, will not come up with new ways to bypass our safeguards, the same way that people break into safes?
The second question is that of global control. As I wrote before, overseeing new technology is complex. Should countries create a World Mind Organization that controls the technologies that develop AI? If so, how do we organize this planet-wide governing board? Who should be a part of its governing structure? What mechanisms will ensure that governments and private companies do not secretly break the rules, especially when to do so would put the most advanced weapons in the hands of the rule breakers? They will need those, after all, if other actors break the rules as well.
As before, the countries with the best scientists and engineers will have a great advantage. A new international détente will emerge in the molds of the nuclear détente of the Cold War. Again, we will fear destructive technology falling into the wrong hands. This can happen easily. AI machines will not need to be built at an industrial scale, as nuclear capabilities were, and AI-based terrorism will be a force to reckon with.
So here we are, afraid of our own technology all over again.
What is missing from this picture? It continues to illustrate the same destructive pattern of greed and power that has defined so much of our civilization. The failure it shows is moral, and only we can change it. We define civilization by the accumulation of wealth, and this worldview is killing us. The project of civilization we invented has become self-cannibalizing. As long as we do not see this, and we keep on following the same route we have trodden for the past 10,000 years, it will be very hard to legislate the technology to come and to ensure such legislation is followed. Unless, of course, AI helps us become better humans, perhaps by teaching us how stupid we have been for so long. This sounds far-fetched, given who this AI will be serving. But one can always hope.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
[Editor's Note: This is the fifth episode in our Moonshot series, which explores cutting-edge scientific developments that stand to fundamentally transform our world.]
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
With the pandemic at the forefront of everyone's minds, many people have wondered if food could be a source of coronavirus transmission. Luckily, that "seems unlikely," according to the CDC, but foodborne illnesses do still sicken a whopping 48 million people per year.
Whole genome sequencing is like "going from an eight-bit image—maybe like what you would see in Minecraft—to a high definition image."
In normal times, when there isn't a historic global health crisis infecting millions and affecting the lives of billions, foodborne outbreaks are real and frightening, potentially deadly, and can cause widespread fear of particular foods. Think of Romaine lettuce spreading E. coli last year— an outbreak that infected more than 500 people and killed eight—or peanut butter spreading salmonella in 2008, which infected 167 people.
The technologies available to detect and prevent the next foodborne disease outbreak have improved greatly over the past 30-plus years, particularly during the past decade, and better, more nimble technologies are being developed, according to experts in government, academia, and private industry. The key to advancing detection of harmful foodborne pathogens, they say, is increasing speed and portability of detection, and the precision of that detection.
Getting to Rapid Results
Researchers at Purdue University have recently developed a lateral flow assay that, with the help of a laser, can detect toxins and pathogenic E. coli. Lateral flow assays are cheap and easy to use; a good example is a home pregnancy test. You place a liquid or liquefied sample on a piece of paper designed to detect a single substance and soon after you get the results in the form of a colored line: yes or no.
"They're a great portable tool for us for food contaminant detection," says Carmen Gondhalekar, a fifth-year biomedical engineering graduate student at Purdue. "But one of the areas where paper-based lateral flow assays could use improvement is in multiplexing capability and their sensitivity."
J. Paul Robinson, a professor in Purdue's Colleges of Veterinary Medicine and Engineering, and Gondhalekar's advisor, agrees. "One of the fundamental problems that we have in detection is that it is hard to identify pathogens in complex samples," he says.
When it comes to foodborne disease outbreaks, you don't always know what substance you're looking for, so an assay made to detect only a single substance isn't always effective. The goal of the project at Purdue is to make assays that can detect multiple substances at once.
These assays would be more complex than a pregnancy test. As detailed in Gondhalekar's recent paper, a laser pulse helps create a spectral signal from the sample on the assay paper, and the spectral signal is then used to determine if any unique wavelengths associated with one of several toxins or pathogens are present in the sample. Though the handheld technology has yet to be built, the idea is that the results would be given on the spot. So someone in the field trying to track the source of a Salmonella infection could, for instance, put a suspected lettuce sample on the assay and see if it has the pathogen on it.
"What our technology is designed to do is to give you a rapid assessment of the sample," says Robinson. "The goal here is speed."
Seeing the Pathogen in "High-Def"
"One in six Americans will get a foodborne illness every year," according to Dr. Heather Carleton, a microbiologist at the Centers for Disease Control and Prevention's Enteric Diseases Laboratory Branch. But not every foodborne outbreak makes the news. In 2017 alone, the CDC monitored between 18 and 37 foodborne poison clusters per week and investigated 200 multi-state clusters. Hardboiled eggs, ground beef, chopped salad kits, raw oysters, frozen tuna, and pre-cut melon are just a taste of the foods that were investigated last year for different strains of listeria, salmonella, and E. coli.
At the heart of the CDC investigations is PulseNet, a national network of laboratories that uses DNA fingerprinting to detect outbreaks at local and regional levels. This is how it works: When a patient gets sick—with symptoms like vomiting and fever, for instance—they will go to a hospital or clinic for treatment. Since we're talking about foodborne illnesses, a clinician will likely take a stool sample from the patient and send it off to a laboratory to see if there is a foodborne pathogen, like salmonella, E. Coli, or another one. If it does contain a potentially harmful pathogen, then a bacterial isolate of that identified sample is sent to a regional public health lab so that whole genome sequencing can be performed.
Whole genome sequencing can differentiate "virtually all" strains of foodborne pathogens, no matter the species, according to the FDA.
Whole genome sequencing is a method for reading the entire genome of a bacterial isolate (or from any organism, for that matter). Instead of working with a couple dozen data points, now you're working with millions of base pairs. Carleton likes to describe it as "going from an eight-bit image—maybe like what you would see in Minecraft—to a high definition image," she says. "It's really an evolution of how we detect foodborne illnesses and identify outbreaks."
If the bacterial isolate matches another in the CDC's database, this means there could be a potential outbreak and an investigation may be started, with the goal of tracking the pathogen to its source.
Whole genome sequencing has been a relatively recent shift in foodborne disease detection. For more than 20 years, the standard technique for analyzing pathogens in foodborne disease outbreaks was pulsed-field gel electrophoresis. This method creates a DNA fingerprint for each sample in the form of a pattern of about 15-30 "bands," with each band representing a piece of DNA. Researchers like Carleton can use this fingerprint to see if two samples are from the same bacteria. The problem is that 15-30 bands are not enough to differentiate all isolates. Some isolates whose bands look very similar may actually come from different sources and some whose bands look different may be from the same source. But if you can see the entire DNA fingerprint, then you don't have that issue. That's where whole genome sequencing comes in.
Although the PulseNet team had piloted whole genome sequencing as early as 2013, it wasn't until July of last year that the transition to using whole genome sequencing for all pathogens was complete. Though whole genome sequencing requires far more computing power to generate, analyze, and compare those millions of data points, the payoff is huge.
Stopping Outbreaks Sooner
The U.S. Food and Drug Administration (FDA) acquired their first whole genome sequencers in 2008, according to Dr. Eric Brown, the Director of the Division of Microbiology in the FDA's Office of Regulatory Science. Since then, through their GenomeTrakr program, a network of more than 60 domestic and international labs, the FDA has sequenced and publicly shared more than 400,000 isolates. "The impact of what whole genome sequencing could do to resolve a foodborne outbreak event was no less impactful than when NASA turned on the Hubble Telescope for the first time," says Brown.
Whole genome sequencing has helped identify strains of Salmonella that prior methods were unable to differentiate. In fact, whole genome sequencing can differentiate "virtually all" strains of foodborne pathogens, no matter the species, according to the FDA. This means it takes fewer clinical cases—fewer sick people—to detect and end an outbreak.
And perhaps the largest benefit of whole genome sequencing is that these detailed sequences—the millions of base pairs—can imply geographic location. The genomic information of bacterial strains can be different depending on the area of the country, helping these public health agencies eventually track the source of outbreaks—a restaurant, a farm, a food-processing center.
Coming Soon: "Lab in a Backpack"
Now that whole genome sequencing has become the go-to technology of choice for analyzing foodborne pathogens, the next step is making the process nimbler and more portable. Putting "the lab in a backpack," as Brown says.
The CDC's Carleton agrees. "Right now, the sequencer we use is a fairly big box that weighs about 60 pounds," she says. "We can't take it into the field."
A company called Oxford Nanopore Technologies is developing handheld sequencers. Their devices are meant to "enable the sequencing of anything by anyone anywhere," according to Dan Turner, the VP of Applications at Oxford Nanopore.
"The sooner that we can see linkages…the sooner the FDA gets in action to mitigate the problem and put in some kind of preventative control."
"Right now, sequencing is very much something that is done by people in white coats in laboratories that are set up for that purpose," says Turner. Oxford Nanopore would like to create a new, democratized paradigm.
The FDA is currently testing these types of portable sequencers. "We're very excited about it. We've done some pilots, to be able to do that sequencing in the field. To actually do it at a pond, at a river, at a canal. To do it on site right there," says Brown. "This, of course, is huge because it means we can have real-time sequencing capability to stay in step with an actual laboratory investigation in the field."
"The timeliness of this information is critical," says Marc Allard, a senior biomedical research officer and Brown's colleague at the FDA. "The sooner that we can see linkages…the sooner the FDA gets in action to mitigate the problem and put in some kind of preventative control."
At the moment, the world is rightly focused on COVID-19. But as the danger of one virus subsides, it's only a matter of time before another pathogen strikes. Hopefully, with new and advancing technology like whole genome sequencing, we can stop the next deadly outbreak before it really gets going.