An illustration of a robust human.
A panel of leading experts gathered this week at a sold-out event in downtown Manhattan to talk about the science and the ethics of enhancing human beings -- making people "better than well" through biomedical interventions. Here are the ten most memorable quotes from their lively discussion, which was organized by the New York Academy of Sciences, the Aspen Brain Institute, and the Hastings Center.
1) "It's okay for us to be enhanced relative to our ancestors; we are with the smallpox vaccine." —Dr. George Church, iconic genetics pioneer; professor at Harvard University and MIT
Church was more concerned with equitable access to enhancements than the morality of intervening in the first place. "We missed the last person with polio and now it's spread around the world again," he lamented.
Discussing how enhancements might become part of our species in the near-future, he mentioned the possibility of doctors slightly "overshooting" an intervention to reverse cognitive decline, for example; or younger people using such an intervention off-label. Another way might be through organ transplants, using organs that are engineered to not get cancer, or to be resistant to pain, pathogens, or senescence.
2) "All the technology we will need to fundamentally transform our species already exists. Humans are made of code, and that code is writable, readable and hackable." —Dr. Jamie Metzl, a technology futurist and geopolitical expert; Senior Fellow of the Atlantic Council, an international affairs think tank
The speed of change is on an exponential curve, and the world where we're going is changing at a much faster rate than we're used to, Metzl said. For example, a baby born 1000 years ago compared to one born today would be basically the same. But a baby born 1000 years in the future would seem like superman to us now, thanks to new capabilities that will become embedded in future people's genes over time. So how will we get from here to there?
"We will line up for small incremental benefits. By the time people are that changed, we will have adapted to a whole new set of social norms."
But, he asked, will well-meaning changes dangerously limit the diversity of our species?
3) "We are locked in a competitive arms race on both an individual and communal level, which will make it very difficult to put the brakes on. Everybody needs to be part of this conversation because it's a conversation about the future of our species." —Jamie Metzl
China, for one, plans to genetically sequence half of all newborns by 2020. In the U.S., it is standard to screen for 34 health conditions in newborns (though the exact number varies by state). There are no national guidelines for newborn genomic screening, though the National Institutes of Health is currently funding several research studies to explore the ethical concerns, potential benefits, and limitations of doing so on a large scale.
4) "I find freedom in not directing exactly how my child will be." —Josephine Johnston, Director of Research at the Hastings Center, the world's oldest bioethics research institute
Johnston cautioned against a full-throttled embrace of biomedical enhancements. Parents seeking to remake nature to serve their own purpose would be "like helicopter parenting on steroids," she said. "It could be a kind of felt obligation, something parents don't want to do but feel they must in order to compete." She warned this would be "one way to totally ruin the parenting experience altogether. I would hate to be the kind of parent who selects and controls her child's traits and talents."
Among other concerns, she worried about parents aiming to comply with social norms through technological intervention. Would a black mom, for example, feel pressure to make her child's skin paler to alleviate racial bias?
5) "We need to seriously consider the risks of a future if a handful of private companies own and monetize a map of our thoughts at any given moment." – Meredith Whittaker, Research Scientist, Open Research Lead at Google, and Co-Director of New York University's AI Now Institute, examining the social implications of artificial intelligence
The recent boom in AI research is the result of the consolidation of the tech industry's resources; only seven companies have the means to create artificial intelligence at scale, and one of the innovations on the horizon is brain-computer interfaces.
Facebook, for example, has a team of 60 engineers working on BCIs to let you type with your mind. Elon Musk's company Neuralink is working on technology that is aiming for "direct lag-free interactions between our brains and our devices."
But who will own this data? In the future, could the National Security Agency ask Neuralink, et al. for your thought log?
6) "The economic, political, and social contexts are as important as the tech itself. We need to look at power, who gets to define normal, and who falls outside of this category?" – Meredith Whittaker
Raising concerns about AI bias, Whittaker discussed how data is often coded by affluent white men from the Bay Area, potentially perpetuating discrimination against women and racial minorities.
Facial recognition, she said, is 30 percent less accurate for black women than for white men. And voice recognition systems don't hear women's voices as well as men's, among many other examples. The big question is: "Who gets to decide what's normal? And how do we ensure that different versions of normal can exist between cultures and communities? It is impossible not see the high stakes here, and how oppressive classifications of normal can marginalize people."
From left: George Church, Jamie Metzl, Josephine Johnston, Meredith Whittaker
7) "We might draw a red line at cloning or germline enhancements, but when you define those or think of specific cases, you realize you threw the baby out with the bathwater." —George Church, answering a question about whether society should agree on any red lines to prohibit certain interventions
"We should be focusing on outcomes," he suggested. "Could enhancement be a consequence of curing a disease like cognitive decline? That would concern me about drawing red lines."
8) "We have the technology to create Black Mirror. We could create a social credit score and it's terrifying." —Meredith Whittaker
In China, she said, the government is calculating scores to rank citizens based on aggregates of data like their educational history, their friend graphs, their employment and credit history, and their record of being critical of the government. These scores have already been used to bar 12 million people from travel.
"If we don't have the ability to make a choice," she said, "it could be a very frightening future."
9) "These tools will make all kinds of wonderful realities possible. Nobody looks at someone dying of cancer and says that's natural." —Jamie Metzl
Using biomedical interventions to restore health is an unequivocal moral good. But other experts questioned whether there should be a limit in how far these technologies are taken to achieve normalcy and beyond.
10) "Cancer's the easy one; what about deafness?" —Josephine Johnston, in retort
Could one person's disability be another person's desired state? "We should be so suspicious" of using technology to eradicate different ways of being in the world, she warned. Hubris has led us down the wrong path in the past, such as when homosexuality was considered a mental disorder.
"If we sometimes make mistakes about disease or dysfunction," she said, "we might make mistakes about what is a valid experience of the human condition."
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens 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.