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.
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.