Should Your Employer Have Access to Your Fitbit Data?
The modern world today has become more dependent on technology than ever. We want to achieve maximal tasks with minimal human effort. And increasingly, we want our technology to go wherever we go.
Wearable devices operate by collecting massive amounts of personal information on unsuspecting users.
At work, we are leveraging the immense computing power of tablet computers. To supplement social interaction, we have turned to smartphones and social media. Lately, another novel and exciting technology is on the rise: wearable devices that track our personal data, like the FitBit and the Apple Watch. The interest and demand for these devices is soaring. CCS Insight, an organization that studies developments in digital markets, has reported that the market for wearables will be worth $25 billion by next year. By 2020, it is estimated that a staggering 411 million smart wearable devices will be sold.
Although wearables include smartwatches, fitness bands, and VR/AR headsets, devices that monitor and track health data are gaining most of the traction. Apple has announced the release of Apple Health Records, a new feature for their iOS operating system that will allow users to view and store medical records on their smart devices. Hospitals such as NYU Langone have started to use this feature on Apple Watch to send push notifications to ER doctors for vital lab results, so that they can review and respond immediately. Previously, Google partnered with Novartis to develop smart contact lens that can monitor blood glucose levels in diabetic patients, although the idea has been in limbo.
As these examples illustrate, these wearable devices present unique opportunities to address some of the most intractable problems in modern healthcare. At the same time, these devices operate by collecting massive personal information on unsuspecting users and pose unique ethical challenges regarding informed consent, user privacy, and health data security. If there is a lesson from the recent Facebook debacle, it is that big data applications, even those using anonymized data, are not immune from malicious third-party data-miners.
On consent: do users of wearable devices really know what they are getting into? There is very little evidence to support the claim that consent obtained on signing up can be considered 'informed.' A few months ago, researchers from Australia published an interesting study that surveyed users of wearable devices that monitor and track health data. The survey reported that users were "highly concerned" regarding issues of privacy and considered informed consent "very important" when asked about data sharing with third parties (for advertising or data analysis).
However, users were not aware of how privacy and informed consent were related. In essence, while they seemed to understand the abstract importance of privacy, they were unaware that clicking on the "I agree" dialog box entailed giving up control of their personal health information. This is not surprising, given that most user agreements for online applications or wearable devices are often in lengthy legalese.
Companies could theoretically use their employees' data to motivate desired behavior, throwing a modern wrench into the concept of work/life balance.
Privacy of health data is another unexamined ethical question. Although wearable devices have traditionally been used for promotion of healthy lifestyles (through fitness tracking) and ease of use (such as the call and message features on Apple Watch), increasing interest is coming from corporations. Tractica, a market research firm that studies trends in wearable devices, reports that corporate consumers will account for 17 percent of the market share in wearable devices by 2020 (current market share stands at 1 percent). This is because wearable devices, loaded with several sensors, provide unique insights to track workers' physical activity, stress levels, sleep, and health information. Companies could theoretically use this information to motivate desired behavior, throwing a modern wrench into the concept of work/life balance.
Since paying for employees' healthcare tends to be one of the largest expenses for employers, using wearable devices is seen as something that can boost the bottom line, while enhancing productivity. Even if one considers it reasonable to devise policies that promote productivity, we have yet to determine ethical frameworks that can prevent discrimination against those who may not be able-bodied, and to determine how much control employers ought to exert over the lifestyle of employees.
To be clear, wearable smart devices can address unique challenges in healthcare and elsewhere, but the focus needs to shift toward the user's needs. Data collection practices should also reflect this shift.
Privacy needs to be incorporated by design and not as an afterthought. If we were to read privacy policies properly, it could take some 180 to 300 hours per year per person. This needs to change. Privacy and consent policies ought to be in clear, simple language. If using your device means ultimately sharing your data with doctors, food manufacturers, insurers, companies, dating apps, or whoever might want access to it, then you should know that loud and clear.
The recent implementation of European Union's General Data Protection Regulation (GDPR) is also a move in the right direction. These protections include firm guidelines for consent, and an ability to withdraw consent; a right to access data, and to know what is being done with user's collected data; inherent privacy protections; notifications of security breach; and, strict penalties for companies that do not comply. For wearable devices in healthcare, collaborations with frontline providers would also reveal which areas can benefit from integrating wearable technology for maximum clinical benefit.
In our pursuit of advancement, we must not erode fundamental rights to privacy and security, and not infringe on the rights of the vulnerable and marginalized.
If current trends are any indication, wearable devices will play a central role in our future lives. In fact, the next generation of wearables will be implanted under our skin. This future is already visible when looking at the worrying rise in biohacking – or grinding, or cybernetic enhancement – where people attempt to enhance the physical capabilities of their bodies with do-it-yourself cybernetic devices (using hacker ethics to justify the practice).
Already, a company in Wisconsin called Three Square Market has become the first U.S. employer to provide rice-grained-sized radio-frequency identification (RFID) chips implanted under the skin between the thumb and forefinger of their employees. The company stated that these RFID chips (also available as wearable rings or bracelets) can be used to login to computers, open doors, or use the copy machines.
Humans have always used technology to push the boundaries of what we can do. But in our pursuit of advancement, we must not erode fundamental rights to privacy and security, and not infringe on the rights of the vulnerable and marginalized. The rise of powerful wearables will also necessitate a global discussion on moral questions such as: what are the boundaries for artificially enhancing the human body, and is hacking our bodies ethically acceptable? We should think long and hard before we answer.
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.