The Algorithm Will See You Now
Artificial intelligence in medicine, still in an early phase, stands to transform how doctors and nurses spend their time.
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
Are the gains from gain-of-function research worth the risks?
Gain-of-function research can make pathogens more infectious and deadly. It also enables scientists to prepare remedies in advance.
Scientists have long argued that gain-of-function research, which can make viruses and other infectious agents more contagious or more deadly, was necessary to develop therapies and vaccines to counter the pathogens in case they were used for biological warfare. As the SARS-CoV-2 origins are being investigated, one prominent theory suggests it had leaked from a biolab that conducted gain-of-function research, causing a global pandemic that claimed nearly 6.9 million lives. Now some question the wisdom of engaging in this type of research, stating that the risks may far outweigh the benefits.
“Gain-of-function research means genetically changing a genome in a way that might enhance the biological function of its genes, such as its transmissibility or the range of hosts it can infect,” says George Church, professor of genetics at Harvard Medical School. This can occur through direct genetic manipulation as well as by encouraging mutations while growing successive generations of micro-organism in culture. “Some of these changes may impact pathogenesis in a way that is hard to anticipate in advance,” Church says.
In the wake of the global pandemic, the pros and cons of gain-of-function research are being fiercely debated. Some scientists say this type of research is vital for preventing future pandemics or for preparing for bioweapon attacks. Others consider it another disaster waiting to happen. The Government Accounting Office issued a report charging that a framework developed by the U.S. Department of Health & Human Services (HHS) provided inadequate oversight of this potentially deadly research. There’s a movement to stop it altogether. In January, the Viral Gain-of-Function Research Moratorium Act (S. 81) was introduced into the Senate to cease awarding federal research funding to institutions doing gain-of-function studies.
While testifying before the House COVID Origins Select Committee on March 8th, Robert Redfield, former director of the U.S. Centers for Disease Control and Prevention, said that COVID-19 may have resulted from an accidental lab leak involving gain-of-function research. Redfield said his conclusion is based upon the “rapid and high infectivity for human-to-human transmission, which then predicts the rapid evolution of new variants.”
“It is a very, very, very small subset of life science research that could potentially generate a potential pandemic pathogen,” said Gerald Parker, associate dean for Global One Health at Texas A&M University.
“In my opinion,” Redfield continues, “the COVID-19 pandemic presents a case study on the potential dangers of such research. While many believe that gain-of-function research is critical to get ahead of viruses by developing vaccines, in this case, I believe that was the exact opposite.” Consequently, Redfield called for a moratorium on gain-of-function research until there is consensus about the value of such risky science.
What constitutes risky?
The Federal Select Agent Program lists 68 specific infectious agents as risky because they are either very contagious or very deadly. In order to work with these 68 agents, scientists must register with the federal government. Meanwhile, research on deadly pathogens that aren’t easily transmitted, or pathogens that are quite contagious but not deadly, can be conducted without such oversight. “If you’re not working with select agents, you’re not required to register the research with the federal government,” says Gerald Parker, associate dean for Global One Health at Texas A&M University. But the 68-item list may not have everything that could possibly become dangerous or be engineered to be dangerous, thus escaping the government’s scrutiny—an issue that new regulations aim to address.
In January 2017, the White House Office of Science and Technology Policy (OSTP) issued additional guidance. It required federal departments and agencies to follow a series of steps when reviewing proposed research that could create, transfer, or use potential pandemic pathogens resulting from the enhancement of a pathogen’s transmissibility or virulence in humans.
In defining risky pathogens, OSTP included viruses that were likely to be highly transmissible and highly virulent, and thus very deadly. The Proposed Biosecurity Oversight Framework for the Future of Science, outlined in 2023, broadened the scope to require federal review of research “that is reasonably anticipated to enhance the transmissibility and/or virulence of any pathogen” likely to pose a threat to public health, health systems or national security. Those types of experiments also include the pathogens’ ability to evade vaccines or therapeutics, or diagnostic detection.
However, Parker says that dangers of generating a pandemic-level germ are tiny. “It is a very, very, very small subset of life science research that could potentially generate a potential pandemic pathogen.” Since gain-of-function guidelines were first issued in 2017, only three such research projects have met those requirements for HHS review. They aimed to study influenza and bird flu. Only two of those projects were funded, according to the NIH Office of Science Policy. For context, NIH funded approximately 11,000 of the 54,000 grant applications it received in 2022.
Guidelines governing gain-of-function research are being strengthened, but Church points out they aren’t ideal yet. “They need to be much clearer about penalties and avoiding positive uses before they would be enforceable.”
What do we gain from gain-of-function research?
The most commonly cited reason to conduct gain-of-function research is for biodefense—the government’s ability to deal with organisms that may pose threats to public health.
In the era of mRNA vaccines, the advance preparedness argument may be even less relevant.
“The need to work with potentially dangerous viruses is central to our preparedness,” Parker says. “It’s essential that we know and understand the basic biology, microbiology, etc. of some of these dangerous pathogens.” That includes increasing our knowledge of the molecular mechanisms by which a virus could become a sustained threat to humans. “Knowing that could help us detect [risks] earlier,” Parker says—and could make it possible to have medical countermeasures, like vaccines and therapeutics, ready.
Most vaccines, however, aren’t affected by this type of research. Essentially, scientists hope they will never need to use it. Moreover, Paul Mango, HSS former deputy chief of staff for policy, and author of the 2022 book Warp Speed, says he believes that in the era of mRNA vaccines, the advance preparedness argument may be even less relevant. “That’s because these vaccines can be developed and produced in less than 12 months, unlike traditional vaccines that require years of development,” he says.
Can better oversight guarantee safety?
Another situation, which Parker calls unnecessarily dangerous, is when regulatory bodies cannot verify that the appropriate biosafety and biosecurity controls are in place.
Gain-of-function studies, Parker points out, are conducted at the basic research level, and they’re performed in high-containment labs. “As long as all the processes, procedures and protocols are followed and there’s appropriate oversight at the institutional and scientific level, it can be conducted safely.”
Globally, there are 69 Biosafety Level 4 (BSL4) labs operating, under construction or being planned, according to recent research from King’s College London and George Mason University for Global BioLabs. Eleven of these 18 high-containment facilities that are planned or under construction are in Asia. Overall, three-quarters of the BSL4 labs are in cities, increasing public health risks if leaks occur.
Researchers say they are confident in the oversight system for BSL4 labs within the U.S. They are less confident in international labs. Global BioLabs’ report concurs. It gives the highest scores for biosafety to industrialized nations, led by France, Australia, Canada, the U.S. and Japan, and the lowest scores to Saudi Arabia, India and some developing African nations. Scores for biosecurity followed similar patterns.
“There are no harmonized international biosafety and biosecurity standards,” Parker notes. That issue has been discussed for at least a decade. Now, in the wake of SARS and the COVID-19 pandemic, scientists and regulators are likely to push for unified oversight standards. “It’s time we got serious about international harmonization of biosafety and biosecurity standards and guidelines,” Parker says. New guidelines are being worked on. The National Science Advisory Board for Biosecurity (NSABB) outlined its proposed recommendations in the document titled Proposed Biosecurity Oversight Framework for the Future of Science.
The debates about whether gain-of-function research is useful or poses unnecessary risks to humanity are likely to rage on for a while. The public too has a voice in this debate and should weigh in by communicating with their representatives in government, or by partaking in educational forums or initiatives offered by universities and other institutions. In the meantime, scientists should focus on improving the research regulations, Parker notes. “We need to continue to look for lessons learned and for gaps in our oversight system,” he says. “That’s what we need to do right now.”
The rise of remote work is a win-win for people with disabilities and employers
Disability advocates see remote work as a silver lining of the pandemic, a win-win for adults with disabilities and the business world alike.
Any corporate leader would jump at the opportunity to increase their talent pool of potential employees by 15 percent, with all these new hires belonging to an underrepresented minority. That’s especially true given tight labor markets and CEO desires to increase headcount. Yet, too few leaders realize that people with disabilities are the largest minority group in this country, numbering 50 million.
Some executives may dread the extra investments in accommodating people’s disabilities. Yet, providing full-time remote work could suffice, according to a new study by the Economic Innovation Group think tank. The authors found that the employment rate for people with disabilities did not simply reach the pre-pandemic level by mid-2022, but far surpassed it, to the highest rate in over a decade. “Remote work and a strong labor market are helping [individuals with disabilities] find work,” said Adam Ozimek, who led the research and is chief economist at the Economic Innovation Group.
Disability advocates see this development as a silver lining of the pandemic, a win-win for adults with disabilities and the business world alike. For decades before the pandemic, employers had refused requests from workers with disabilities to work remotely, according to Thomas Foley, executive director of the National Disability Institute. During the pandemic, "we all realized that...many of us could work remotely,” Foley says. “[T]hat was disproportionately positive for people with disabilities."
Charles-Edouard Catherine, director of corporate and government relations for the National Organization on Disability, said that remote-work options had been advocated for many years to accommodate disabilities. “It’s a little frustrating that for decades corporate America was saying it’s too complicated, we’ll lose productivity, and now suddenly it’s like, sure, let’s do it.”
The pandemic opened doors for people with disabilities
Early in the pandemic, employment rates dropped for everyone, including people with disabilities, according to Ozimek’s research. However, these rates recovered quickly. In the second quarter of 2022, people with disabilities aged 25 to 54, the prime working age, are 3.5 percent more likely to be employed, compared to before the pandemic.
What about people without disabilites? They are still 1.1 percent less likely to be employed.
These numbers suggest that remote work has enabled a substantial number of people with disabilities to find and retain employment.
“We have a last-in, first-out labor market, and [people with disabilities] are often among the last in and the first out,” Ozimek says. However, this dynamic has changed, with adults with disabilities seeing employment rates recover much faster. Now, the question is whether the new trend will endure, Ozimek adds. “And my conclusion is that not only is it a permanent thing, but it’s going to improve.”
Gene Boes, president and chief executive of the Northwest Center, a Seattle organization that helps people with disabilities become more independent, confirms this finding. “The new world we live in has opened the door a little bit more…because there’s just more demand for labor.”
Long COVID disabilities put a premium on remote work
Remote work can help mitigate the impact of long COVID. The U.S. Centers for Disease Control and Prevention reports that about 19 percent of those who had COVID developed long COVID. Recent Census Bureau data indicates that 16 million working age Americans suffer from it, with economic costs estimated at $3.7 trillion.
Certainly, many of these so-called long-haulers experience relatively mild symptoms - such as loss of smell - which, while troublesome, are not disabling. But other symptoms are serious enough to be disabilities.
According to a recent study from the Federal Reserve Bank of Minneapolis, about a quarter of those with long COVID changed their employment status or working hours. That means long COVID was serious enough to interfere with work for 4 million people. For many, the issue was serious enough to qualify them as disabled.
Indeed, the Federal Reserve Bank of New York found in a just-released study that the number of individuals with disabilities in the U.S. grew by 1.7 million. That growth stemmed mainly from long COVID conditions such as fatigue and brain fog, meaning difficulties with concentration or memory, with 1.3 million people reporting an increase in brain fog since mid-2020.
Many had to drop out of the labor force due to long COVID. Yet, about 900,000 people who are newly disabled have managed to continue working. Without remote work, they might have lost these jobs.
For example, a software engineer at one of my client companies has struggled with brain fog related to long COVID. With remote work, this employee can work during the hours when she feels most mentally alert and focused, even if that means short bursts of productivity throughout the day. With flexible scheduling, she can take rests, meditate, or engage in activities that help her regain focus and energy. Without the need to commute to the office, she can save energy and time and reduce stress, which is crucial when dealing with brain fog.
In fact, the author of the Federal Reserve Bank of New York study notes that long COVID can be considered a disability under the Americans with Disability Act, depending on the specifics of the condition. That means the law can require private employers with fifteen or more staff, as well as government agencies, to make reasonable accommodations for those with long COVID. Richard Deitz, the author of this study, writes in the paper that “telework and flexible scheduling are two accommodations that can be particularly beneficial for workers dealing with fatigue and brain fog.”
The current drive to return to the office, led by many C-suite executives, may need to be reconsidered in light of legal and HR considerations. Arlene S. Kanter, director of the disability law and policy program at the Syracuse University College of Law, said that the question should depend on whether people with disabilities can perform their work well at home, as they did during Covid outbreaks. “[T]hen people with disabilities, as a matter of accommodation, shouldn’t be denied that right,” Kanter said.
Diversity benefits
But companies shouldn’t need to worry about legal regulations. It simply makes dollars and sense to expand their talent pool by 15% of an underrepresented minority. After all, extensive research shows that improving diversity boosts both decision-making and financial performance.
Companies that are offering more flexible work options have already gained significant benefits in terms of diverse hires. In its efforts to adapt to the post-pandemic environment, Meta, the owner of Facebook and Instagram, decided to offer permanent fully remote work options to its entire workforce. And according to Meta chief diversity officer Maxine Williams, the candidates who accepted job offers for remote positions were “substantially more likely” to come from diverse communities: people with disabilities, Black, Hispanic, Alaskan Native, Native American, veterans, and women. The numbers bear out these claims: people with disabilities increased from 4.7 to 6.2 percent of Meta’s employees.
Having consulted for 21 companies to help them transition to hybrid work arrangements, I can confirm that Meta’s numbers aren’t a fluke. The more my clients proved willing to offer remote work, the more staff with disabilities they recruited - and retained. That includes employees with mobility challenges. But it also includes employees with less visible disabilities, such as people with long COVID and immunocompromised people who feel reluctant to put themselves at risk of getting COVID by coming into the office.
Unfortunately, many leaders fail to see the benefits of remote work for underrepresented groups, such as those with disabilities. Some even say the opposite is true, with JP Morgan CEO Jamie Dimon claiming that returning to the office will aid diversity.
What explains this poor executive decision making? Part of the answer comes from a mental blindspot called the in-group bias. Our minds tend to favor and pay attention to the concerns of those in the group of people who seem to look and think like us. Dimon and other executives without disabilities don’t perceive people with disabilities to be part of their in-group. They thus are blind to the concerns of those with disabilities, which leads to misperceptions such as Dimon’s that returning to the office will aid diversity.
In-group bias is one of many dangerous judgment errors known as cognitive biases. They impact decision making in all life areas, ranging from the future of work to relationships.
Another relevant cognitive bias is the empathy gap. This term refers to our difficulty empathizing with those outside of our in-group. The lack of empathy combines with the blindness from the in-group bias, causing executives to ignore the feelings of employees with disabilities and prospective hires.
Omission bias also plays a role. This dangerous judgment error causes us to perceive failure to act as less problematic than acting. Consequently, executives perceive a failure to support the needs of those with disabilities as a minor matter.
Conclusion
The failure to empower people with disabilities through remote work options will prove costly to the bottom lines of companies. Not only are limiting their talent pool by 15 percent, they’re harming their ability to recruit and retain diverse candidates. And as their lawyers and HR departments will tell them, by violating the ADA, they are putting themselves in legal jeopardy.
By contrast, companies like Meta - and my clients - that offer remote work opportunities are seizing a competitive advantage by recruiting these underrepresented candidates. They’re lowering costs of labor while increasing diversity. The future belongs to the savvy companies that offer the flexibility that people with disabilities need.