The rise of remote work is a win-win for people with disabilities and employers
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.
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.
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.
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.
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.
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.
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.
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.
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.
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the bookThe Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
When David M. Kurtz was doing his clinical fellowship at Stanford University Medical Center in 2009, specializing in lymphoma treatments, he found himself grappling with a question no one could answer. A typical regimen for these blood cancers prescribed six cycles of chemotherapy, but no one knew why. "The number seemed to be drawn out of a hat," Kurtz says. Some patients felt much better after just two doses, but had to endure the toxic effects of the entire course. For some elderly patients, the side effects of chemo are so harsh, they alone can kill. Others appeared to be cancer-free on the CT scans after the requisite six but then succumbed to it months later.
"Anecdotally, one patient decided to stop therapy after one dose because he felt it was so toxic that he opted for hospice instead," says Kurtz, now an oncologist at the center. "Five years down the road, he was alive and well. For him, just one dose was enough." Others would return for their one-year check up and find that their tumors grew back. Kurtz felt that while CT scans and MRIs were powerful tools, they weren't perfect ones. They couldn't tell him if there were any cancer cells left, stealthily waiting to germinate again. The scans only showed the tumor once it was back.
Blood cancers claim about 68,000 people a year, with a new diagnosis made about every three minutes, according to the Leukemia Research Foundation. For patients with B-cell lymphoma, which Kurtz focuses on, the survival chances are better than for some others. About 60 percent are cured, but the remaining 40 percent will relapse—possibly because they will have a negative CT scan, but still harbor malignant cells. "You can't see this on imaging," says Michael Green, who also treats blood cancers at University of Texas MD Anderson Medical Center.
The new blood test is sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
Kurtz wanted a better diagnostic tool, so he started working on a blood test that could capture the circulating tumor DNA or ctDNA. For that, he needed to identify the specific mutations typical for B-cell lymphomas. Working together with another fellow PhD student Jake Chabon, Kurtz finally zeroed-in on the tumor's genetic "appearance" in 2017—a pair of specific mutations sitting in close proximity to each other—a rare and telling sign. The human genome contains about 3 billion base pairs of nucleotides—molecules that compose genes—and in case of the B-cell lymphoma cells these two mutations were only a few base pairs apart. "That was the moment when the light bulb went on," Kurtz says.
The duo formed a company named Foresight Diagnostics, focusing on taking the blood test to the clinic. But knowing the tumor's mutational signature was only half the process. The other was fishing the tumor's DNA out of patients' bloodstream that contains millions of other DNA molecules, explains Chabon, now Foresight's CEO. It would be like looking for an escaped criminal in a large crowd. Kurtz and Chabon solved the problem by taking the tumor's "mug shot" first. Doctors would take the biopsy pre-treatment and sequence the tumor, as if taking the criminal's photo. After treatments, they would match the "mug shot" to all DNA molecules derived from the patient's blood sample to see if any molecular criminals managed to escape the chemo.
Foresight isn't the only company working on blood-based tumor detection tests, which are dubbed liquid biopsies—other companies such as Natera or ArcherDx developed their own. But in a recent study, the Foresight team showed that their method is significantly more sensitive in "fishing out" the cancer molecules than existing tests. Chabon says that this test can detect circulating tumor DNA in concentrations that are nearly 100 times lower than other methods. Put another way, it's sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers.
"It increases the sensitivity of detection and really catches most patients who are going to progress," says Green, the University of Texas oncologist who wasn't involved in the study, but is familiar with the method. It would also allow monitoring patients during treatment and making better-informed decisions about which therapy regimens would be most effective. "It's a minimally invasive test," Green says, and "it gives you a very high confidence about what's going on."
Having shown that the test works well, Kurtz and Chabon are planning a new trial in which oncologists would rely on their method to decide when to stop or continue chemo. They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers. The latest genome sequencing technologies have sequenced and catalogued over 2,500 different tumor specimens and the Foresight team is analyzing this data, says Chabon, which gives the team the opportunity to create more molecular "mug shots."
The team hopes that that their blood cancer test will become available to patients within about five years, making doctors' job easier, and not only at the biological level. "When I tell patients, "good news, your cancer is in remission', they ask me, 'does it mean I'm cured?'" Kurtz says. "Right now I can't answer this question because I don't know—but I would like to." His company's test, he hopes, will enable him to reply with certainty. He'd very much like to have the power of that foresight.
This article is republished from our archives to coincide with Blood Cancer Awareness Month, which highlights progress in cancer diagnostics and treatment.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.