More Families Are Using Nanny Cams to Watch Elderly Loved Ones, Raising Ethical Questions
After Jackie Costanzo's mother broke her right hip in a fall, she needed more hands-on care in her assisted-living apartment near Sacramento, California. A social worker from her health plan suggested installing a video camera to help ensure those services were provided.
Without the camera, Costanzo wouldn't have a way to confirm that caregivers had followed through with serving meals, changing clothes, and fulfilling other care needs.
When Costanzo placed the device in May 2018, she informed the administrator and staff, and at first, there were no objections. The facility posted a sign on the apartment's front door, alerting anyone who entered of recording in progress.
But this past spring, a new management company came across the sign and threatened to issue a 30-day eviction notice to her 93-year-old mother, Louise Munch, who has dementia, for violating a policy that prohibits cameras in residents' rooms. With encouragement from California Advocates for Nursing Home Reform, Costanzo researched the state's regulations but couldn't find anything to support or deny camera use. She refused to remove the recording device and prevailed.
"In essence, my mom was 'grandfathered in' because she moved in under a management company that did not specify that residents could not have cameras," says Costanzo, 73, a retired elementary schoolteacher who lives a three-hour drive away, in Silicon Valley, and visits one day every two weeks. Without the camera, Costanzo, who is her mother's only surviving child, wouldn't have a way to confirm that caregivers had followed through with serving meals, changing clothes, and fulfilling other care needs.
As technological innovations enable next of kin to remain apprised of the elderly's daily care in long-term care facilities, surveillance cameras bring legal and privacy issues to the forefront of a complex ethical debate. Families place them overtly or covertly—disguised in a makeshift clock radio, for instance—when they suspect or fear abuse or neglect, so they can maintain a watchful eye, perhaps deterring egregious behavior. But the cameras also capture intimate caregiving tasks, such as bathing and toileting, as well as dressing and undressing, which may undermine the dignity of residents.
So far, laws or guidelines in eight states—Illinois, Maryland, New Mexico, Oklahoma, Texas, Utah, Virginia, and Washington—have granted families the rights to install cameras in a resident's room. In addition, about 15 other states have proposed legislation. Some states, such as Pennsylvania, have put forth regulatory compliance guidance, according to a column published in the July/August 2018 issue of Annals of Long-Term Care.
The increasing prevalence of this legislation has placed it on the radar of long-term care providers. It also suggests a trend to clarify responsible camera use in monitoring services while respecting privacy, says Victor Lane Rose, the column's editor and director of aging services at ECRI Institute, a health care nonprofit near Philadelphia, Pennsylvania.
In most cases, a resident's family installs a camera or instigates a request in hopes of sparing their loved one from the harms of abuse, says James Wright, a family physician who serves as the ethics committee's vice chair of the Society for Post-Acute and Long-Term Care Medicine in Columbia, Maryland. A camera also allows the family to check in on the resident from afar and remain on alert for a potential fall or agitated state, he says.
"It's rare that a facility will have 24-hour presence in a patient's room. You won't have a nurse in there all the time," says Wright, who is also medical director of two long-term care centers and one assisted-living facility around Richmond, Virginia. Particularly "with dementia, the family often wonders" if their loved one is safe.
While offering families peace of mind, he notes that video cameras can also help exonerate caregivers accused of abuse or theft. Hearing aids, which typically cost between $2,000 and $3,000 each, often go missing. By reviewing a video together, families and administrators may find clues to a device's disappearance. Conversely, Wright empathizes with the main counterargument against camera use, which is the belief that "invasion of privacy is also invasion of human dignity."
In respecting modesty, ethical questions abound over whether a camera should be turned off when a patient is in the midst of receiving personal care, such as dressing and undressing or using bedpans. Other ethical issues revolve around who may access the recordings, says Lori Smetanka, executive director of the National Consumer Voice for Quality Long-Term Care in Washington, D.C.
Video cameras, she contends, are only one tool in shielding residents from abuse. They are "not substitutes for personal involvement," she says. "People need to be very vigilant visiting their family members, and facilities have a responsibility to ensure that residents are free of abuse."
Lack of accountability perpetuates abuse in long-term care settings and stems in large part from systemic underfunding.
Educating employees in abuse prevention becomes paramount, and families should ask about staff training before placing their loved one in a long-term care facility, Smetanka says. Prior to installing a camera, she recommends consulting an attorney who is familiar with this issue.
But thoughts of a camera often don't occur to families until an adverse event affects their loved one, says Toby Edelman, a senior policy attorney at the Center for Medicare Advocacy, a nonprofit organization with headquarters in Washington, D.C., and Connecticut.
"These cameras can show exactly what's going on," she explains, noting that prosecutors have used the recordings in litigation. "When residents have injuries of unknown origin" and they can't verbalize what happened to them, "the cameras may document that yes, the resident was actually hit by somebody."
With a resident's safety and security being "the most important consideration," the American Health Care Association in Washington, D.C., which represents long-term and post-acute care providers, supports allowing states, clinicians, and patients to decide about camera use on a local level, says David Gifford, senior vice president of quality and regulatory affairs and chief medical officer.
"We've seen some success with tools such as permissive legislation, where residents and their loved ones have the ability to determine whether a camera is right for them while working with the center openly and ensuring the confidentiality of other residents," says Gifford, who practiced as a geriatrician. "It is important to note, however, that surveillance cameras are still only one element of the quality matrix. We can never hope to truly improve quality care by catching bad actors after the fact."
Lack of accountability perpetuates abuse in long-term care settings and stems in large part from systemic underfunding. Low wages and morale are tied to high turnover, and cameras don't address this overarching problem, says Clara Berridge, an assistant professor of social work at the University of Washington in Seattle, who has co-authored articles on surveillance devices in elder care.
Employees often don't perceive a nursing assistant position as a long-term career trajectory and may not feel vested in the workplace. Training in the recognition and reporting of abuse becomes ineffective when workers quit shortly thereafter. Many must juggle multiple jobs to make ends meet. Staffing shortages are endemic, leading to inadequate oversight of residents and voicing of abuse complaints, she says.
In Berridge's assessment, cameras may do more harm than good. Respondents to a survey she conducted of nursing homes and assisted-living facilities in the United States found that recording devices tend to fuel workers' anxiety amid a culture that further demoralizes and dehumanizes the care they provide.
Consent becomes particularly thorny in shared rooms, which are more common than not in nursing homes. States that permit in-room cameras mandate that roommates or their legal representative be made aware. Even if the camera is directed away from their bed, it will still capture conversations as well as movements that enter its scope. "Surveillance isn't the best way to protect adults in need of support," Berridge says. "Public investment in quality care is."
"The camera is invaluable. But there's no law that says you can have it automatically, so that's wrong."
In the one-bedroom assisted-living apartment where Costanzo's mother lives alone, consent from another resident wasn't needed. Without a roommate, the camera is much less intrusive, although Costanzo wishes she had put one in the living room, not just the bedroom, for more security.
Her safety concerns escalated when she read about a Texas serial killer who smothered victims after gaining access to senior care facilities by "masquerading as a maintenance man." She points to such horrifying incidents, although exceedingly rare, as further justification for permitting cameras to help guard the vulnerable against abuse in long-term care settings. And she hopes to advocate for an applicable law in California.
"The camera is invaluable," says Costanzo, who pays for monthly Wi-Fi service so she can see and interact with her mother, who turns 94 in October, any time of day or night. "But there's no law that says you can have it automatically, so that's wrong."
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
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 book The 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.
AI's accountability
“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.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
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.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”