Should egg and sperm donors reveal their identities? The debate pivots on genetics and medical history.
Until age 35, Cassandra Adams assumed her mother and father were her biological parents. Then she took saliva tests through two genealogy databases—23andMe and AncestryDNA—and discovered a discrepancy in her heritage. In bringing up the matter with her parents, she learned that fertility issues had led the couple to use a sperm donor.
“Most people my age were not told,” said Adams, now 40 and a stay-at-home mom in Jersey City, New Jersey, who is involved with donor-conception advocacy. “Even now, there’s still a lot of secrecy in the industry. There are still many parents who aren’t truthful or planning not to be truthful with their children.”
While some of those offspring may never know a significant part of their medical history, Adams is grateful that she does. Surprisingly, the DNA test revealed Jewish ancestry.
“There are a lot more genetic conditions that run in Jewish families, so it was really important that I get my medical history, because it’s very different from my dad who raised me,” said Adams, who has met her biological father and two of three known half-siblings. As a result of this experience, she converted to Judaism. “It has been a big journey,” she said.
In an era of advancing assisted reproduction technologies, genetics and medical history have become front and center of the debate as to whether or not egg and sperm donations should be anonymous – and whether secrecy is even possible in many cases.
Obstacles to staying anonymous
People looking to become parents can choose what’s called an “identity-release donor,” meaning their child can receive information about the donor when he or she turns 18. There’s no way to ensure that the donor will consent to a relationship at that time. Instead, if a relationship between the donor and child is a priority, parents may decide to use a known donor.
The majority of donors want to remain anonymous, said reproductive endocrinologist Robert Kiltz, founder and director of CNY Fertility in Syracuse, New York. “In general, egg and sperm donation is mostly anonymous, meaning the recipient doesn’t know the donor and the donor doesn’t know the recipient.”
Even if the donor isn’t disclosed, though, the mystery may become unraveled when a donor-conceived person undergoes direct-to-consumer genetic testing through ancestry databases, which are growing in number and popularity. These services offer DNA testing and links to relatives with identifiable information.
In the future, another obstacle to anonymity could be laws that prohibit anonymous sperm and egg donations, if they catch on. In June, Colorado became the first state in the nation to ban anonymous sperm and egg donations. The law, which takes effect in 2025, will give donor-conceived adults the legal authority to obtain their donor’s identity and medical history. It also requires banks that provide sperm and egg collection to keep current medical records and contact information for all donors. Meanwhile, it prohibits donations from those who won’t consent to identity disclosures.
“The tradition of anonymous sperm or egg donation has created a vast array of problems, most significantly that the people thus created want to know who their mommy and daddy are,” said Kenneth W. Goodman, professor and director of the Institute for Bioethics and Health Policy at the University of Miami Miller School of Medicine.
“There are counter arguments on both sides. But the current situation has led to great uncertainty and, in many cases, grief,” Goodman said.
Donors should bear some moral responsibility for their role in reproduction by allowing their identity to be disclosed to donor-conceived individuals when they turn 18, Goodman added, noting that “there are counter arguments on both sides. But the current situation has led to great uncertainty and, in many cases, grief.”
Adams, the Jersey City woman who learned she was Jewish, has channeled these feelings into several works of art and performances on stage at venues such as the Jersey City Theater Center. During these performances, she describes the trauma of “not knowing where we come from [or] who we look like.”
In the last five years, Kathleen “Casey” DiPaola, a lawyer in Albany, New York, who focuses her practice on adoption, assisted reproduction and surrogacy, has observed a big shift toward would-be parents looking to use known sperm donors. On the other hand, with egg donation, “I’m not seeing a whole lot of change,” she said. Compared to sperm donation, more medical screening is involved with egg donation, so donors are primarily found through fertility clinics and egg donor agencies that prefer anonymity. This leads to fewer options for prospective parents seeking an egg donor with disclosed identity, DiPaola said.
Some donors want to keep in touch
Rachel Lemmons, 32, who lives in Denver, grew interested in becoming an egg donor when, as a graduate student in environmental sciences, she saw an online advertisement. “It seemed like a good way to help pay off my student loan debt,” said Lemmons, who is married and has a daughter who will turn 2-years-old in December. She didn’t end up donating until many years later, after she’d paid off the debt. “The primary motivation at that point wasn’t financial,” she said. “Instead, it felt like a really wonderful way to help someone else have a family in a few weeks’ time.”
Lemmons originally donated anonymously because she didn’t know open donations existed. She was content with that until she became aware of donor-conceived individuals’ struggles. “It concerned me that I could potentially be contributing to this,” she said, adding that the egg donor and surrogacy agency and fertility clinic wouldn’t allow her to disclose her identity retroactively.
Since then, she has donated as an open donor, and kept in touch with the recipients through email and video calls. Knowing that they were finally able to have children is “incredibly rewarding,” Lemmons said.
When to tell the kids
Stanton Honig, professor of urology and division chief of sexual and reproductive medicine at Yale School of Medicine, said for years his team has recommended that couples using donor sperm inform children about the role of the donor and their identity. “Honesty is always the best policy, and it is likely that when they become of age, they might or will be able to find out about their biological sperm donor,” he said. “Hiding it creates more of a complicated situation for children in the long run.”
Amy Jones, a 45-year-old resident of Syracuse, N.Y., has three children, including twins, who know they were conceived with anonymous donor eggs from the same individual, so they share the same genetics. Jones, who is a registered nurse and asked for her real name not to be published, told them around age seven.
“The thought of using a known donor brought more concerns—what if she wanted my babies after they were born, or how would I feel if she treated them as her own every time I saw her?” said Jones.
“I did a lot of reading, and all psychologists said that it is best to start the conversation early,” she recalled. “They understood very little of what I was telling them, but through the years, I have brought it up in discussion and encouraged them to ask questions. To this day, they don't seem to be all that interested, but I expect that later on in life they may have more questions.”
Jones and her husband opted to use a donor because premature ovarian failure at age 27 had rendered her infertile. “The decision to use an egg donor was hard enough,” she said. “The thought of using a known donor brought more concerns—what if she wanted my babies after they were born, or how would I feel if she treated them as her own every time I saw her?”
Susan C. Klock, a clinical psychologist in the section of fertility and reproductive medicine at Northwestern University Feinberg School of Medicine, said, “Anonymity is virtually impossible in the age of direct-to-consumer genetic testing.” In addition, “selecting an identity-release donor is typically not the first thing parents are looking at when they select a donor. First and foremost, they are looking for a donor with a healthy medical background. Then they may consider donor characteristics that resemble the parents.”
The donor’s medical history can be critical
Donor agencies rely on the self-reported medical history of egg and sperm donors, which can lead to gaps in learning important information. Knowing a donor’s medical history may have led some families to make different or more well-informed choices.
After Steven Gunner, a donor-conceived adult, suffered from schizophrenia and died of a drug overdose at age 27 in 2020, his parents, who live in New York, learned of a potential genetic link to his mental illness. A website, Donor Sibling Registry, revealed that the sperm donor the couple had used, a college student at the time of donation, had been hospitalized during childhood for schizophrenia and died of a drug overdose at age 46. Gunner’s story inspired Steven’s Law, a bill that was introduced in Congress in July. If passed, it would mandate sperm banks to collect information on donors’ medical conditions, and donors would have to disclose medical information the banks weren’t able to find.
With limited exceptions, the U.S. Food and Drug Administration requires donors to be screened and tested for relevant communicable disease agents and diseases such as HIV, hepatitis viruses B and C, the Zika virus and several STDs. With current technology, it is also impossible to screen for thousands of rare genetic diseases. “If a couple is using IVF (in vitro fertilization) to conceive with the donor gamete, some may opt for pre-implantation genetic testing to assess for chromosomal abnormalities,” Klock said.
Even these precautions wouldn't cover every disease, and some would-be parents don't get the genetic screening. In a situation where one donor has a large number of offspring, it is concerning that he or she can spread a rare disease to multiple people, said Nick Isel, 37, of Yorkville, Illinois, who was conceived with donor sperm due to his parents’ fertility issues. They told him the truth when he was a teenager, and he found his biological father with a journalist’s help.
Since 2016, Isel, who owns a roofing company, has been petitioning the FDA to extend the retention of medical records, requiring the fertility establishment to maintain information on sperm and egg donors for 50 years instead of the current 10-year mandate.
“The lack of family health information,” he said, “is an ongoing, slow-motion public health crisis since donor conception began being regulated by the FDA as a practice.”
Researchers probe extreme gene therapy for severe alcoholism
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
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.