Nature Climate Change, Published online: 05 November 2025; doi:10.1038/s41558-025-02477-w

To mark the tenth anniversary of the Paris Agreement, Nature Climate Change asked experts to reflect on the progress of and barriers to several of its key Articles. They share their thoughts on important policy implications, what has been achieved and missed, as well as future directions.

Nature Climate Change, Published online: 05 November 2025; doi:10.1038/s41558-025-02471-2

How mesoscale horizontal stirring changes with warming is not well understood. Here the authors present high-resolution simulations that show that mesoscale horizontal stirring increases in the Arctic Ocean and around Antarctica, mainly due to sea ice reduction.

Although heart cells and skin cells contain identical instructions for creating proteins encoded in their DNA, they’re able to fill such disparate niches because molecular machinery can cut out and stitch together different segments of those instructions to create endlessly unique combinations.

The ingenuity of using the same genes in different ways is made possible by a process called splicing and is controlled by splicing factors; which splicing factors a cell employs determines what sets of instructions that cell produces, which, in turn, gives rise to proteins that allow cells to fulfill different functions. 

In an open-access paper published today in Nature Biotechnology, researchers in the MIT Department of Biology outlined a framework for parsing the complex relationship between sequences and splicing regulation to investigate the regulatory activities of splicing factors, creating models that can be applied to interpret and predict splicing regulation across different cell types, and even different species. Called Knockdown Activity and Target Models from Additive regression Predictions, KATMAP draws on experimental data from disrupting the expression of a splicing factor and information on which sequences the splicing factor interacts with to predict its likely targets. 

Aside from the benefits of a better understanding of gene regulation, splicing mutations — either in the gene that is spliced or in the splicing factor itself — can give rise to diseases such as cancer by altering how genes are expressed, leading to the creation or accumulation of faulty or mutated proteins. This information is critical for developing therapeutic treatments for those diseases. The researchers also demonstrated that KATMAP can potentially be used to predict whether synthetic nucleic acids, a promising treatment option for disorders including a subset of muscular atrophy and epilepsy disorders, affect splicing.

Perturbing splicing 

In eukaryotic cells, including our own, splicing occurs after DNA is transcribed to produce an RNA copy of a gene, which contains both coding and non-coding regions of RNA. The noncoding intron regions are removed, and the coding exon segments are spliced back together to make a near-final blueprint, which can then be translated into a protein. 

According to first author Michael P. McGurk, a postdoc in the lab of MIT Professor Christopher Burge, previous approaches could provide an average picture of regulation, but could not necessarily predict the regulation of splicing factors at particular exons in particular genes.

KATMAP draws on RNA sequencing data generated from perturbation experiments, which alter the expression level of a regulatory factor by either overexpressing it or knocking down its levels. The consequences of overexpression or knockdown are that the genes regulated by the splicing factor should exhibit different levels of splicing after perturbation, which helps the model identify the splicing factor’s targets. 

Cells, however, are complex, interconnected systems, where one small change can cause a cascade of effects. KATMAP is also able to distinguish between direct targets from indirect, downstream impacts by incorporating known information about the sequence the splicing factor is likely to interact with, referred to as a binding site or binding motif.

“In our analyses, we identify predicted targets as exons that have binding sites for this particular factor in the regions where this model thinks they need to be to impact regulation,” McGurk says, while non-targets may be affected by perturbation but don’t have the likely appropriate binding sites nearby. 

This is especially helpful for splicing factors that aren’t as well-studied. 

“One of our goals with KATMAP was to try to make the model general enough that it can learn what it needs to assume for particular factors, like how similar the binding site has to be to the known motif or how regulatory activity changes with the distance of the binding sites from the splice sites,” McGurk says. 

Starting simple

Although predictive models can be very powerful at presenting possible hypotheses, many are considered “black boxes,” meaning the rationale that gives rise to their conclusions is unclear. KATMAP, on the other hand, is an interpretable model that enables researchers to quickly generate hypotheses and interpret splicing patterns in terms of regulatory factors while also understanding how the predictions were made. 

“I don’t just want to predict things, I want to explain and understand,” McGurk says. “We set up the model to learn from existing information about splicing and binding, which gives us biologically interpretable parameters.” 

The researchers did have to make some simplifying assumptions in order to develop the model. KATMAP considers only one splicing factor at a time, although it is possible for splicing factors to work in concert with one another. The RNA target sequence could also be folded in such a way that the factor wouldn’t be able to access a predicted binding site, so the site is present but not utilized.

“When you try to build up complete pictures of complex phenomena, it’s usually best to start simple,” McGurk says. “A model that only considers one splicing factor at a time is a good starting point.” 

David McWaters, another postdoc in the Burge Lab and a co-author on the paper, conducted key experiments to test and validate that aspect of the KATMAP model.

Future directions

The Burge lab is collaborating with researchers at Dana-Farber Cancer Institute to apply KATMAP to the question of how splicing factors are altered in disease contexts, as well as with other researchers at MIT as part of an MIT HEALS grant to model splicing factor changes in stress responses. McGurk also hopes to extend the model to incorporate cooperative regulation for splicing factors that work together. 

“We’re still in a very exploratory phase, but I would like to be able to apply these models to try to understand splicing regulation in disease or development. In terms of variation of splicing factors, they are related, and we need to understand both,” McGurk says.

Burge, the Uncas (1923) and Helen Whitaker Professor and senior author of the paper, will continue to work on generalizing this approach to build interpretable models for other aspects of gene regulation.

“We now have a tool that can learn the pattern of activity of a splicing factor from types of data that can be readily generated for any factor of interest,” says Burge, who is also an extra-mural member of the Koch Institute for Integrative Cancer Research and an associate member of the Broad Institute of MIT and Harvard. “As we build up more of these models, we’ll be better able to infer which splicing factors have altered activity in a disease state from transcriptomic data, to help understand which splicing factors are driving pathology.”

MIT engineers have developed a flexible drug-delivery patch that can be placed on the heart after a heart attack to help promote healing and regeneration of cardiac tissue.

The new patch is designed to carry several different drugs that can be released at different times, on a pre-programmed schedule. In a study of rats, the researchers showed that this treatment reduced the amount of damaged heart tissue by 50 percent and significantly improved cardiac function.

If approved for use in humans, this type of patch could help heart attack victims recover more of their cardiac function than is now possible, the researchers say.

“When someone suffers a major heart attack, the damaged cardiac tissue doesn’t regenerate effectively, leading to a permanent loss of heart function. The tissue that was damaged doesn’t recover,” says Ana Jaklenec, a principal investigator at MIT’s Koch Institute for Integrative Cancer Research. “Our goal is to restore that function and help people regain a stronger, more resilient heart after a myocardial infarction.”

Jaklenec and Robert Langer, the David H. Koch Institute Professor at MIT and a member of the Koch Institute, are the senior authors of the new study, which appears today in Cell Biomaterials. Former MIT postdoc Erika Wangis the lead author of the paper.

Programmed drug delivery

After a heart attack, many patients end up having bypass surgery, which improves blood flow to the heart but doesn’t repair the cardiac tissue that was damaged. In the new study, the MIT team wanted to create a patch that could be applied to the heart at the same time that the surgery is performed.

This patch, they hoped, could deliver drugs over an extended time period to promote tissue healing. Many diseases, including heart conditions, require phase-specific treatment, but most systems release drugs all at once. Timed delivery better synchronizes therapy with recovery.

“We wanted to see if it’s possible to deliver a precisely orchestrated therapeutic intervention to help heal the heart, right at the site of damage, while the surgeon is already performing open-heart surgery,” Jaklenec says.

To achieve this, the researchers set out to adapt drug-delivery microparticles they had previously developed, which consist of capsules similar to tiny coffee cups with lids. These capsules are made from a polymer called PLGA and can be sealed with a drug inside.

By changing the molecular weight of the polymers used to form the lids, the researchers can control how quickly they degrade, which enables them to program the particles to release their contents at specific times. For this application, the researchers designed particles that break down during days 1-3, days 7-9, and days 12-14 after implantation.

This allowed them to devise a regimen of three drugs that promote heart healing in different ways. The first set of particles release neuregulin-1, a growth factor that helps to prevent cell death. At the next time point, particles release VEGF, a growth factor that promotes formation of blood vessels surrounding the heart. The last batch of particles releases a small molecule drug called GW788388, which inhibits the formation of scar tissue that can occur following a heart attack.

“When tissue regenerates, it follows a carefully timed series of steps,” Jaklenec says. “Dr. Wang created a system that delivers key components at just the right time, in the sequence that the body naturally uses to heal.”

The researchers embedded rows of these particles into thin sheets of a tough but flexible hydrogel, similar to a contact lens. This hydrogel is made from alginate and PEGDA, two biocompatible polymers that eventually break down in the body. For this study, the researchers created compact, miniature patches only a few millimeters across.

“We encapsulate arrays of these particles in a hydrogel patch, and then we can surgically implant this patch into the heart. In this way, we’re really programming the treatment into this material,” Wang says.

Better heart function

Once they created these patches, the researchers tested them on spheres of heart tissue that included cardiomyocytes generated from induced pluripotent stem cells. These spheres also included endothelial cells and human ventricular cardiac fibroblasts, which are also important components of the heart.

The researchers exposed those spheres to low-oxygen conditions, mimicking the effects of a heart attack, then placed the patches over them. They found that the patches promoted blood vessel growth, helped more cells to survive, and reduced the amount of fibrosis that developed.

In tests in a rat model of heart attack, the researchers also saw significant improvements following treatment with the patch. Compared to no treatment or IV injection of the same drugs, animals treated with the patch showed 33 percent higher survival rates, a 50 percent reduction in the amount of damaged tissue, and significantly increased cardiac output.

The researchers showed that the patches would eventually dissolve over time, becoming a very thin layer over the course of a year without disrupting the heart’s mechanical function.

“This is an important way to combine drug delivery and biomaterials to potentially new treatments for patients,” Langer says.

Of the drugs tested in this study, neuregulin-1 and VEGF have been tested in clinical trials to treat heart conditions, but GW788388 has only been explored in animal models. The researchers now hope to test their patches in additional animal models in hopes of running a clinical trial in the future.

The current version of the patch needs to be implanted surgically, but the researchers are exploring the possibility of incorporating these microparticles into stents that could be inserted into arteries to deliver drugs on a programmed schedule.

Other authors of the paper include Elizabeth Calle, Binbin Ying, Behnaz Eshaghi, Linzixuan Zhang, Xin Yang, Stacey Qiaohui Lin, Jooli Han, Alanna Backx, Yuting Huang, Sevinj Mursalova, Chuhan Joyce Qi, and Yi Liu.

The researchers were supported by the Natural Sciences and Engineering Research Council of Canada and the U.S. National Heart, Lung, and Blood Institute.

Microsoft is warning of a scam involving online payroll systems. Criminals use social engineering to steal people’s credentials, and then divert direct deposits into accounts that they control. Sometimes they do other things to make it harder for the victim to realize what is happening.

I feel like this kind of thing is happening everywhere, with everything. As we move more of our personal and professional lives online, we enable criminals to subvert the very systems we rely on.

The move — revealed in emails and internal drafts — sidelined EPA's deep bench of career economists.

The budge office wanted to weaken curbs on cars' soot- and smog-forming air pollutants as it unraveled a key climate policy.

Negotiators at shipping talks in London were told both they and their countries could be punished unless they voted with the U.S.

An “executive branch machinery that defaulted to caution, process, and reactive strategies” undercut the ex-president’s massive energy and infrastructure programs, a report by his former staffers details.

At risk is the ability for researchers to forecast dangerous blooms weeks in advance.

The bill would use tolls and gas taxes to expand rail and bus service. Republicans criticized the deal for taking money from highways.

“Clearly, that does damage,” EU Climate Commissioner Wopke Hoekstra told Bloomberg.

Teresa Ribera told ministers reducing the EU’s 2040 target would be an “invitation to waste money.”

Government coalition program says EU Green Deal “is unsustainable in its current form.”

The recommendation, by the former prime minister's policy think tank, is Blair’s third intervention on green policy this year.

More than 70 aircraft are struck by lightning every day. If you happen to be flying when a strike occurs, chances are you won’t feel a thing, thanks to lightning protection measures that are embedded in key zones throughout the aircraft.

Lightning protection systems work well, largely because they are designed for planes with a “tube-and-wing” structure, a simple geometry common to most aircraft today. But future airplanes may not look and fly the same way. The aviation industry is exploring new designs, including blended-wing bodies and truss-braced wings, partly to reduce fuel and weight costs. But researchers don’t yet know how these unconventional designs might respond to lightning strikes.

MIT aerospace engineers are hoping to change that with a new physics-based approach that predicts how lightning would sweep across a plane with any design. The tool then generates a zoning map highlighting sections of an aircraft that would require various degrees of lightning protection, given how they are likely to experience a strike.

“People are starting to conceive aircraft that look very different from what we’re used to, and we can’t apply exactly what we know from historical data to these new configurations because they’re just too different,” says Carmen Guerra-Garcia, associate professor of aeronautics and astronautics (AeroAstro) at MIT. “Physics-based methods are universal. They’re agnostic to the type of geometry or vehicle. This is the path forward to be able to do this lightning zoning and protect future aircraft.”

She and her colleagues report their results in a study appearing this week in IEEE Access. The study’s first author is AeroAstro graduate student Nathanael Jenkins. Other co-authors include Louisa Michael and Benjamin Westin of Boeing Research and Technology.

First strike

When lightning strikes, it first attaches to a part of a plane — typically a sharp edge or extremity — and hangs on for up to a second. During this brief flash, the plane continues speeding through the air, causing the lightning current to “sweep” over parts of its surface, potentially changing in intensity and re-attaching at certain points where the intense current flow could damage vulnerable sections of an aircraft.

In previous work, Guerra-Garcia’s group developed a model to predict the parts of a plane where lightning is most likely to first connect. That work, led by graduate student Sam Austin, established a starting point for the team’s new work, which aims to predict how and where the lightning will then sweep over the plane’s surface. The team next converted their lightning sweep predictions into zoning maps to identify vulnerable regions requiring certain levels of protection.

A typical tube-and-wing plane is divided into three main zones, as classified by the aviation industry. Each zone has a clear description of the level of current it must withstand in order to be certified for flight. Parts of a plane that are more likely to be hit by lightning are generally classified as zone 1 and require more protection, which can include embedded metal foil in the skin of the airplane that conducts away a lightning current.

To date, an airplane’s lightning zones have been determined over many years of flight inspections after lightning strikes and fine-tuning of protection measures. Guerra-Garcia and her colleagues looked to develop a zoning approach based on physics, rather than historical flight data. Such a physics-based mapping could be applied to any shape of aircraft, such as unconventional and largely untested designs, to identify regions that really require reinforcement.

“Protecting aircraft from lightning is heavy,” Jenkins says. “Embedding copper mesh or foil throughout an aircraft is an added weight penalty. And if we had the greatest level of protection for every part of the plane’s surface, the plane would weigh far too much. So zoning is about trying to optimize the weight of the system while also having it be as safe as possible.”

In the zone

For their new approach, the team developed a model to predict the pattern of lightning sweep and the corresponding lightning protection zones, for a given airplane geometry. Starting with a specific airplane shape — in their case, a typical tube-and-wing structure — the researchers simulated the fluid dynamics, or how air would flow around a plane, given a certain speed, altitude, and pitch angle. They also incorporated their previous model that predicts the places where lightning is more likely to initially attach.

For each initial attachment point, the team simulated tens of thousands of potential lightning arcs, or angles from which the current strikes the plane. They then ran the model forward to predict how the tens of thousands of potential strikes would follow the air flow across the plane’s surface. These runs produced a statistical representation of where lightning, striking a specific point on a plane, is likely to flow and potentially cause damage. The team converted this statistical representation into a map of zones of varying vulnerability.

They validated the method on a conventional tube-and-wing structure, showing that the zoning maps generated by the physics-based approach were consistent with what the aviation industry has determined over decades of fine-tuning.

“We now have a physics-based tool that provides some metrics like the probability of lightning attachment and dwell time, which is how long an arc will linger at a specific point,” Guerra-Garcia explains. “We convert those physics metrics into zoning maps to show, if I’m in this red region, the lightning arc will stay for a long time, so that region needs to be heavily protected.”

The team is starting to apply the approach to new geometries, such as blended-wing designs and truss-braced structures. The researchers envision that the tool can help designers incorporate safe and efficient lightning-protection systems early on in the design process.

“Lightning is incredible and terrifying at the same time, and I have full confidence in flying on planes at the moment,” Jenkins says. “I want to have that same confidence in 20 years’ time. So, we need a new way to zone aircraft.”

“With physics-based methods like the ones developed with professor Guerra-Garcia’s group we have the opportunity to shape industry standards and as an industry rely on the underlying physics to develop guidelines for aircraft certification through simulation,” says co-author Louisa Michael of Boeing Technology Innovation. Currently, we are engaging with industrial committees to propose these methods to be included in Aerospace Recommended Practices.”

“Zoning unconventional aircraft is not an easy task,” adds co-author Ben Westin of Boeing Technology Innovation. “But these methods will allow us to confidently identify which threat levels each part of the aircraft needs to be protected against and certified for, and they give our design engineers a platform to do their best work to optimize aircraft design.”

Beyond airplanes, Guerra-Garcia is looking at ways to adapt the lightning protection model to other technologies, including wind turbines.

“About 60 percent of blade losses are due to lightning and will become worse as we move offshore because wind turbines will be even bigger and more susceptible to upward lightning,” she says. “They have many of the same challenges of a flowing gas environment. It’s more complex, and we will apply this same sort of methodology to this space.”

This research was funded, in part, by the Boeing Company.

Quantum computers have the potential to model new molecules and weather patterns better than any computer today. They may also one day accelerate artificial intelligence algorithms at a much lower energy footprint. But anyone interested in using quantum computers faces a steep learning curve that starts with getting access to quantum devices and then figuring out one of the many quantum software programs on the market.

Now qBraid, founded by Kanav Setia and Jason Necaise ’20, is providing a gateway to quantum computing with a platform that gives users access to the leading quantum devices and software. Users can log on to qBraid’s cloud-based interface and connect with quantum devices and other computing resources from leading companies like Nvidia, Microsoft, and IBM. In a few clicks, they can start coding or deploy cutting-edge software that works across devices.

“The mission is to take you from not knowing anything about quantum computing to running your first program on these amazing machines in less than 10 minutes,” Setia says. “We’re a one-stop platform that gives access to everything the quantum ecosystem has to offer. Our goal is to enable anyone — whether they’re enterprise customers, academics, or individual users — to build and ultimately deploy applications.”

Since its founding in June of 2020, qBraid has helped more than 20,000 people in more than 120 countries deploy code on quantum devices. That traction is ultimately helping to drive innovation in a nascent industry that’s expected to play a key role in our future.

“This lowers the barrier to entry for a lot of newcomers,” Setia says. “They can be up and running in a few minutes instead of a few weeks. That’s why we’ve gotten so much adoption around the world. We’re one of the most popular platforms for accessing quantum software and hardware.”

A quantum “software sandbox”

Setia met Necaise while the two interned at IBM. At the time, Necaise was an undergraduate at MIT majoring in physics, while Setia was at Dartmouth College. The two enjoyed working together, and Necaise said if Setia ever started a company, he’d be interested in joining.

A few months later, Setia decided to take him up on the offer. At Dartmouth, Setia had taken one of the first applied quantum computing classes, but students spent weeks struggling to install all the necessary software programs before they could even start coding.

“We hadn’t even gotten close to developing any useful algorithms,” Seita said. “The idea for qBraid was, ‘Why don’t we build a software sandbox in the cloud and give people an easy programming setup out of the box?’ Connection with the hardware would already be done.”

The founders received early support from the MIT Sandbox Innovation Fund and took part in the delta v summer startup accelerator run by the Martin Trust Center for MIT Entrepreneurship.

“Both programs provided us with very strong mentorship,” Setia says. “They give you frameworks on what a startup should look like, and they bring in some of the smartest people in the world to mentor you — people you’d never have access to otherwise.”

Necaise left the company in 2021. Setia, meanwhile, continued to find problems with quantum software outside of the classroom.

“This is a massive bottleneck,” Setia says. “I’d worked on several quantum software programs that pushed out updates or changes, and suddenly all hell broke loose on my codebase. I’d spend two to four weeks jostling with these updates that had almost nothing to do with the quantum algorithms I was working on.”

QBraid started as a platform with pre-installed software that let developers start writing code immediately. The company also added support for version-controlled quantum software so developers could build applications on top without worrying about changes. Over time, qBraid added connections to quantum computers and tools that lets quantum programs run across different devices.

“The pitch was you don’t need to manage a bunch of software or a whole bunch of cloud accounts,” Setia says. “We’re a single platform: the quantum cloud.”

QBraid also launched qBook, a learning platform that offers interactive courses in quantum computing.

“If you see a piece of code you like, you just click play and the code runs,” Setia says. “You can run a whole bunch of code, modify it on the fly, and you can understand how it works. It runs on laptops, iPads, and phones. A significant portion of our users are from developing countries, and they’re developing applications from their phones.”

Democratizing quantum computing

Today qBraid’s 20,000 users come from over 400 universities and 100 companies around the world. As qBraid’s user base has grown, the company went from integrating quantum computers onto their platform from the outside to creating a quantum operating system, qBraid-OS, that is currently being used by four leading quantum companies.

“We are productizing these quantum computers,” Setia explains. “Many quantum companies are realizing they want to focus their energy completely on the hardware, with us productizing their infrastructure. We’re like the operating system for quantum computers.”

People are using qBraid to build quantum applications in AI and machine learning, to discover new molecules or develop new drugs, and to develop applications in finance and cybersecurity. With every new use case, Setia says qBraid is democratizing quantum computing to create the quantum workforce that will continue to advance the field.

“[In 2018], an article in The New York Times said there were possibly less than 1,000 people in the world that could be called experts in quantum programming,” Setia says. “A lot of people want to access these cutting-edge machines, but they don’t have the right software backgrounds. They are just getting started and want to play with algorithms. QBraid gives those people an easy programming setup out of the box.”

Nature Climate Change, Published online: 04 November 2025; doi:10.1038/s41558-025-02468-x

Human greenhouse gas emissions are raising temperatures and sea levels, collapsing ice sheets and acidifying oceans. Now, research maps out the range of emissions pathways that can limit these changes.

Nature Climate Change, Published online: 04 November 2025; doi:10.1038/s41558-025-02460-5

This study explores pathways of emissions and mitigation compatible with four climate boundaries—planetary boundaries for the climate system. The results highlight the importance of peak emission timing, limitation of carbon budgets as a sole indicator and trade-offs between mitigation options.

Amazon Ring’s upcoming face recognition tool has the potential to violate the privacy rights of millions of people and could result in Amazon breaking state biometric privacy laws.

Ring plans to introduce a feature to its home surveillance cameras called “Familiar Faces,” to identify specific people who come into view of the camera. When turned on, the feature will scan the faces of all people who approach the camera to try and find a match with a list of pre-saved faces. This will include many people who have not consented to a face scan, including friends and family, political canvassers, postal workers, delivery drivers, children selling cookies, or maybe even some people passing on the sidewalk.

When turned on, the feature will scan the faces of all people who approach the camera.

Many biometric privacy laws across the country are clear: Companies need your affirmative consent before running face recognition on you. In at least one state, ordinary people with the help of attorneys can challenge Amazon’s data collection. Where not possible, state privacy regulators should step in.

Sen. Ed Markey (D-Mass.) has already called on Amazon to abandon its plans and sent the company a list of questions. Ring spokesperson Emma Daniels answered written questions posed by EFF, which can be viewed here.

What is Ring’s “Familiar Faces”?

Amazon describes “Familiar Faces” as a tool that “intelligently recognizes familiar people.” It says this tool will provide camera owners with “personalized context of who is detected, eliminating guesswork and making it effortless to find and review important moments involving specific familiar people.” Amazon plans to release the feature in December.

The feature will allow camera owners to tag particular people so Ring cameras can automatically recognize them in the future. In order for Amazon to recognize particular people, it will need to perform face recognition on every person that steps in front of the camera. Even if a camera owner does not tag a particular face, Amazon says it may retain that biometric information for up to six months. Amazon said it does not currently use the biometric data for “model training or algorithmic purposes.”

In order to biometrically identify you, a company typically will take your image and extract a faceprint by taking tiny measurements of your face and converting that into a series of numbers that is saved for later. When you step in front of a camera again, the company takes a new faceprint and compares it to a list of previous prints to find a match. Other forms of biometric tracking can be done with a scan of your fingertip, eyeball, or even your particular gait.

Amazon has told reporters that the feature will be off by default and that it would be unavailable in certain jurisdictions with the most active biometric privacy enforcement—including the states of Illinois and Texas, and the city of Portland, Oregon. The company would not promise that this feature will remain off by default in the future.

Why is This a Privacy Problem?

Your biometric data, such as your faceprint, are some of the most sensitive pieces of data that a company can collect. Associated risks include mass surveillance, data breach, and discrimination.

Today’s feature to recognize your friend at your front door can easily be repurposed tomorrow for mass surveillance. Ring’s close partnership with police amplifies that threat. For example, in a city dense with face recognition cameras, the entirety of a person’s movements could be tracked with the click of a button, or all people could be identified at a particular location. A recent and unrelated private-public partnership in New Orleans unfortunately shows that mass surveillance through face recognition is not some far flung concern.

Amazon has already announced a related tool called “search party” that can identify and track lost dogs using neighbors’ cameras. A tool like this could be repurposed for law enforcement to track people. At least for now, Amazon says it does not have the technical capability to comply with law enforcement demanding a list of all cameras in which a person has been identified. Though, it complies with other law enforcement demands.

In addition, data breaches are a perpetual concern with any data collection. Biometrics magnify that risk because your face cannot be reset, unlike a password or credit card number. Amazon says it processes and stores biometrics collected by Ring cameras on its own servers, and that it uses comprehensive security measure to protect the data.

Face recognition has also been shown to have higher error rates with certain groups—most prominently with dark-skinned women. Similar technology has also been used to make questionable guesses about a person’s emotions, age, and gender.

Will Ring’s “Familiar Faces” Violate State Biometric Laws?

Any Ring collection of biometric information in states that require opt-in consent poses huge legal risk for the company. Amazon already told reporters that the feature will not be available in Illinois and Texas—strongly suggesting its feature could not survive legal scrutiny there. The company said it is also avoiding Portland, Oregon, which has a biometric privacy law that similar companies have avoided.

Its “familiar faces” feature will necessarily require its cameras to collect a faceprint from of every person who comes into view of an enabled camera, to try and find a match. It is impossible for Amazon to obtain consent from everyone—especially people who do not own Ring cameras. It appears that Amazon will try to unload some consent requirements onto individual camera owners themselves. Amazon says it will provide in-app messages to customers, reminding them to comply with applicable laws. But Amazon—as a company itself collecting, processing, and storing this biometric data—could have its own consent obligations under numerous laws.

Lawsuits against similar features highlight Amazon’s legal risks. In Texas, Google paid $1.375 billion to settle a lawsuit that alleged, among other things, that Google’s Nest cameras "indiscriminately capture the face geometry of any Texan who happens to come into view, including non-users." In Illinois, Facebook paid $650 million and shut down its face recognition tools that automatically scanned Facebook photos—even the faces of non-Facebook users—in order to identify people to recommend tagging. Later, Meta paid another $1.4 billion to settle a similar suit in Texas.

Many states aside from Illinois and Texas now protect biometric data. While the state has never enforced its law, Washington in 2017 passed a biometric privacy law. In 2023, the state passed an ever stronger law that protects biometric privacy, which allows individuals to sue on their own behalf. And at least 16 states have recently passed comprehensive privacy laws that often require companies to obtain opt-in consent for the collection of sensitive data, which typically includes biometric data. For example, in Colorado, a company that jointly with others determines the purpose and means of processing biometric data must obtain consent. Maryland goes farther, and such companies are essentially prohibited from collecting or processing biometric data from bystanders.

Many of these comprehensive laws have numerous loopholes and can only be enforced by state regulators—a glaring weakness facilitated in part by Amazon lobbyists.

Nonetheless, Ring’s new feature provides regulators a clear opportunity to step up to investigate, protect people’s privacy, and test the strength of their laws.