Privacy laws are only as strong as their enforcement. In California, the state’s privacy agency recently issued its largest-ever fine for violation of the state’s privacy law—and all because of a consumer complaint.

The state’s  privacy law, the California Consumer Privacy Act or CCPA, requires many companies to respect California customers' and job applicants' rights to know, delete and correct information that businesses collect about them, and to opt-out of some types of sharing and use. It also requires companies to give notice of these rights, along with other information, to customers, job applicants, and others. (Bonus tip: Have a complaint about something else, such as a data breach? Go to the CA Attorney General.)

If you’re a Californian and think a business isn’t obeying the law, then the best thing to do is tell someone who can do something about it. How? It’s easy. In fewer than a dozen questions, you can share enough information to get the agency started.

Start With the Basics

First, head to the California Privacy Protection Agency’s website at cppa.ca.gov. On the front page, you’ll see an option to “File a Complaint.” Click on that option.

That button takes you to the online complaint form. You can also print out the agency’s paper complaint form here.

The complaint form starts, fittingly, by explaining the agency’s own privacy practices. Then it gets down to business by asking for information about your situation.

The first question offers a list of rights people have under the CCPA, such as a right to delete or a right to correct sensitive personal information. So, for example, if you’ve asked ABC Company to delete your information, but they have refused, you’d select “Right to Delete.” This helps the agency categorize your complaint and tie it directly to the requirements in the law.  The form then asks for the names of businesses, contractors, or people you want to report.

It also asks whether you’re a California resident. If you’re unsure, because you split residency or for other reasons, there is an “Unsure” option.

Adding the Details

From there, the form asks for more detailed information about what’s happened. There is a character limit on this question, so you’ll have to choose your words carefully. If you can, check out the agency’s FAQ on how to write a successful complaint before you submit the form. This will help you be specific and tell the agency what they need to hear to act on your complaint.

In the next question, include information about any proof you have supporting your complaint. So, for example, you could tell the agency you have your email asking ABC Company to delete your information, and also a screenshot of proof that they haven’t erased it. Or, say “I spoke to a person on the phone on this date.” This should just be a list of information you have, rather than a place to paste in emails or attach images.

The form will also ask if you’ve directly contacted the business about your complaint. You can just answer yes or no to this question. If it’s an issue such as a company not posting a privacy notice, or something similar, it may not have made sense to contact them directly. But if you made a deletion request, you probably have contacted them about it.

Anonymous or Not?

Finally, the complaint form will ask you to make either an “unsworn complaint” or a “sworn complaint.” This choice affects how you’ll be involved in the process going forward. You can file an anonymous unsworn complaint. But that will mean the agency can’t contact you about the issue in the future, since they don’t have any of your information.

For a sworn complaint, you have to provide some contact information and confirm that what you’re saying is true and that you’d swear to it in court.

Just because you submit contact information, that doesn’t mean the agency will contact you. Investigations are usually confidential, until there’s something like a settlement to announce. But we’ve seen that consumer complaints can be the spark for an investigation. It’s important for all of us to speak up, because it really does make a difference.

The California Privacy Protection Agency (CPPA) issued a record fine earlier this month to Tractor Supply, the country’s self-proclaimed largest “rural lifestyle” retailer, for apparently ducking its responsibilities under the California Consumer Privacy Act. Under that law, companies are required to respect California customers’ and job applicants’ rights to know, delete, and correct information that businesses collect about them, and to opt-out of some types of sharing and use. The law also requires companies to give notice of these rights, along with other information, to customers, job applicants, and others. The CPPA said that Tractor Supply failed several of these requirements. This is the first time the agency has enforced this data privacy law to protect job applicants. Perhaps best of all, the company's practices came to light all thanks to a consumer complaint filed with the agency.

Your complaints matter—so keep speaking up. 

Tractor Supply, which has 2,500 stores in 49 states, will pay for their actions to the tune of $1,350,000—the largest fine the agency has issued to date. Specifically, the agency said, Tractor Supply violated the law by:

• Failing to maintain a privacy policy that notified consumers of their rights;
• Failing to notify California job applicants of their privacy rights and how to exercise them;
• Failing to provide consumers with an effective mechanism to opt-out of the selling and sharing of their personal information, including through opt-out preference signals such as Global Privacy Control; and
• Disclosing personal information to other companies without entering into contracts that contain privacy protections.

In addition to the fine, the company also must take an inventory of its digital properties and tracking technologies and will have to certify its compliance with the California privacy law for the next four years.

It may surprise people to see that the agency’s most aggressive fine isn’t levied on a large technology company, data broker, or advertising company. But this case merely highlights what anyone who uses the internet knows: practically every company is tracking your online behavior. 

The agency may be trying to make exactly this point by zeroing in on Tractor Supply. In its press release on the fine, the agency's top enforcer was clear that they'll be casting a wide net. 

 “We will continue to look broadly across industries to identify violations of California’s privacy law,” said Michael Macko, the Agency’s head of enforcement. “We made it an enforcement priority to investigate whether businesses are properly implementing privacy rights, and this action underscores our ongoing commitment to doing that for consumers and job applicants alike.”

It is encouraging to see the agency stand up for Californians’ rights. For years, we have said privacy laws are only as strong as their enforcement. Ideally we'd like to see privacy laws—including California’s—include a private right to action to let anyone sue for privacy violations, in addition to enforcement actions like this one from regulators. Since individuals can't stand up for the majority of their own privacy rights in California, however, it's even more important that regulators such as the CPPA are active, strategic, and bold. 

It also highlights why it's important for people like you to submit complaints to regulators. As the agency itself said, “The CPPA opened an investigation into Tractor Supply’s privacy practices after receiving a complaint from a consumer in Placerville, California.” Your complaints matter—so keep speaking up. 

Laurent Demanet, MIT professor of applied mathematics, has been appointed co-director of the MIT Center for Computational Science and Engineering (CCSE), effective Sept. 1.

Demanet, who holds a joint appointment in the departments of Mathematics and Earth, Atmospheric and Planetary Sciences — where he previously served as director of the Earth Resources Laboratory — succeeds Youssef Marzouk, who is now serving as the associate dean of the MIT Schwarzman College of Computing.

Joining co-director Nicolas Hadjiconstantinou, the Quentin Berg (1937) Professor of Mechanical Engineering, Demanet will help lead CCSE, supporting students, faculty, and researchers while fostering a vibrant community of innovation and discovery in computational science and engineering (CSE).

“Laurent’s ability to translate concepts of computational science and engineering into understandable, real-world applications is an invaluable asset to CCSE. His interdisciplinary experience is a benefit to the visibility and impact of CSE research and education. I look forward to working with him,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science.

“I’m pleased to welcome Laurent into his new role as co-director of CCSE. His work greatly supports the cross-cutting methodology at the heart of the computational science and engineering community. I’m excited for CCSE to have a co-director from the School of Science, and eager to see the center continue to broaden its connections across MIT,” says Asu Ozdaglar, deputy dean of the MIT Schwarzman College of Computing, department head of Electrical Engineering and Computer Science, and MathWorks Professor.

Established in 2008, CCSE was incorporated into the MIT Schwarzman College of Computing as one of its core academic units in January 2020. An interdisciplinary research and education center dedicated to pioneering applications of computation, CCSE houses faculty, researchers, and students from a range of MIT schools, such as the schools of Engineering, Science, Architecture and Planning, and the MIT Sloan School of Management, as well as other units of the college.

“I look forward to working with Nicolas and the college leadership on raising the profile of CCSE on campus and globally. We will be pursuing a set of initiatives that span from enhancing the visibility of our research and strengthening our CSE PhD program, to expanding professional education offerings and deepening engagement with our alumni and with industry,” says Demanet.

Demanet’s research lies at the intersection of applied mathematics and scientific computing to visualize the structures beneath Earth’s surface. He also has a strong interest in scientific computing, machine learning, inverse problems, and wave propagation. Through his position as principal investigator of the Imaging and Computing Group, Demanet and his students aim to answer fundamental questions in computational seismic imaging to increase the quality and accuracy of mapping and the projection of changes in Earth’s geological structures. The implications of his work are rooted in environmental monitoring, water resources and geothermal energy, and the understanding of seismic hazards, among others.

He joined the MIT faculty in 2009. He received an Alfred P. Sloan Research Fellowship and the U.S. Air Force Young Investigator Award in 2011, and a CAREER award from the National Science Foundation in 2012. He also held the Class of 1954 Career Development Professorship from 2013 to 2016. Prior to coming to MIT, Demanet held the Szegö Assistant Professorship at Stanford University. He completed his undergraduate studies in mathematical engineering and theoretical physics at Universite de Louvain in Belgium, and earned a PhD in applied and computational mathematics at Caltech, where he was awarded the William P. Carey Prize for best dissertation in the mathematical sciences.

For Priya Donti, childhood trips to India were more than an opportunity to visit extended family. The biennial journeys activated in her a motivation that continues to shape her research and her teaching.

Contrasting her family home in Massachusetts, Donti — now the Silverman Family Career Development Professor in the MIT Department of Electrical Engineering and Computer Science (EECS) and a principal investigator at the MIT Laboratory for Information and Decision Systems — was struck by the disparities in how people live.

“It was very clear to me the extent to which inequity is a rampant issue around the world,” Donti says. “From a young age, I knew that I definitely wanted to address that issue.”

That motivation was further stoked by a high school biology teacher, who focused his class on climate and sustainability.

“We learned that climate change, this huge, important issue, would exacerbate inequity,” Donti says. “That really stuck with me and put a fire in my belly.”

So, when Donti enrolled at Harvey Mudd College, she thought she would direct her energy toward the study of chemistry or materials science to create next-generation solar panels.

Those plans, however, were jilted. Donti “fell in love” with computer science, and then discovered work by researchers in the United Kingdom who were arguing that artificial intelligence and machine learning would be essential to help integrate renewables into power grids.

“It was the first time I’d seen those two interests brought together,” she says. “I got hooked and have been working on that topic ever since.”

Pursuing a PhD at Carnegie Mellon University, Donti was able to design her degree to include computer science and public policy. In her research, she explored the need for fundamental algorithms and tools that could manage, at scale, power grids relying heavily on renewables.

“I wanted to have a hand in developing those algorithms and tool kits by creating new machine learning techniques grounded in computer science,” she says. “But I wanted to make sure that the way I was doing the work was grounded both in the actual energy systems domain and working with people in that domain” to provide what was actually needed.

While Donti was working on her PhD, she co-founded a nonprofit called Climate Change AI. Her objective, she says, was to help the community of people involved in climate and sustainability — “be they computer scientists, academics, practitioners, or policymakers” — to come together and access resources, connection, and education “to help them along that journey.”

“In the climate space,” she says, “you need experts in particular climate change-related sectors, experts in different technical and social science tool kits, problem owners, affected users, policymakers who know the regulations — all of those — to have on-the-ground scalable impact.”

When Donti came to MIT in September 2023, it was not surprising that she was drawn by its initiatives directing the application of computer science toward society’s biggest problems, especially the current threat to the health of the planet.

“We’re really thinking about where technology has a much longer-horizon impact and how technology, society, and policy all have to work together,” Donti says. “Technology is not just one-and-done and monetizable in the context of a year.”

Her work uses deep learning models to incorporate the physics and hard constraints of electric power systems that employ renewables for better forecasting, optimization, and control.

“Machine learning is already really widely used for things like solar power forecasting, which is a prerequisite to managing and balancing power grids,” she says. “My focus is, how do you improve the algorithms for actually balancing power grids in the face of a range of time-varying renewables?”

Among Donti’s breakthroughs is a promising solution for power grid operators to be able to optimize for cost, taking into account the actual physical realities of the grid, rather than relying on approximations. While the solution is not yet deployed, it appears to work 10 times faster, and far more cheaply, than previous technologies, and has attracted the attention of grid operators.

Another technology she is developing works to provide data that can be used in training machine learning systems for power system optimization. In general, much data related to the systems is private, either because it is proprietary or because of security concerns. Donti and her research group are working to create synthetic data and benchmarks that, Donti says, “can help to expose some of the underlying problems” in making power systems more efficient.

“The question is,” Donti says, “can we bring our datasets to a point such that they are just hard enough to drive progress?”

For her efforts, Donti has been awarded the U.S. Department of Energy Computational Science Graduate Fellowship and the NSF Graduate Research Fellowship. She was recognized as part of MIT Technology Review’s 2021 list of “35 Innovators Under 35” and Vox’s 2023 “Future Perfect 50.”

Next spring, Donti will co-teach a class called AI for Climate Action with Sara Beery, EECS assistant professor, whose focus is AI for biodiversity and ecosystems, and Abigail Bodner, assistant professor in the departments of EECS and Earth, Atmospheric and Planetary Sciences, whose focus is AI for climate and Earth science.

“We’re all super-excited about it,” Donti says.

Coming to MIT, Donti says, “I knew that there would be an ecosystem of people who really cared, not just about success metrics like publications and citation counts, but about the impact of our work on society.”

New documents and court records obtained by EFF show that Texas deputies queried Flock Safety's surveillance data in an abortion investigation, contradicting the narrative promoted by the company and the Johnson County Sheriff that she was “being searched for as a missing person,” and that “it was about her safety.” 

The new information shows that deputies had initiated a "death investigation" of a "non-viable fetus," logged evidence of a woman’s self-managed abortion, and consulted prosecutors about possibly charging her. 

Johnson County Sheriff Adam King repeatedly denied the automated license plate reader (ALPR) search was related to enforcing Texas's abortion ban, and Flock Safety called media accounts "false," "misleading" and "clickbait." However, according to a sworn affidavit by the lead detective, the case was in fact a death investigation in response to a report of an abortion, and deputies collected documentation of the abortion from the "reporting person," her alleged romantic partner. The death investigation remained open for weeks, with detectives interviewing the woman and reviewing her text messages about the abortion. 

The documents show that the Johnson County District Attorney's Office informed deputies that "the State could not statutorily charge [her] for taking the pill to cause the abortion or miscarriage of the non-viable fetus."

An excerpt from the JCSO detective's sworn affidavit.

The records include previously unreported details about the case that shocked public officials and reproductive justice advocates across the country when it was first reported by 404 Media in May. The case serves as a clear warning sign that when data from ALPRs is shared across state lines, it can put people at risk, including abortion seekers. And, in this case, the use may have run afoul of laws in Washington and Illinois.

A False Narrative Emerges

Last May, 404 Media obtained data revealing the Johnson County Sheriff’s Office conducted a nationwide search of more than 83,000 Flock ALPR cameras, giving the reason in the search log: “had an abortion, search for female.” Both the Sheriff's Office and Flock Safety have attempted to downplay the search as akin to a search for a missing person, claiming deputies were only looking for the woman to “check on her welfare” and that officers found a large amount of blood at the scene – a claim now contradicted by the responding investigator’s affidavit. Flock Safety went so far as to assert that journalists and advocates covering the story intentionally misrepresented the facts, describing it as "misreporting" and "clickbait-driven." 

As Flock wrote of EFF's previous commentary on this case (bold in original statement): 

Earlier this month, there was purposefully misleading reporting that a Texas police officer with the Johnson County Sheriff’s Office used LPR “to target people seeking reproductive healthcare.” This organization is actively perpetuating narratives that have been proven false, even after the record has been corrected.

According to the Sheriff in Johnson County himself, this claim is unequivocally false.

… No charges were ever filed against the woman and she was never under criminal investigation by Johnson County. She was being searched for as a missing person, not as a suspect of a crime.

That sheriff has since been arrested and indicted on felony counts in an unrelated sexual harassment and whistleblower retaliation case. He has also been charged with aggravated perjury for allegedly lying to a grand jury. EFF filed public records requests with Johnson County to obtain a more definitive account of events.

The newly released incident report and affidavit unequivocally describe the case as a "death investigation" of a "non-viable fetus." These documents also undermine the claim that the ALPR search was in response to a medical emergency, since, in fact, the abortion had occurred more than two weeks before deputies were called to investigate. 

In recent years, anti-abortion advocates and prosecutors have increasingly attempted to use “fetal homicide” and “wrongful death” statutes – originally intended to protect pregnant people from violence – to criminalize abortion and pregnancy loss. These laws, which exist in dozens of states, establish legal personhood of fetuses and can be weaponized against people who end their own pregnancies or experience a miscarriage. 

In fact, a new report from Pregnancy Justice found that in just the first two years since the Supreme Court’s decision in Dobbs, prosecutors initiated at least 412 cases charging pregnant people with crimes related to pregnancy, pregnancy loss, or birth–most under child neglect, endangerment, or abuse laws that were never intended to target pregnant people. Nine cases included allegations around individuals’ abortions, such as possession of abortion medication or attempts to obtain an abortion–instances just like this one. The report also highlights how, in many instances, prosecutors use tangentially related criminal charges to punish people for abortion, even when abortion itself is not illegal.

By framing their investigation of a self-administered abortion as a “death investigation” of a “non-viable fetus,” Texas law enforcement was signaling their intent to treat the woman’s self-managed abortion as a potential homicide, even though Texas law does not allow criminal charges to be brought against an individual for self-managing their own abortion. 

The Investigator's Sworn Account

Over two days in April, the woman went through the process of taking medication to induce an abortion. Two weeks later, her partner–who would later be charged with domestic violence against her–reported her to the sheriff's office. 

The documents confirm that the woman was not present at the home when the deputies “responded to the death (Non-viable fetus).” As part of the investigation, officers collected evidence that the man had assembled of the self-managed abortion, including photographs, the FedEx envelope the medication arrived in, and the instructions for self-administering the medication. 

Another Johnson County official ran two searches through the ALPR database with the note "had an abortion, search for female," according to Flock Safety search logs obtained by EFF. The first search, which has not been previously reported, probed 1,295 Flock Safety networks–composed of 17,684 different cameras–going back one week. The second search, which was originally exposed by 404 Media, was expanded to a full month of data across 6,809 networks, including 83,345 cameras. Both searches listed the same case number that appears on the death investigation/incident report obtained by EFF. 

After collecting the evidence from the woman’s partner, the investigators say they consulted the district attorney’s office, only to be told they could not press charges against the woman. 

An excerpt from the JCSO detective's sworn affidavit.

Nevertheless, when the subject showed up at the Sheriff’s office a week later, officers were under the impression that she came to “to tell her side of the story about the non-viable fetus.” They interviewed her, inspected text messages about the abortion on her phone, and watched her write a timeline of events. 

Only after all that did they learn that she actually wanted to report a violent assault by her partner–the same individual who had called the police to report her abortion. She alleged that less than an hour after the abortion, he choked her, put a gun to her head, and made her beg for her life. The man was ultimately charged in connection with the assault, and the case is ongoing. 

This documented account runs completely counter to what law enforcement and Flock have said publicly about the case. 

Johnson County Sheriff Adam King told 404 media: "Her family was worried that she was going to bleed to death, and we were trying to find her to get her to a hospital.” He later told the Dallas Morning News: “We were just trying to check on her welfare and get her to the doctor if needed, or to the hospital."

The account by the detective on the scene makes no mention of concerned family members or a medical investigator. To the contrary, the affidavit says that they questioned the man as to why he "waited so long to report the incident," and he responded that he needed to "process the event and call his family attorney." The ALPR search was recorded 2.5 hours after the initial call came in, as documented in the investigation report.

The Desk Sergeant's Report—One Month Later

EFF obtained a separate "case supplemental report" written by the sergeant who says he ran the May 9 ALPR searches. 

The sergeant was not present at the scene, and his account was written belatedly on June 5, almost a month after the incident and nearly a week after 404 Media had already published the sheriff’s alternative account of the Flock Safety search, kicking off a national controversy. The sheriff's office provided this sergeant's report to Dallas Morning News. 

In the report, the sergeant claims that the officers on the ground asked him to start "looking up" the woman due to there being "a large amount of blood" found at the residence—an unsubstantiated claim that is in conflict with the lead investigator’s affidavit. The sergeant repeatedly expresses that the situation was "not making sense." He claims he was worried that the partner had hurt the woman and her children, so "to check their welfare," he used TransUnion's TLO commercial investigative database system to look up her address. Once he identified her vehicle, he ran the plate through the Flock database, returning hits in Dallas.

Two abortion-related searches in the JCSO's Flock Safety ALPR audit log

The sergeant's report, filed after the case attracted media attention, notably omits any mention of the abortion at the center of the investigation, although it does note that the caller claimed to have found a fetus. The report does not explain, or even address, why the sergeant used the phrase "had an abortion, search for female” as the official reason for the ALPR searches in the audit log. 

It's also unclear why the sergeant submitted the supplemental report at all, weeks after the incident. By that time, the lead investigator had already filed a sworn affidavit that contradicted the sergeant's account. For example, the investigator, who was on the scene, does not describe finding any blood or taking blood samples into evidence, only photographs of what the partner believed to be the fetus. 

One area where they concur: both reports are clearly marked as a "death investigation." 

Correcting the Record

Since 404 Media first reported on this case, King has perpetuated the false narrative, telling reporters that the woman was never under investigation, that officers had not considered charges against her, and that "it was all about her safety."

But here are the facts: 

• The reports that have been released so far describe this as a death investigation.
• The lead detective described himself as "working a death investigation… of a non-viable fetus" at the time he interviewed the woman (a week after the ALPR searches).
• The detective wrote that they consulted the district attorney's office about whether they could charge her for "taking the pill to cause the abortion or miscarriage of the non-viable fetus." They were told they could not.
• Investigators collected a lot of data, including photos and documentation of the abortion, and ran her through multiple databases. They even reviewed her text messages about the abortion. 
• The death investigation was open for more than a month.

The death investigation was only marked closed in mid-June, weeks after 404 Media's article and a mere days before the Dallas Morning News published its report, in which the sheriff inaccurately claimed the woman "was not under investigation at any point."

Flock has promoted this unsupported narrative on its blog and in multimedia appearances. We did not reach out to Flock for comment on this article, as their communications director previously told us the company will not answer our inquiries until we "correct the record and admit to your audience that you purposefully spread misinformation which you know to be untrue" about this case. 

Consider the record corrected: It turns out the truth is even more damning than initially reported.

The Aftermath

In the aftermath of the original reporting, government officials began to take action. The networks searched by Johnson County included cameras in Illinois and Washington state, both states where abortion access is protected by law. Since then: 

• The Illinois Secretary of State has announced his intent to “crack down on unlawful use of license plate reader data,” and urged the state’s Attorney General to investigate the matter. 
• In California, which also has prohibitions on sharing ALPR out of state and for abortion-ban enforcement, the legislature cited the case in support of pending legislation to restrict ALPR use.
• Ranking Members of the House Oversight Committee and one of its subcommittees launched a formal investigation into Flock’s role in “enabling invasive surveillance practices that threaten the privacy, safety, and civil liberties of women, immigrants, and other vulnerable Americans.” 
• Senator Ron Wyden secured a commitment from Flock to protect Oregonians' data from out-of-state immigration and abortion-related queries.

In response to mounting pressure, Flock announced a series of new features supposedly designed to prevent future abuses. These include blocking “impermissible” searches, requiring that all searches include a “reason,” and implementing AI-driven audit alerts to flag suspicious activity. But as we've detailed elsewhere, these measures are cosmetic at best—easily circumvented by officers using vague search terms or reusing legitimate case numbers. The fundamental architecture that enabled the abuse remains unchanged. 

Meanwhile, as the news continued to harm the company's sales, Flock CEO Garrett Langley embarked on a press tour to smear reporters and others who had raised alarms about the usage. In an interview with Forbes, he even doubled down and extolled the use of the ALPR in this case. 

So when I look at this, I go “this is everything’s working as it should be.” A family was concerned for a family member. They used Flock to help find her, when she could have been unwell. She was physically okay, which is great. But due to the political climate, this was really good clickbait.

Nothing about this is working as it should, but it is working as Flock designed. 

The Danger of Unchecked Surveillance

Flock Safety ALPR cameras

This case reveals the fundamental danger of allowing companies like Flock Safety to build massive, interconnected surveillance networks that can be searched across state lines with minimal oversight. When a single search query can access more than 83,000 cameras spanning almost the entire country, the potential for abuse is staggering, particularly when weaponized against people seeking reproductive healthcare. 

The searches in this case may have violated laws in states like Washington and Illinois, where restrictions exist specifically to prevent this kind of surveillance overreach. But those protections mean nothing when a Texas deputy can access cameras in those states with a few keystrokes, without external review that the search is legal and legitimate under local law. In this case, external agencies should have seen the word "abortion" and questioned the search, but the next time an officer is investigating such a case, they may use a more vague or misleading term to justify the search. In fact, it's possible it has already happened. 

ALPRs were marketed to the public as tools to find stolen cars and locate missing persons. Instead, they've become a dragnet that allows law enforcement to track anyone, anywhere, for any reason—including investigating people's healthcare decisions. This case makes clear that neither the companies profiting from this technology nor the agencies deploying it can be trusted to tell the full story about how it's being used.

States must ban law enforcement from using ALPRs to investigate healthcare decisions and prohibit sharing data across state lines. Local governments may try remedies like reducing data retention period to minutes instead of weeks or months—but, really, ending their ALPR programs altogether is the strongest way to protect their most vulnerable constituents. Without these safeguards, every license plate scan becomes a potential weapon against a person seeking healthcare.

Citizen Lab has uncovered a coordinated AI-enabled influence operation against the Iranian government, probably conducted by Israel.

Key Findings

• A coordinated network of more than 50 inauthentic X profiles is conducting an AI-enabled influence operation. The network, which we refer to as “PRISONBREAK,” is spreading narratives inciting Iranian audiences to revolt against the Islamic Republic of Iran.
• While the network was created in 2023, almost all of its activity was conducted starting in January 2025, and continues to the present day.
• The profiles’ activity appears to have been synchronized, at least in part, with the military campaign that the Israel Defense Forces conducted against Iranian targets in June 2025. ...

The unannounced move came after President Donald Trump threatened to reduce FEMA aid, jarring emergency management professionals.

Jeffrey Lantz had long served as a U.S. envoy to the International Maritime Organization, which aims to cut shipping emissions.

Republicans in Congress have gone from trying to develop conservative solutions to climate change to all but ignoring the issue.

Researchers say marine heat waves could soon become more frequent in the future.

A judge ruled that FEMA should have considered options like installing solar panels for restoring the island's grid.

The program aims to cover additional expenses incurred by firms switching to cleaner processes.

Finance Minister Lars Klingbeil will present a draft law soon that will keep the existing tax exemption for EVs in place until 2035, said a spokesperson.

In the Illam district, whole villages were swept away by landslides. Rainfall was hampering rescue efforts.

Landslides destroyed homes and infrastructure and left hundreds of tourists stranded over the weekend in the Darjeeling region.

Tokamaks are machines that are meant to hold and harness the power of the sun. These fusion machines use powerful magnets to contain a plasma hotter than the sun’s core and push the plasma’s atoms to fuse and release energy. If tokamaks can operate safely and efficiently, the machines could one day provide clean and limitless fusion energy.

Today, there are a number of experimental tokamaks in operation around the world, with more underway. Most are small-scale research machines built to investigate how the devices can spin up plasma and harness its energy. One of the challenges that tokamaks face is how to safely and reliably turn off a plasma current that is circulating at speeds of up to 100 kilometers per second, at temperatures of over 100 million degrees Celsius.

Such “rampdowns” are necessary when a plasma becomes unstable. To prevent the plasma from further disrupting and potentially damaging the device’s interior, operators ramp down the plasma current. But occasionally the rampdown itself can destabilize the plasma. In some machines, rampdowns have caused scrapes and scarring to the tokamak’s interior — minor damage that still requires considerable time and resources to repair.

Now, scientists at MIT have developed a method to predict how plasma in a tokamak will behave during a rampdown. The team combined machine-learning tools with a physics-based model of plasma dynamics to simulate a plasma’s behavior and any instabilities that may arise as the plasma is ramped down and turned off. The researchers trained and tested the new model on plasma data from an experimental tokamak in Switzerland. They found the method quickly learned how plasma would evolve as it was tuned down in different ways. What’s more, the method achieved a high level of accuracy using a relatively small amount of data. This training efficiency is promising, given that each experimental run of a tokamak is expensive and quality data is limited as a result.

The new model, which the team highlights this week in an open-access Nature Communications paper, could improve the safety and reliability of future fusion power plants.

“For fusion to be a useful energy source it’s going to have to be reliable,” says lead author Allen Wang, a graduate student in aeronautics and astronautics and a member of the Disruption Group at MIT’s Plasma Science and Fusion Center (PSFC). “To be reliable, we need to get good at managing our plasmas.”

The study’s MIT co-authors include PSFC Principal Research Scientist and Disruptions Group leader Cristina Rea, and members of the Laboratory for Information and Decision Systems (LIDS) Oswin So, Charles Dawson, and Professor Chuchu Fan, along with Mark (Dan) Boyer of Commonwealth Fusion Systems and collaborators from the Swiss Plasma Center in Switzerland.

“A delicate balance”

Tokamaks are experimental fusion devices that were first built in the Soviet Union in the 1950s. The device gets its name from a Russian acronym that translates to a “toroidal chamber with magnetic coils.” Just as its name describes, a tokamak is toroidal, or donut-shaped, and uses powerful magnets to contain and spin up a gas to temperatures and energies high enough that atoms in the resulting plasma can fuse and release energy.

Today, tokamak experiments are relatively low-energy in scale, with few approaching the size and output needed to generate safe, reliable, usable energy. Disruptions in experimental, low-energy tokamaks are generally not an issue. But as fusion machines scale up to grid-scale dimensions, controlling much higher-energy plasmas at all phases will be paramount to maintaining a machine’s safe and efficient operation.

“Uncontrolled plasma terminations, even during rampdown, can generate intense heat fluxes damaging the internal walls,” Wang notes. “Quite often, especially with the high-performance plasmas, rampdowns actually can push the plasma closer to some instability limits. So, it’s a delicate balance. And there’s a lot of focus now on how to manage instabilities so that we can routinely and reliably take these plasmas and safely power them down. And there are relatively few studies done on how to do that well.”

Bringing down the pulse

Wang and his colleagues developed a model to predict how a plasma will behave during tokamak rampdown. While they could have simply applied machine-learning tools such as a neural network to learn signs of instabilities in plasma data, “you would need an ungodly amount of data” for such tools to discern the very subtle and ephemeral changes in extremely high-temperature, high-energy plasmas, Wang says.

Instead, the researchers paired a neural network with an existing model that simulates plasma dynamics according to the fundamental rules of physics. With this combination of machine learning and a physics-based plasma simulation, the team found that only a couple hundred pulses at low performance, and a small handful of pulses at high performance, were sufficient to train and validate the new model.

The data they used for the new study came from the TCV, the Swiss “variable configuration tokamak” operated by the Swiss Plasma Center at EPFL (the Swiss Federal Institute of Technology Lausanne). The TCV is a small experimental fusion experimental device that is used for research purposes, often as test bed for next-generation device solutions. Wang used the data from several hundred TCV plasma pulses that included properties of the plasma such as its temperature and energies during each pulse’s ramp-up, run, and ramp-down. He trained the new model on this data, then tested it and found it was able to accurately predict the plasma’s evolution given the initial conditions of a particular tokamak run.

The researchers also developed an algorithm to translate the model’s predictions into practical “trajectories,” or plasma-managing instructions that a tokamak controller can automatically carry out to for instance adjust the magnets or temperature maintain the plasma’s stability. They implemented the algorithm on several TCV runs and found that it produced trajectories that safely ramped down a plasma pulse, in some cases faster and without disruptions compared to runs without the new method.

“At some point the plasma will always go away, but we call it a disruption when the plasma goes away at high energy. Here, we ramped the energy down to nothing,” Wang notes. “We did it a number of times. And we did things much better across the board. So, we had statistical confidence that we made things better.”

The work was supported in part by Commonwealth Fusion Systems (CFS), an MIT spinout that intends to build the world’s first compact, grid-scale fusion power plant. The company is developing a demo tokamak, SPARC, designed to produce net-energy plasma, meaning that it should generate more energy than it takes to heat up the plasma. Wang and his colleagues are working with CFS on ways that the new prediction model and tools like it can better predict plasma behavior and prevent costly disruptions to enable safe and reliable fusion power.

“We’re trying to tackle the science questions to make fusion routinely useful,” Wang says. “What we’ve done here is the start of what is still a long journey. But I think we’ve made some nice progress.”

Additional support for the research came from the framework of the EUROfusion Consortium, via the Euratom Research and Training Program and funded by the Swiss State Secretariat for Education, Research, and Innovation.

MIT engineers have developed a printable aluminum alloy that can withstand high temperatures and is five times stronger than traditionally manufactured aluminum.

The new printable metal is made from a mix of aluminum and other elements that the team identified using a combination of simulations and machine learning, which significantly pruned the number of possible combinations of materials to search through. While traditional methods would require simulating over 1 million possible combinations of materials, the team’s new machine learning-based approach needed only to evaluate 40 possible compositions before identifying an ideal mix for a high-strength, printable aluminum alloy.

When they printed the alloy and tested the resulting material, the team confirmed that, as predicted, the aluminum alloy was as strong as the strongest aluminum alloys that are manufactured today using traditional casting methods.

The researchers envision that the new printable aluminum could be made into stronger, more lightweight and temperature-resistant products, such as fan blades in jet engines. Fan blades are traditionally cast from titanium — a material that is more than 50 percent heavier and up to 10 times costlier than aluminum — or made from advanced composites.

“If we can use lighter, high-strength material, this would save a considerable amount of energy for the transportation industry,” says Mohadeseh Taheri-Mousavi, who led the work as a postdoc at MIT and is now an assistant professor at Carnegie Mellon University.

“Because 3D printing can produce complex geometries, save material, and enable unique designs, we see this printable alloy as something that could also be used in advanced vacuum pumps, high-end automobiles, and cooling devices for data centers,” adds John Hart, the Class of 1922 Professor and head of the Department of Mechanical Engineering at MIT.

Hart and Taheri-Mousavi provide details on the new printable aluminum design in a paper published in the journal Advanced Materials. The paper’s MIT co-authors include Michael Xu, Clay Houser, Shaolou Wei, James LeBeau, and Greg Olson, along with Florian Hengsbach and Mirko Schaper of Paderborn University in Germany, and Zhaoxuan Ge and Benjamin Glaser of Carnegie Mellon University.

Micro-sizing

The new work grew out of an MIT class that Taheri-Mousavi took in 2020, which was taught by Greg Olson, professor of the practice in the Department of Materials Science and Engineering. As part of the class, students learned to use computational simulations to design high-performance alloys. Alloys are materials that are made from a mix of different elements, the combination of which imparts exceptional strength and other unique properties to the material as a whole.

Olson challenged the class to design an aluminum alloy that would be stronger than the strongest printable aluminum alloy designed to date. As with most materials, the strength of aluminum depends in large part on its microstructure: The smaller and more densely packed its microscopic constituents, or “precipitates,” the stronger the alloy would be.

With this in mind, the class used computer simulations to methodically combine aluminum with various types and concentrations of elements, to simulate and predict the resulting alloy’s strength. However, the exercise failed to produce a stronger result. At the end of the class, Taheri-Mousavi wondered: Could machine learning do better?

“At some point, there are a lot of things that contribute nonlinearly to a material’s properties, and you are lost,” Taheri-Mousavi says. “With machine-learning tools, they can point you to where you need to focus, and tell you for example, these two elements are controlling this feature. It lets you explore the design space more efficiently.”

Layer by layer

In the new study, Taheri-Mousavi continued where Olson’s class left off, this time looking to identify a stronger recipe for aluminum alloy. This time, she used machine-learning techniques designed to efficiently comb through data such as the properties of elements, to identify key connections and correlations that should lead to a more desirable outcome or product.

She found that, using just 40 compositions mixing aluminum with different elements, their machine-learning approach quickly homed in on a recipe for an aluminum alloy with higher volume fraction of small precipitates, and therefore higher strength, than what the previous studies identified. The alloy’s strength was even higher than what they could identify after simulating over 1 million possibilities without using machine learning.

To physically produce this new strong, small-precipitate alloy, the team realized 3D printing would be the way to go instead of traditional metal casting, in which molten liquid aluminum is poured into a mold and is left to cool and harden. The longer this cooling time is, the more likely the individual precipitate is to grow.

The researchers showed that 3D printing, broadly also known as additive manufacturing, can be a faster way to cool and solidify the aluminum alloy. Specifically, they considered laser bed powder fusion (LBPF) — a technique by which a powder is deposited, layer by layer, on a surface in a desired pattern and then quickly melted by a laser that traces over the pattern. The melted pattern is thin enough that it solidfies quickly before another layer is deposited and similarly “printed.” The team found that LBPF’s inherently rapid cooling and solidification enabled the small-precipitate, high-strength aluminum alloy that their machine learning method predicted.

“Sometimes we have to think about how to get a material to be compatible with 3D printing,” says study co-author John Hart. “Here, 3D printing opens a new door because of the unique characteristics of the process — particularly, the fast cooling rate. Very rapid freezing of the alloy after it’s melted by the laser creates this special set of properties.”

Putting their idea into practice, the researchers ordered a formulation of printable powder, based on their new aluminum alloy recipe. They sent the powder — a mix of aluminum and five other elements — to collaborators in Germany, who printed small samples of the alloy using their in-house LPBF system. The samples were then sent to MIT where the team ran multiple tests to measure the alloy’s strength and image the samples’ microstructure.

Their results confirmed the predictions made by their initial machine learning search: The printed alloy was five times stronger than a casted counterpart and 50 percent stronger than alloys designed using conventional simulations without machine learning. The new alloy’s microstructure also consisted of a higher volume fraction of small precipitates, and was stable at high temperatures of up to 400 degrees Celsius — a very high temperature for aluminum alloys.

The researchers are applying similar machine-learning techniques to further optimize other properties of the alloy.

“Our methodology opens new doors for anyone who wants to do 3D printing alloy design,” Taheri-Mousavi says. “My dream is that one day, passengers looking out their airplane window will see fan blades of engines made from our aluminum alloys.”

This work was carried out, in part, using MIT.nano’s characterization facilities.

In a world full of competing sounds, we often have to filter out a lot of noise to hear what’s most important. This critical skill may come more easily for people with musical training, according to scientists at MIT’s McGovern Institute for Brain Research, who used brain imaging to follow what happens when people try to focus their attention on certain sounds.

When Cassia Low Manting, a recent MIT postdoc working in the labs of MIT Professor and McGovern Institute PI John Gabrieli and former McGovern Institute PI Dimitrios Pantazis, asked people to focus on a particular melody while another melody played at the same time, individuals with musical backgrounds were, unsurprisingly, better able to follow the target tune. An analysis of study participants’ brain activity suggests this advantage arises because musical training sharpens neural mechanisms that amplify the sounds they want to listen to while turning down distractions. 

“People can hear, understand, and prioritize multiple sounds around them that flow on a moment-to-moment basis,” explains Gabrieli, who is the Grover Hermann Professor of Health Sciences and Technology at MIT. “This study reveals the specific brain mechanisms that successfully process simultaneous sounds on a moment-to-moment basis and promote attention to the most important sounds. It also shows how musical training alters that processing in the mind and brain, offering insight into how experience shapes the way we listen and pay attention.”

The research team, which also included senior author Daniel Lundqvist at the Karolinska Institute in Sweden, reported their open-access findings Sept. 17 in the journal Science Advances. Manting, who is now at the Karolinska Institute, notes that the research is part of an ongoing collaboration between the two institutions.

Overcoming challenges

Participants in the study had vastly difference backgrounds when it came to music. Some were professional musicians with deep training and experience, while others struggled to differentiate between the two tunes they were played, despite each one’s distinct pitch. This disparity allowed the researchers to explore how the brain’s capacity for attention might change with experience. “Musicians are very fun to study because their brains have been morphed in ways based on their training,” Manting says. “It’s a nice model to study these training effects.”

Still, the researchers had significant challenges to overcome. It has been hard to study how the brain manages auditory attention, because when researchers use neuroimaging to monitor brain activity, they see the brain’s response to all sounds: those that the listener cares most about, as well as those the listener is trying to ignore. It is usually difficult to figure out which brain signals were triggered by which sounds.

Manting and her colleagues overcame this challenge with a method called frequency tagging. Rather than playing the melodies in their experiments at a constant volume, the volume of each melody oscillated, rising and falling with a particular frequency. Each melody had its own frequency, creating detectable patterns in the brain signals that responded to it. “When you play these two sounds simultaneously to the subject and you record the brain signal, you can say, this 39-Hertz activity corresponds to the lower-pitch sound and the 43-Hertz activity corresponds specifically to the higher-pitch sound,” Manting explains. “It is very clean and very clear.”

When they paired frequency tagging with magnetoencephalography, a noninvasive method of monitoring brain activity, the team was able to track how their study participants’ brains responded to each of two melodies during their experiments. While the two tunes played, subjects were instructed to follow either the higher-pitched or the lower-pitched melody. When the music stopped, they were asked about the final notes of the target tune: did they rise or did they fall? The researchers could make this task harder by making the two tunes closer together in pitch, as well as by altering the timing of the notes.

Manting used a survey that asked about musical experience to score each participant’s musicality, and this measure had an obvious effect on task performance: The more musical a person was, the more successful they were at following the tune they had been asked to track.

To look for differences in brain activity that might explain this, the research team developed a new machine-learning approach to analyze their data. They used it to tease apart what was happening in the brain as participants focused on the target tune — even, in some cases, when the notes of the distracting tune played at the exact same time.

Top-down versus bottom-up attention

What they found was a clear separation of brain activity associated with two kinds of attention, known as top-down and bottom-up attention. Manting explains that top-down attention is goal-oriented, involving a conscious focus — the kind of attention listeners called on as they followed the target tune. Bottom-up attention, on the other hand, is triggered by the nature of the sound itself. A fire alarm would be expected to trigger this kind of attention, both with its volume and its suddenness. The distracting tune in the team’s experiments triggered activity associated with bottom-up attention — but more so in some people than in others.

“The more musical someone is, the better they are at focusing their top-down selective attention, and the less the effect of bottom-up attention is,” Manting explains.

Manting expects that musicians use their heightened capacity for top-down attention in other situations, as well. For example, they might be better than others at following a conversation in a room filled with background chatter. “I would put my bet on it that there is a high chance that they will be great at zooming into sounds,” she says.

She wonders, however, if one kind of distraction might actually be harder for a musician to filter out: the sound of their own instrument. Manting herself plays both the piano and the Chinese harp, and she says hearing those instruments is “like someone calling my name.” It’s one of many questions about how musical training affects cognition that she plans to explore in her future work.

Matthew D. Shoulders, the Class of 1942 Professor of Chemistry, a MacVicar Faculty Fellow, and an associate member of the Broad Institute of MIT and Harvard, has been named head of the MIT Department of Chemistry, effective Jan. 16, 2026. 

“Matt has made pioneering contributions to the chemistry research community through his research on mechanisms of proteostasis and his development of next-generation techniques to address challenges in biomedicine and agriculture,” says Nergis Mavalvala, dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics. “He is also a dedicated educator, beloved by undergraduates and graduates alike. I know the department will be in good hands as we double down on our commitment to world-leading research and education in the face of financial headwinds.”

Shoulders succeeds Troy Van Voorhis, the Robert T. Haslam and Bradley Dewey Professor of Chemistry, who has been at the helm since October 2019.

“I am tremendously grateful to Troy for his leadership the past six years, building a fantastic community here in our department. We face challenges, but also many exciting opportunities, as a department in the years to come,” says Shoulders. “One thing is certain: Chemistry innovations are critical to solving pressing global challenges. Through the research that we do and the scientists we train, our department has a huge role to play in shaping the future.”

Shoulders studies how cells fold proteins, and he develops ​and applies novel protein engineering techniques to challenges in biotechnology. His work across chemistry and biochemistry fields including proteostasis, extracellular matrix biology, virology, evolution, and synthetic biology is yielding not just important insights into topics like how cells build healthy tissues and how proteins evolve, but also influencing approaches to disease therapy and biotechnology development.

“Matt is an outstanding researcher whose work touches on fundamental questions about how the cell machinery directs the synthesis and folding of proteins. His discoveries about how that machinery breaks down as a result of mutations or in response to stress has a fundamental impact on how we think about and treat human diseases,” says Van Voorhis.

In one part of Matt's current research program, he is studying how protein folding systems in cells — known as chaperones — shape the evolution of their clients. Amongst other discoveries, his lab has shown that viral pathogens hijack human chaperones to enable their rapid evolution and escape from host immunity. In related recent work, they have discovered that these same chaperones can promote access to malignancy-driving mutations in tumors. Beyond fundamental insights into evolutionary biology, these findings hold potential to open new therapeutic strategies to target cancer and viral infections.

“Matt’s ability to see both the details and the big picture makes him an outstanding researcher and a natural leader for the department,” says Timothy Swager, the John D. MacArthur Professor of Chemistry. “MIT Chemistry can only benefit from his dedication to understanding and addressing the parts and the whole.” 

Shoulders also leads a food security project through the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS). Shoulders, along with MIT Research Scientist Robbie Wilson, assembled an interdisciplinary team based at MIT to enhance climate resilience in agriculture by improving one of the most inefficient aspects of photosynthesis, the carbon dioxide-fixing plant enzyme RuBisCO. J-WAFS funded this high-risk, high-reward MIT Grand Challenge project in 2023, and it has received further support from federal research agencies and the Grantham Foundation for the Protection of the Environment. 

“Our collaborative team of biochemists and synthetic biologists, computational biologists, and chemists is deeply integrated with plant biologists, creating a robust feedback loop for enzyme engineering,” Shoulders says. “Together, this team is making a concerted effort using state-of-the-art techniques to engineer crop RuBisCO with an eye to helping make meaningful gains in securing a stable crop supply, hopefully with accompanying improvements in both food and water security.”

In addition to his research contributions, Shoulders has taught multiple classes for Course V, including 5.54 (Advances in Chemical Biology) and 5.111 (Principles of Chemical Science), along with a number of other key chemistry classes. His contributions to a 5.111 “bootcamp” through the MITx platform served to address gaps in the classroom curriculum by providing online tools to help undergraduate students better grasp the material in the chemistry General Institute Requirement (GIR). His development of Guided Learning Demonstrations to support first-year chemistry courses at MIT has helped bring the lab to the GIR, and also contributed to the popularity of 5.111 courses offered regularly via MITx.

“I have had the pleasure of teaching with Matt on several occasions, and he is a fantastic educator. He is an innovator both inside and outside the classroom and has an unwavering commitment to his students’ success,” says Van Voorhis of Shoulders, who was named a 2022 MacVicar Faculty Fellow, and who received a Committed to Caring award through the Office of Graduate Education.

Shoulders also founded the MIT Homeschool Internship Program for Science and Technology, which brings high school students to campus for paid summer research experiences in labs across the Institute.

He is a founding member of the Department of Chemistry’s Quality of Life Committee and chair for the last six years, helping to improve all aspects of opportunity, professional development, and experience in the department: “countless changes that have helped make MIT a better place for all,” as Van Voorhis notes, including creating a peer mentoring program for graduate students and establishing universal graduate student exit interviews to collect data for department-wide assessment and improvement.

At the Institute level, Shoulders has served on the Committee on Graduate Programs, Committee on Sexual Misconduct Prevention and Response (in which he co-chaired the provost's working group on the Faculty and Staff Sexual Misconduct Survey), and the Committee on Assessment of Biohazards and Embryonic Stem Cell Research Oversight, among other roles.

Shoulders graduated summa cum laude from Virginia Tech in 2004, earning a BS in chemistry with a minor in biochemistry. He earned a PhD in chemistry at the University of Wisconsin at Madison in 2009 under Professor Ronald Raines. Following an American Cancer Society Postdoctoral Fellowship at Scripps Research Institute, working with professors Jeffery Kelly and Luke Wiseman, Shoulders joined the MIT Department of Chemistry faculty as an assistant professor in 2012. Shoulders also serves as an associate member of the Broad Institute and an investigator at the Center for Musculoskeletal Research at Massachusetts General Hospital.

Among his many awards, Shoulders has received a NIH Director's New Innovator Award under the NIH High-Risk, High-Reward Research Program; an NSF CAREER Award; an American Cancer Society Research Scholar Award; the Camille Dreyfus Teacher-Scholar Award; and most recently the Ono Pharma Foundation Breakthrough Science Award.

Corporations are actively seeking sustainability advances in their supply chains — but many need to improve the business metrics they use in this area to realize more progress, according to a new report by MIT researchers.   

During a time of shifting policies globally and continued economic uncertainty, the survey-based report finds 85 percent of companies say they are continuing supply chain sustainability practices at the same level as in recent years, or are increasing those efforts.

“What we found is strong evidence that sustainability still matters,” says Josué Velázquez Martínez, a research scientist and director of the MIT Sustainable Supply Chain Lab, which helped produce the report. “There are many things that remain to be done to accomplish those goals, but there’s a strong willingness from companies in all parts of the world to do something about sustainability.”

The new analysis, titled “Sustainability Still Matters,” was released today. It is the sixth annual report on the subject prepared by the MIT Sustainable Supply Chain Lab, which is part of MIT’s Center for Transportation and Logistics. The Council of Supply Chain Management Professionals collaborated on the project as well.

The report is based on a global survey, with responses from 1,203 professionals in 97 countries. This year, the report analyzes three issues in depth, including regulations and the role they play in corporate approaches to supply chain management. A second core topic is management and mitigation of what industry professionals call “Scope 3” emissions, which are those not from a firm itself, but from a firm’s supply chain. And a third issue of focus is the future of freight transportation, which by itself accounts for a substantial portion of supply chain emissions.

Broadly, the survey finds that for European-based firms, the principal driver of action in this area remains government mandates, such as the Corporate Sustainability Reporting Directive, which requires companies to publish regular reports on their environmental impact and the risks to society involved. In North America, firm leadership and investor priorities are more likely to be decisive factors in shaping a company’s efforts.

“In Europe the pressure primarily comes more from regulation, but in the U.S. it comes more from investors, or from competitors,” Velázquez Martínez says.

The survey responses on Scope 3 emissions reveal a number of opportunities for improvement. In business and sustainability terms, Scope 1 greenhouse gas emissions are those a firm produces directly. Scope 2 emissions are the energy it has purchased. And Scope 3 emissions are those produced across a firm’s value chain, including the supply chain activities involved in producing, transporting, using, and disposing of its products.

The report reveals that about 40 percent of firms keep close track of Scope 1 and 2 emissions, but far fewer tabulate Scope 3 on equivalent terms. And yet Scope 3 may account for roughly 75 percent of total firm emissions, on aggregate. About 70 percent of firms in the survey say they do not have enough data from suppliers to accurately tabulate the total greenhouse gas and climate impact of their supply chains.

Certainly it can be hard to calculate the total emissions when a supply chain has many layers, including smaller suppliers lacking data capacity. But firms can upgrade their analytics in this area, too. For instance, 50 percent of North American firms are still using spreadsheets to tabulate emissions data, often making rough estimates that correlate emissions to simple economic activity. An alternative is life cycle assessment software that provides more sophisticated estimates of a product’s emissions, from the extraction of its materials to its post-use disposal. By contrast, only 32 percent of European firms are still using spreadsheets rather than life cycle assessment tools.

“You get what you measure,” Velázquez Martínez says. “If you measure poorly, you’re going to get poor decisions that most likely won’t drive the reductions you’re expecting. So we pay a lot of attention to that particular issue, which is decisive to defining an action plan. Firms pay a lot of attention to metrics in their financials, but in sustainability they’re often using simplistic measurements.”

When it comes to transportation, meanwhile, the report shows that firms are still grappling with the best ways to reduce emissions. Some see biofuels as the best short-term alternative to fossil fuels; others are investing in electric vehicles; some are waiting for hydrogen-powered vehicles to gain traction. Supply chains, after all, frequently involve long-haul trips. For firms, as for individual consumers, electric vehicles are more practical with a larger infrastructure of charging stations. There are advances on that front but more work to do as well.

That said, “Transportation has made a lot of progress in general,” Velázquez Martínez says, noting the increased acceptance of new modes of vehicle power in general.

Even as new technologies loom on the horizon, though, supply chain sustainability is not wholly depend on their introduction. One factor continuing to propel sustainability in supply chains is the incentives companies have to lower costs. In a competitive business environment, spending less on fossil fuels usually means savings. And firms can often find ways to alter their logistics to consume and spend less.

“Along with new technologies, there is another side of supply chain sustainability that is related to better use of the current infrastructure,” Velázquez Martínez observes. “There is always a need to revise traditional ways of operating to find opportunities for more efficiency.”