Steel is one of the most carbon-intensive industries, producing roughly 8 percent of energy sector emissions annually,

More than 1,800 people in North and South America have died this year from the mosquito-borne disease.

Tuesday's agreement with Norway outlines cooperation on green transportation, energy, agriculture and recycling.

It will support investments in early stage companies focused on renewable energy, biomanufacturing and rare mineral processing.

Over 4.75 inches of rainfall had soaked the United Arab Emirates — the typical average for a year in the desert nation — with more expected in the coming hours.

Water rationing is rare in Colombia's capital, which is located in the humid northern Andes Mountains and surrounded by cloud forests and emerald green fields.

Regulators will audit companies — including in the nation’s crucial mining and energy sectors — to ensure they are complying with regulations, officials said.

Using a pair of sensors made from carbon nanotubes, researchers from MIT and the Singapore-MIT Alliance for Research and Technology (SMART) have discovered signals that reveal when plans are experiencing stresses such as heat, light, or attack from insects or bacteria.

The sensors detect two signaling molecules that plants use to coordinate their response to stress: hydrogen peroxide and salicylic acid (a molecule similar to aspirin). The researchers found that plants produce these molecules at different timepoints for each type of stress, creating distinctive patterns that could serve as an early warning system.

Farmers could use these sensors to monitor potential threats to their crops, allowing them to intervene before the crops are lost, the researchers say.

“What we found is that these two sensors together can tell the user exactly what kind of stress the plant is undergoing. Inside the plant, in real time, you get chemical changes that rise and fall, and each one serves as a fingerprint of a different stress,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT and one of the senior authors of the study. Strano is also the co-lead principal investigator at the Disruptive and Sustainable Technologies for Agricultural Precision research group at SMART.

Sarojam Rajani, a senior principal investigator at the Temasek Life Sciences Laboratory in Singapore, is also a senior author of the paper, which appears in Nature Communications. The paper’s lead authors are Mervin Chun-Yi Ang, associate scientific director at SMART and Jolly Madathiparambil Saju, a research officer at Temasek Life Sciences Laboratory.

Sensing stress

Plants respond to different kinds of stress in different ways. In 2020, Strano’s lab developed a sensor that can detect hydrogen peroxide, which plant cells use as a distress signal when they are under attack from insects or encounter other stresses such as bacterial infection or too much light.

These sensors consist of tiny carbon nanotubes wrapped in polymers. By changing the three-dimensional structure of the polymers, the sensors can be tailored to detect different molecules, giving off a fluorescent signal when the target is present. For the new study, the researchers used this approach to develop a sensor that can detect salicylic acid, a molecule that is involved in regulating many aspects of plant growth, development, and response to stress.

To embed the nanosensors into plants, the researchers dissolve them in a solution, which is then applied to the underside of a plant leaf. The sensors can enter leaves through pores called stomata and take up residence in the mesophyll — the layer where most photosynthesis takes place. When a sensor is activated, the signal can be easily detecting using an infrared camera.

In this study, the researchers applied the sensors for hydrogen peroxide and salicylic acid to pak choi, a leafy green vegetable also known as bok choy or Chinese cabbage. Then, they exposed the plants to four different types of stress — heat, intense light, insect bites, and bacterial infection — and found that the plants generated distinctive responses to each type of stress.

Each type of stress led the plants to produce hydrogen peroxide within minutes, reaching maximum levels within an hour and then returning to normal. Heat, light, and bacterial infection all provoked salicylic acid production within two hours of the stimulus, but at distinct time points. Insect bites did not stimulate salicylic acid production at all.

The findings represent a “language” that plants use to coordinate their response to stress, Strano says. The hydrogen peroxide and salicylic acid waves trigger additional responses that help a plant survive whatever type of stress it’s facing.

For a stress such as an insect bite, this response includes the production of chemical compounds that insects don’t like, driving them away from the plant. Salicylic acid and hydrogen peroxide can also activate signaling pathways that turn on the production of proteins that help plants respond to heat and other stresses.

“Plants don't have a brain, they don't have a central nervous system, but they evolved to send different mixtures of chemicals, and that's how they communicate to the rest of the plant that it's getting too hot, or an insect predator is attacking,” Strano says.

Early warning

This technique is the first that can obtain real-time information from a plant, and the only one that can be applied to nearly any plant. Most existing sensors consist of fluorescent proteins that must be genetically engineered into a specific type of plant, such as tobacco or the common experimental plant Arabidopsis thaliana, and can’t be universally applied.

The researchers are now adapting these sensors to create sentinel plants that could be monitored to give farmers a much earlier warning when their crops are under stress. When plants don’t have enough water, for example, they eventually begin to turn brown, but by the time that happens, it’s usually too late to intervene.

“With climate change and the increasing population, there is a great need to understand better how plants respond and acclimate to stress, and also to engineer plants that are more tolerant to stress. The work reveals the interplay between H2O2, one of the most important reactive oxygen species in plants, and the hormone salicylic acid, which is widely involved in plants’ stress responses, therefore contributing to the mechanistic understanding of plants stress signaling,” says Eleni Stavrinidou, a senior associate professor of bioengineering at Linköping University in Sweden, who was not involved in the research.

This technology could also be used to develop systems that not only sense when plants are in distress but would also trigger a response such as altering the temperature or the amount of light in a greenhouse.

“We're incorporating this technology into diagnostics that can give farmers real-time information much faster than any other sensor can, and fast enough for them to intervene,” Strano says.

The researchers are also developing sensors that could be used to detect other plant signaling molecules, in hopes of learning more about their responses to stress and other stimuli.

The research was supported by the National Research Foundation of Singapore under its Campus for Research Excellence And Technological Enterprise (CREATE) program through SMART, and by the USDA National Institute of Food and Agriculture.

In a large, open space on the first floor of 750 Main Street in Cambridge, Massachusetts, a carbon-capture company is heating up molten salts to 600 degrees Celsius right next to a quantum computing company’s device for supercooling qubits. The difference is about 900 degrees across 15 feet.

It doesn’t take long in the tour of The Engine Accelerator to realize this isn’t your typical co-working space. Companies here are working at the extremes to develop new technologies with world-changing impact — what The Engine Accelerator’s leaders call “tough tech.”

Comprising four floors and 150,000 square feet next door to MIT’s campus, the new space offers startups specialized lab equipment, advanced machining, fabrication facilities, office space, and a range of startup support services.

The goal is to give young companies merging science and engineering all of the resources they need to move ideas from the lab bench to their own mass manufacturing lines.

“The infrastructure has always been a really important accelerant for getting these kinds of companies off and running,” The Engine Accelerator President Emily Knight says. “Now you can start a company and, on day one, start building. Real estate is such a big factor. Our thought was, let’s make this investment in the infrastructure for the founders. It’s an agile lease that enables them to be very flexible as they grow.”

Since the new facility opened its doors in the summer of 2022, the Accelerator has welcomed around 100 companies that employ close to 1,000 people. In addition to the space, members enjoy educational workshops on topics like fundraising and hiring, events, and networking opportunities that the Accelerator team hopes foster a sense of community among people working in the tough tech space overall.

“We’re not just advocates for the startups in the space,” Knight says. “We’re advocates for tough tech as a whole. We think it’s important for the state of Massachusetts to create a tough tech hub here, and we think it’s important for national competitiveness.”

Tough tech gets a home

The Engine was spun out of MIT in 2016 as a public benefit corporation with the mission of bridging the gap between discovery and commercialization. Since its inception, it has featured an investment component, now known as Engine Ventures, and a shared services component.

From the moment The Engine opened its doors to startups in its original headquarters on Massachusetts Avenue in Cambridge, the services team got a firsthand look at the unique challenges faced by tough tech startups. After speaking with founders, they realized their converted office space would need more power, stronger floors, and full lab accommodations.

The team rose to the challenge. They turned a closet into a bio lab. They turned an unused wellness room into a laser lab. They managed to accommodate Commonwealth Fusion Systems when the founders informed them a 5,000-pound magnet would soon arrive for testing.

But supporting ambitious founders in their quest to build world-changing companies was always going to require a bigger boat. As early as 2017, MIT’s leaders were considering turning the old Polaroid building, which had sat empty next to MIT’s campus for nearly 20 years, into the new home for tough tech.

Speaking of tough, construction crews began the extensive building renovations for the Accelerator at the end of 2019, a few months before the Covid-19 pandemic. The team managed to avoid the worst of the supply chain disruptions, but they quickly learned the building has its quirks. Each floor is a different ceiling height, and massive pillars known as mushroom columns punctuate each floor.

Based on conversations with founders, The Engine’s Accelerator team outfitted the renovated building with office and co-working space, a full machine shop, labs for biology and chemistry work, an array of 3D printers, bike storage, and, perhaps most important, cold brew on tap.

“I think of the Accelerator as a really great Airbnb host rather than a landlord, where maybe you rented a bedroom in a large house, but you feel like you rented the whole thing because you have access to all kinds of amazing equipment,” says Bernardo Cervantes PhD ’20, co-founder of Concerto Biosciences, which is developing microbes for a variety of uses in human health and agriculture.

The Engine Accelerator’s team credits MIT leadership with helping them manage the project, noting that the MIT Environment, Health and Safety office was particularly helpful.

A week after the Accelerator opened its doors in August 2022, on a single sweltering day, 35 companies moved in. By 2023, the Accelerator was home to 55 companies. Since then, the Accelerator’s team has done everything they could to continue to grow.

“At one point, one of our team members came to me with her tail between her legs and sheepishly said, ‘I gave our office space to a startup,’” Knight recalls. “I said, ‘Yes! That means you get it! We don’t need an office — we can sit anywhere.’”

The first floor holds some of the largest machinery, including that molten salt device (developed by Mantel Capture) and the quantum computer (developed by Atlantic Quantum). On the next level, a machine shop and a fabrication space featuring every 3D printer imaginable offer ways for companies to quickly build prototype products or parts. Another floor is dubbed “the Avenue” and features a kitchen and tables for networking and serendipitous meetings. The Avenue is lined by huge garage doors that open to accommodate larger crowds for workshops and meeting spaces.

“Even though the founders are working in different spaces, we wanted to create an area where people can connect and run into each other and get help with 3D printing or hiring or anything else,” Knight says. “It fosters those casual interactions that are very important for startups.”

An ecosystem to change the world

Only about one-fifth of the companies in the Accelerator space are portfolio companies of Engine Ventures. The two entities operate separately, but they pool their shared learning about supporting tough tech, and Engine Ventures has an office in the Accelerator’s space.

Engine Ventures CEO Katie Rae sees it as a symbiotic partnership.

“We needed to have all these robust services for everyone in tough tech, not just the portfolio companies,” Rae says. “We’ll always work together and produce the Tough Tech Summit together because of our overarching missions. It’s very much like a rising tide lifts all boats. All of these companies are working to change the world in their own verticals, so we’re just focusing on the impact they’re trying to have and making that the story.”

Rae says MIT has helped both of The Engine’s teams think through the best way to support tough tech startups.

“Being a partner with MIT, which understands innovation and safety better than anyone, has allowed us to say yes to more things and have more flexibility,” Rae says. “If you’re going to go at breakneck speed to solve global problems, you better have a mentality of getting things done fast and safely, and I think that’s been a core tenet of The Engine.”

Meanwhile, Knight says her team hasn’t stopped learning from the tough tech community and will continue to adapt.

“There’s just a waterfall of information coming from these companies,” Knight says. “It’s about iterating on our services to best support them, so we can go to people on our team and ask, ‘Can you learn to run this type of program, because we just learned these five founders need it?’ Every founder we know in the area has a badge so they can come in. We want to create a hub for tough tech within this Kendall Square area that’s already a hub in so many ways.”

Nature Climate Change, Published online: 17 April 2024; doi:10.1038/s41558-024-02003-4

Global projections of the economic impacts of climate change have usually focused on rising average temperatures. Now, two studies depict more complex and gloomier scenarios by incorporating variability in temperature and precipitation.

Nature Climate Change, Published online: 17 April 2024; doi:10.1038/s41558-024-01990-8

Existing global economic damage assessments only focus on the impacts induced by annual temperature changes. Including variability and extremes of temperature and precipitation in climate damage projections raises global gross domestic product losses and exacerbates global disparities of economic damage.

Data about potential voters—who they are, where they are, and how to reach them—is an extremely valuable commodity during an election year. And while the right to a secret ballot is a cornerstone of the democratic process, your personal information is gathered, used, and sold along the way. It's not possible to fully shield yourself from all this data processing, but you can take steps to at least minimize and understand it.

Political campaigns use the same invasive tricks that behavioral ads do—pulling in data from a variety of sources online to create a profile—so they can target you. Your digital trail is a critical tool for campaigns, but the process starts in the real world, where longstanding techniques to collect data about you can be useful indicators of how you'll vote. This starts with voter records.

Your IRL Voting Trail Is Still Valuable

Politicians have long had access to public data, like voter registration, party registration, address, and participation information (whether or not a voter voted, not who they voted for). Online access to such records has made them easier to get in some states, with unintended consequences, like doxing.

Campaigns can purchase this voter information from most states. These records provide a rough idea of whether that person will vote or not, and—if they're registered to a particular party—who they might lean toward voting for. Campaigns use this to put every voter into broad categories, like "supporter," "non-supporter," or "undecided." Campaigns gather such information at in-person events, too, like door-knocking and rallies, where you might sign up for emails or phone calls.

Campaigns also share information about you with other campaigns, so if you register with a candidate one year, it's likely that information goes to another in the future. For example, the website for Adam’s Schiff’s campaign to serve as U.S. Senator from California has a privacy policy with this line under “Sharing of Information”:

With organizations, candidates, campaigns, groups, or causes that we believe have similar political viewpoints, principles, or objectives or share similar goals and with organizations that facilitate communications and information sharing among such groups

Similar language can be found on other campaign sites, including those for Elizabeth Warren and Ted Cruz. These candidate lists are valuable, and are often shared within the national party. In 2017, the Hillary Clinton campaign gave its email list to the Democratic National Committee, a contribution valued at $3.5 million.

If you live in a state with citizen initiative ballot measures, data collected from signature sheets might be shared or used as well. Signing a petition doesn't necessarily mean you support the proposed ballot measure—it's just saying you think it deserves to be put on the ballot. But in most states, these signature pages will remain a part of the public record, and the information you provide may get used for mailings or other targeted political ads. 

How Those Voter Records, and Much More, Lead to Targeted Digital Ads

All that real world information is just one part of the puzzle these days. Political campaigns tap into the same intrusive adtech tracking systems used to deliver online behavioral ads. We saw a glimpse into how this worked after the Cambridge Analytica scandal, and the system has only grown since then.

Specific details are often a mystery, as a political advertising profile may be created by combining disparate information—from consumer scoring data brokers like Acxiom or Experian, smartphone data, and publicly available voter information—into a jumble of data points that’s often hard to trace in any meaningful way. A simplified version of the whole process might go something like this:

1. A campaign starts with its voter list, which includes names, addresses, and party affiliation. It may have purchased this from the state or its own national committee, or collected some of it for itself through a website or app.
2. The campaign then turns to a data broker to enhance this list with consumer information. The data broker combines the voter list with its own data, then creates a behavioral profile using inferences based on your shopping, hobbies, demographics, and more. The campaign looks this all over, then chooses some categories of people it thinks will be receptive to its messages in its various targeted ads.
3. Finally, the campaign turns to an ad targeting company to get the ad on your device. Some ad companies might use an IP address to target the ad to you. As The Markup revealed, other companies might target you based on your phone's location, which is particularly useful in reaching voters not in the campaign's files. 

In 2020, Open Secrets found political groups paid 37 different data brokers at least $23 million for access to services or data. These data brokers collect information from browser cookies, web beacons, mobile phones, social media platforms, and more. They found that some companies specialize in more general data, while others, like i360, TargetSmart, and Grassroots Analytics, focus on data useful to campaigns or advocacy.

A sample of some categories and inferences in a political data broker file that we received through a CCPA request shows the wide variety of assumptions these companies may make.

These political data brokers make a lot of promises to campaigns. TargetSmart claims to have 171 million highly accurate cell phone numbers, and i360 claims to have data on 220 million voters. They also tend to offer specialized campaign categories that go beyond the offerings of consumer-focused data brokers. Check out data broker L2’s “National Models & Predictive Analytics” page, which breaks down interests, demographics, and political ideology—including details like "Voter Fraud Belief," and "Ukraine Continue." The New York Times demonstrated a particularly novel approach to these sorts of profiles where a voter analytics firm created a “Covid concern score” by analyzing cell phone location, then ranked people based on travel patterns during the pandemic.

Some of these companies target based on location data. For example, El Toro claims to have once “identified over 130,000 IP-matched voter homes that met the client’s targeting criteria. El Toro served banner and video advertisements up to 3 times per day, per voter household – across all devices within the home.”

That “all devices within the home” claim may prove important in the coming elections: as streaming video services integrate more ad-based subscription tiers, that likely means more political ads this year. One company, AdImpact, projects $1.3 billion in political ad spending on “connected television” ads in 2024. This may be driven in part by the move away from tracking cookies, which makes web browsing data less appealing.

In the case of connected televisions, ads can also integrate data based on what you've watched, using information collected through automated content recognition (ACR). Streaming device maker and service provider Roku's pitch to potential political advertisers is straightforward: “there’s an opportunity for campaigns to use their own data like never before, for instance to reach households in a particular district where they need to get out the vote.” Roku claims to have at least 80 million users. As a platform for televisions and “streaming sticks,” and especially if you opted into ACR (we’ll detail how to check below), Roku can collect and use a lot of your viewing data ranging from apps, to broadcast TV, or even to video games.

This is vastly different from traditional broadcast TV ads, which might be targeted broadly based on a city or state, and the show being aired. Now, a campaign can target an ad at one household, but not their neighbor, even if they're watching the same show. Of the main streaming companies, only Amazon and Netflix don’t accept political ads.

Finally, there are Facebook and Google, two companies that have amassed a mountain of data points about all their users, and which allow campaigns to target based on some of those factors. According to at least one report, political ad spending on Google (mostly through YouTube) is projected to be $552 million, while Facebook is projected at $568 million. Unlike the data brokers discussed above, most of what you see on Facebook and Google is derived from the data collected by the company from its users. This may make it easier to understand why you’re seeing a political ad, for example, if you follow or view content from a specific politician or party, or about a specific political topic.

What You Can Do to Protect Your Privacy

Managing the flow of all this data might feel impossible, but you can take a few important steps to minimize what’s out there. The chances you’ll catch everything is low, but minimizing what is accessible is still a privacy win.

Install Privacy Badger
Considering how much data is collected just from your day-to-day web browsing, it’s a good idea to protect that first. The simplest way to do so is with our own tracking blocker extension, Privacy Badger.

Disable Your Phone Advertising ID and Audit Your Location Settings
Your phone has an ad identifier that makes it simple for advertisers to track and collate everything you do. Thankfully, you can make this much harder for those advertisers by disabling it:

• On iPhone: Head into Settings > Privacy & Security > Tracking, and make sure “Allow Apps to Request to Track” is disabled. 
• On Android: Open Settings > Security & Privacy > Privacy > Ads, and select “Delete advertising ID.”

Similarly, as noted above, your location is a valuable asset for campaigns. They can collect your location through data brokers, which usually get it from otherwise unaffiliated apps. This is why it's a good idea to limit what sorts of apps have access to your location:

• On iPhone: open Settings > Privacy & Security > Location Services, and disable access for any apps that do not need it. You can also set location for only "While using," for certain apps where it's helpful, but unnecessary to track you all the time. Also, consider disabling "Precise Location" for any apps that don't need your exact location (for example, your GPS navigation app needs precise location, but no weather app does).
• On Android: Open Settings > Location > App location permissions, and confirm that no apps are accessing your location that you don't want to. As with iOS, you can set it to "Allow only while using the app," for apps that don't need it all the time, and disable "Use precise location," for any apps that don't need exact location access.

Opt Out of Tracking on Your TV or Streaming Device, and Any Video Streaming Service
Nearly every brand of TV is connected to the internet these days. Consumer Reports has a guide for disabling what you can on most popular TVs and software platforms. If you use an Apple TV, you can disable the ad identifier following the exact same directions as on your phone.

Since the passage of a number of state privacy laws, streaming services, like other sites, have offered a way for users to opt out of the sale of their info. Many have extended this right outside of states that require it. You'll need to be logged into your streaming service account to take action on most of these, but TechHive has a list of opt out links for popular streaming services to get you started. Select the "Right to Opt Out" option, when offered.

Don't Click on Links in (or Respond to) Political Text Messages
You've likely been receiving political texts for much of the past year, and that's not going to let up until election day. It is increasingly difficult to decipher whether they're legitimate or spam, and with links that often use a URL shortener or odd looking domains, it's best not to click them. If there's a campaign you want to donate to, head directly to the site of the candidate or ballot sponsor.

Create an Alternate Email and Phone Number for Campaign Stuff
If you want to keep updated on campaign or ballot initiatives, consider setting up an email specifically for that, and nothing else. Since a phone number is also often required, it's a good idea to set up a secondary phone number for these same purposes (you can do so for free through services like Google Voice).

Keep an Eye Out for Deceptive Check Boxes
Speaking of signing up for updates, be mindful of when you don't intend to sign up for emails. Campaigns might use pre-selected options for everything from donation amounts to signing up for a newsletter. So, when you sign up with any campaign, keep an eye on any options you might not intend to opt into.

Mind Your Social Media
Now's a great time to take any sort of "privacy checkup" available on whatever social media platforms you use to help minimize any accidental data sharing. Even though you can't completely opt out of behavioral advertising on Facebook, review your ad preferences and opt out whatever you can. Also be sure to disable access to off-site activity. You should also opt out of personalized ads on Google's services. You cannot disable behavioral ads on TikTok, but the company doesn't allow political ads.

If you're curious to learn more about why you're seeing an ad to begin with, on Facebook you can always click the three-dot icon on an ad, then click "Why am I seeing this ad?" to learn more. For ads on YouTube, you can click the "More" button and then "About this advertiser" to see some information about who placed the ad. Anywhere else you see a Google ad you can click the "Adchoices" button and then "Why this ad?"

You shouldn't need to spend an afternoon jumping through opt out hoops and tweaking privacy settings on every device you own just so you're not bombarded with highly targeted ads. That’s why EFF supports comprehensive consumer data privacy legislation, including a ban on online behavioral ads.

Democracy works because we participate, and you should be able to do so without sacrificing your privacy. 

Lynn Hamadallah is a Syrian-Palestinian-French Psychologist based in London. An outspoken voice for the Palestinian cause, Lynn is interested in the ways in which narratives, spoken and unspoken, shape identity. Having lived in five countries and spent a lot of time traveling, she takes a global perspective on freedom of expression. Her current research project investigates how second-generation British-Arabs negotiate their cultural identity. Lynn works in a community mental health service supporting some of London's most disadvantaged residents, many of whom are migrants who have suffered extensive psychological trauma.

York: What does free speech or free expression mean to you? 

Being Arab and coming from a place where there is much more speech policing in the traditional sense, I suppose there is a bit of an idealization of Western values of free speech and democracy. There is this sense of freedom we grow up associating with the West. Yet recently, we’ve come to realize that the way it works in practice is quite different to the way it is described, and this has led to a lot of disappointment and disillusionment in the West and its ideals amongst Arabs. There’s been a lot of censorship for example on social media, which I’ve experienced myself when posting content in support of Palestine. At a national level, we have witnessed the dehumanization going on around protesters in the UK, which undermines the idea of free speech. For example, the pro-Palestine protests where we saw the then-Home Secretary Suella Braverman referring to protesters as “hate marchers.” So we’ve come to realize there’s this kind of veneer of free speech in the West which does not really match up to the more idealistic view of freedom we were taught about.

With the increased awareness we have gained as a result of the latest aggression going on in Palestine, actually what we’re learning is that free speech is just another arm of the West to support political and racist agendas. It’s one of those things that the West has come up with which only applies to one group of people and oppresses another. It’s the same as with human rights you know - human rights for who? Where are Palestinian’s human rights? 

We’ve seen free speech being weaponized to spread hate and desecrate Islam, for example, in the case of Charlie Hebdo and the Quran burning in Denmark and in Sweden. The argument put forward was that those cases represented instances of free speech rather than hate speech. But actually to millions of Muslims around the world those incidents were very, very hateful. They were acts of violence not just against their religious beliefs but right down to their sense of self. It’s humiliating to have a part of your identity targeted in that way with full support from the West, politicians and citizens alike. 

And then, when we— we meaning Palestinians and Palestine allies—want to leverage this idea of free speech to speak up against the oppression happening by the state of Israel, we see time and time again accusations flying around: hate speech, anti-semitism, and censorship. Heavy, heavy censorship everywhere. So that’s what I mean when I say that free speech in the West is a racist concept, actually. And I don’t know that true free speech exists anywhere in the world really. In the Middle East we don’t have democracies but at least there’s no veneer of democracy— the messaging and understanding is clear. Here, we have a supposed democracy, but in practice it looks very different. And that’s why, for me, I don’t really believe that free speech exists. I’ve never seen a real example of it. I think as long as people are power hungry there’s going to be violence, and as long as there’s violence, people are going to want to hide their crimes. And as long as people are trying to hide their crimes there’s not going to be free speech. Sorry for the pessimistic view!

York: It’s okay, I understand where you’re coming from. And I think that a lot of those things are absolutely true. Yet, from my perspective, I still think it’s a worthy goal even though governments—and organizationally we’ve seen this as well—a lot of times governments do try to abuse this concept. So I guess then I would just as a follow-up, do you feel that despite these issues that some form of universalized free expression is still a worthy ideal? 

Of course, I think it’s a worthy ideal. You know, even with social media – there is censorship. I’ve experienced it and it’s not just my word and an isolated incident. It’s been documented by Human Rights Watch—even Meta themselves! They did an internal investigation in 2021—Meta had a nonprofit called Business for Social Responsibility do an investigation and produce a report—and they’ve shown there was systemic censorship of Palestine-related content. And they’re doing it again now. That being said, I do think social media is making free speech more accessible, despite the censorship. 

And I think—to your question—free speech is absolutely worth pursuing. Because we see that despite these attempts at censorship, the truth is starting to come out. Palestine support is stronger than it’s ever been. To the point where we’ve now had South Africa take Israel to trial at the International Court of Justice for genocide, using evidence from social media videos that went viral. So what I’m saying is, free speech has the power to democratize demanding accountability from countries and creating social change, so yes, absolutely something we should try to pursue. 

York: You just mentioned two issues close to my heart. One is the issues around speech on social media platforms, and I’ve of course followed and worked on the Palestinian campaigns quite closely and I’m very aware of the BSR report. But also, video content, specifically, that’s found on social media being used in tribunals. So let me shift this question a bit. You have such a varied background around the world. I’m curious about your perspective over the past decade or decade and a half since social media has become so popular—how do you feel social media has shaped people’s views or their ability to advocate for themselves globally? 

So when we think about stories and narratives, something I’m personally interested in, we have to think about which stories get told and which stories remain untold. These stories and their telling is very much controlled by the mass media— BBC, CNN, and the like. They control the narrative. And I guess what social media is doing is it’s giving a voice to those who are often voiceless. In the past, the issue was that there was such a monopoly over mouthpieces. Mass  media were so trusted, to the point where no one would have paid attention to these alternative viewpoints. But what social media has done… I think it’s made people become more aware or more critical of mass media and how it shapes public opinion. There’s been a lot of exposure of their failure for example, like that video that went viral of Egyptian podcaster and activist Rahma Zain confronting CNN’s Clarissa Ward at the Rafah border about their biased reporting of the genocide in Palestine. I think that confrontation spoke to a lot of people. She was shouting “ You own the narrative, this is our problem. You own the narrative, you own the United Nations, you own Hollywood, you own all these mouthpieces— where are our voices?! Our voices need to be heard!” It was SO powerful and that video really spoke to the sentiment of many Arabs who have felt angry, betrayed and abandoned by the West’s ideals and their media reporting.

Social media is providing  a voice to more diverse people, elevating them and giving the public more control around narratives. Another example we’ve seen recently is around what’s currently happening in Sudan and the Democratic Republic of Congo. These horrific events and stories would never have had much of a voice or exposure before at the global stage. And now people all over the world are paying more attention and advocating for Sudanese and Congolese rights, thanks to social media. 

I personally was raised with quite a critical view of mass media, I think in my family there was a general distrust of the West, their policies and their media, so I never really relied personally on the media as this beacon of truth, but I do think that’s an exception. I think the majority of people rely on mass media as their source of truth. So social media plays an important role in keeping them accountable and diversifying narratives.

York: What are some of the biggest challenges you see right now anywhere in the world in terms of the climate for free expression for Palestinian and other activism? 

I think there’s two strands to it. There’s the social media strand. And there’s the governmental policies and actions. So I think on social media, again, it’s very documented, but it’s this kind of constant censorship. People want to be able to share content that matters to them, to make people more aware of global issues and we see time and time again viewership going down, content being deleted or reports from Meta of alleged hate speech or antisemitism. And that’s really hard. There’ve been random strategies that have popped up to increase social media engagement, like posting random content unrelated to Palestine or creating Instagram polls for example. I used to do that, I interspersed Palestine content with random polls like, “What’s your favorite color?” just to kind of break up the Palestine content and boost my engagement. And it was honestly so exhausting. It was like… I’m watching a genocide in real time, this is an attack on my people and now I’m having to come up with silly polls? Eventually I just gave up and accepted my viewership as it was, which was significantly lower.

At a government level, which is the other part of it, there’s this challenge of constant intimidation that we’re witnessing. I just saw recently there was a 17-year-old boy who was interviewed by the counterterrorism police at an airport because he was wearing a Palestinian flag. He was interrogated about his involvement in a Palestinian protest. When has protesting become a crime and what does that say about democratic rights and free speech here in the UK? And this is one example, but there are so many examples of policing, there was even talk of banning protests all together at one point. 

The last strand I’d include, actually, that I already touched on, is the mass media. Just recently we’ve seen the BBC reporting on the ICJ hearing, they showed the Israeli defense part, but they didn’t even show the South African side. So this censorship is literally in plain sight and poses a real challenge to the climate of free expression for Palestine activism.

York: Who is your free speech hero? 

Off the top of my head I’d probably say Mohammed El-Kurd. I think he’s just been so unapologetic in his stance. Not only that but I think he’s also made us think critically about this idea of narrative and what stories get told. I think it was really powerful when he was arguing the need to stop giving the West and mass media this power, and that we need to disempower them by ceasing to rely on them as beacons of truth, rather than working on changing them. Because, as he argues, oppressors who have monopolized and institutionalized violence will never ever tell the truth or hold themselves to account. Instead, we need to turn to Palestinians, and to brave cultural workers, knowledge producers, academics, journalists, activists, and social media commentators who understand the meaning of oppression and view them as the passionate, angry and, most importantly, reliable narrators that they are.

EFF is concerned that a new federal bill would freeze consumer data privacy protections in place, by preempting existing state laws and preventing states from creating stronger protections in the future. Federal law should be the floor on which states can build, not a ceiling.

We also urge the authors of the American Privacy Rights Act (APRA) to strengthen other portions of the bill. It should be easier to sue companies that violate our rights. The bill should limit sharing with the government and expand the definition of sensitive data. And it should narrow exceptions that allow companies to exploit our biometric information, our so-called “de-identified” data, and our data obtained in corporate “loyalty” schemes.

Despite our concerns with the APRA bill, we are glad Congress is pivoting the debate to a privacy-first approach to online regulation. Reining in companies’ massive collection, misuse, and transfer of everyone’s personal data should be the unifying goal of those who care about the internet. This debate has been absent at the federal level in the past year, giving breathing room to flawed bills that focus on censorship and content blocking, rather than privacy.

In general, the APRA would require companies to minimize their processing of personal data to what is necessary, proportionate, and limited to certain enumerated purposes. It would specifically require opt-in consent for the transfer of sensitive data, and most processing of biometric and genetic data. It would also give consumers the right to access, correct, delete, and export their data. And it would allow consumers to universally opt-out of the collection of their personal data from brokers, using a registry maintained by the Federal Trade Commission.

We welcome many of these privacy protections. Below are a few of our top priorities to correct and strengthen the APRA bill.

Allow States to Pass Stronger Privacy Laws

The APRA should not preempt existing and future state data privacy laws that are stronger than the current bill. The ability to pass stronger bills at the state and local level is an important tool in the fight for data privacy. We ask that Congress not compromise our privacy rights by undercutting the very state-level action that spurred this compromise federal data privacy bill in the first place.

Subject to exceptions, the APRA says that no state may “adopt, maintain, enforce, or continue in effect” any state-level privacy requirement addressed by the new bill. APRA would allow many state sectoral privacy laws to remain, but it would still preempt protections for biometric data, location data, online ad tracking signals, and maybe even privacy protections in state constitutions or some other limits on what private companies can share with the government. At the federal level, the APRA would also wrongly preempt many parts of the federal Communications Act, including provisions that limit a telephone company’s use, disclosure, and access to customer proprietary network information, including location information.

Just as important, it would prevent states from creating stronger privacy laws in the future. States are more nimble at passing laws to address new privacy harms as they arise, compared to Congress which has failed for decades to update important protections. For example, if lawmakers in Washington state wanted to follow EFF’s advice to ban online behavioral advertising or to allow its citizens to sue companies for not minimizing their collection of personal data (provisions where APRA falls short), state legislators would have no power to do so under the new federal bill.

Make It Easier for Individuals to Enforce Their Privacy Rights

The APRA should prevent coercive forced arbitration agreements and class action waivers, allow people to sue for statutory damages, and allow them to bring their case in state court. These rights would allow for rigorous enforcement and help force companies to prioritize consumer privacy.

The APRA has a private right of action, but it is a half-measure that still lets companies side-step many legitimate lawsuits. And the private right of action does not apply to some of the most important parts of the law, including the central data minimization requirement.

The favorite tool of companies looking to get rid of privacy lawsuits is to bury provision in their terms of service that force individuals into private arbitration and prevent class action lawsuits. The APRA does not address class action waivers and only prevents forced arbitration for children and people who allege “substantial” privacy harm. In addition, statutory damages and enforcement in state courts is essential, because many times federal courts still struggle to acknowledge privacy harm as real—relying instead on a cramped view that does not recognize privacy as a human right. In addition, the bill would allow companies to cure violations rather than face a lawsuit, incentivizing companies to skirt the law until they are caught.

Limit Exceptions for Sharing with the Government

APRA should close a loophole that may allow data brokers to sell data to the government and should require the government to obtain a court order before compelling disclosure of user data. This is important because corporate surveillance and government surveillance are often the same.

Under the APRA, government contractors do not have to follow the bill’s privacy protections. Those include any “entity that is collecting, processing, retaining, or transferring covered data on behalf of a Federal, State, Tribal, territorial, or local government entity, to the extent that such entity is acting as a service provider to the government entity.” Read broadly, this provision could protect data brokers who sell biometric information and location information to the government. In fact, Clearview AI previously argued it was exempt from Illinois’ strict biometric law using a similar contractor exception. This is a point that needs revision because other parts of the bill rightly prevent covered entities (government contractors excluded) from selling data to the government for the purpose of fraud detection, public safety, and criminal activity detection.

The APRA also allows entities to transfer personal data to the government pursuant to a “lawful warrant, administrative subpoena, or other form of lawful process.” EFF urges that the requirement be strengthened to at least a court order or warrant with prompt notice to the consumer. Protections like this are not unique, and it is especially important in the wake of the Dobbs decision.

Strengthen the Definition of Sensitive Data

The APRA has heightened protections for sensitive data, and it includes a long list of 18 categories of sensitive data, like: biometrics, precise geolocation, private communications, and an individual’s online activity overtime and across websites. This is a good list that can be added to. We ask Congress to add other categories, like immigration status, union membership, employment history, familial and social relationships, and any covered data processed in a way that would violate a person’s reasonable expectation of privacy. The sensitivity of data is context specific—meaning any data can be sensitive depending on how it is used. The bill should be amended to reflect that.

Limit Other Exceptions for Biometrics, De-identified Data, and Loyalty Programs

An important part of any bill is to make sure the exceptions do not swallow the rule. The APRA’s exceptions on biometric information, de-identified data, and loyalty programs should be narrowed.

In APRA, biometric information means data “generated from the measurement or processing of the individual’s unique biological, physical, or physiological characteristics that is linked or reasonably linkable to the individual” and excludes “metadata associated with a digital or physical photograph or an audio or video recording that cannot be used to identify an individual.” EFF is concerned this definition will not protect biometric information used for analysis of sentiment, demographics, and emotion, and could be used to argue hashed biometric identifiers are not covered.

De-identified data is excluded from the definition of personal data covered by the APRA, and companies and service providers can turn personal data into de-identified data to process it however they want. The problem with de-identified data is that many times it is not. Moreover, many people do not want their private data that they store in confidence with a company to then be used to improve that company’s product or train its algorithm—even if the data has purportedly been de-identified.

Many companies under the APRA can host loyalty programs and can sell that data with opt-in consent. Loyalty programs are a type of pay-for-privacy scheme that pressure people to surrender their privacy rights as if they were a commodity. Worse, because of our society’s glaring economic inequalities, these schemes will unjustly lead to a society of privacy “haves” and “have-nots.” At the very least, the bill should be amended to prevent companies from selling data that they obtain from a loyalty program.

We welcome Congress' privacy-first approach in the APRA and encourage the authors to improve the bill to ensure privacy is protected for generations to come.

Across the country, hundreds of thousands of drivers deliver packages and parcels to customers and companies each day, with many click-to-door times averaging only a few days. Coordinating a supply chain feat of this magnitude in a predictable and timely way is a longstanding problem of operations research, where researchers have been working to optimize the last leg of delivery routes. This is because the last phase of the process is often the costliest due to inefficiencies like long distances between stops due to increased ecommerce demand, weather delays, traffic, lack of parking availability, customer delivery preferences, or partially full trucks — inefficiencies that became more exaggerated and evident during the pandemic.

With newer technology and more individualized and nuanced data, researchers are able to develop models with better routing options but at the same time need to balance the computational cost of running them. Matthias Winkenbach, MIT principal research scientist, director of research for the MIT Center for Transportation and Logistics (CTL) and a researcher with the MIT-IBM Watson AI Lab, discusses how artificial intelligence could provide better and more computationally efficient solutions to a combinatorial optimization problem like this one.

Q: What is the vehicle routing problem, and how do traditional operations research (OR) methods address it?

A: The vehicle routing problem is faced by pretty much every logistics and delivery company like USPS, Amazon, UPS, FedEx, DHL every single day. Simply speaking, it's finding an efficient route that connects a set of customers that need to be either delivered to, or something needs to be picked up from them. It’s deciding which customers each of those vehicles — that you see out there on the road — should visit on a given day and in which sequence. Usually, the objective there is to find routes that lead to the shortest, or the fastest, or the cheapest route. But very often they are also driven by constraints that are specific to a customer. For instance, if you have a customer who has a delivery time window specified, or a customer on the 15th floor in the high-rise building versus the ground floor. This makes these customers more difficult to integrate into an efficient delivery route.

To solve the vehicle routing problem, we obviously we can't do our modeling without proper demand information and, ideally, customer-related characteristics. For instance, we need to know the size or weight of the packages ordered by a given customer, or how many units of a certain product need to be shipped to a certain location. All of this determines the time that you would need to service that particular stop. For realistic problems, you also want to know where the driver can park the vehicle safely. Traditionally, a route planner had to come up with good estimates for these parameters, so very often you find models and planning tools that are making blanket assumptions because there weren’t stop-specific data available.

Machine learning can be very interesting for this because nowadays most of the drivers have smartphones or GPS trackers, so there is a ton of information as to how long it takes to deliver a package. You can now, at scale, in a somewhat automated way, extract that information and calibrate every single stop to be modeled in a realistic way.

Using a traditional OR approach means you write up an optimization model, where you start by defining the objective function. In most cases that's some sort of cost function. Then there are a bunch of other equations that define the inner workings of a routing problem. For instance, you must tell the model that, if the vehicle visits a customer, it also needs to leave the customer again. In academic terms, that's usually called flow conservation. Similarly, you need to make sure that every customer is visited exactly once on a given route. These and many other real-world constraints together define what constitutes a viable route. It may seem obvious to us, but this needs to be encoded explicitly.

Once an optimization problem is formulated, there are algorithms out there that help us find the best possible solution; we refer to them as solvers. Over time they find solutions that comply with all the constraints. Then, it tries to find routes that are better and better, so cheaper and cheaper ones until you either say, "OK, this is good enough for me," or until it can mathematically prove that it found the optimal solution. The average delivery vehicle in a U.S. city makes about 120 stops. It can take a while to solve that explicitly, so that's usually not what companies do, because it's just too computationally expensive. Therefore, they use so-called heuristics, which are algorithms that are very efficient in finding reasonably good solutions but typically cannot quantify how far away these solutions are from the theoretical optimum.

Q: You’re currently applying machine learning to the vehicle routing problem. How are you employing it to leverage and possibly outperform traditional OR methods?

A: That's what we're currently working on with folks from the MIT-IBM Watson AI Lab. Here, the general idea is that you train a model on a large set of existing routing solutions that you either observed in a company’s real-world operations or that you generated using one of these efficient heuristics. In most machine-learning models, you no longer have an explicit objective function. Instead, you need to make the model understand what kind of problem it's actually looking at and what a good solution to the problem looks like. For instance, similar to training a large language model on words in a given language, you need to train a route learning model on the concept of the various delivery stops and their demand characteristics. Like understanding the inherent grammar of natural language, your model needs to understand how to connect these delivery stops in a way that results in a good solution — in our case, a cheap or fast solution. If you then throw a completely new set of customer demands at it, it will still be able to connect the dots quite literally in a way that you would also do if you were trying to find a good route to connect these customers.

For this, we're using model architectures that most people know from the language processing space. It seems a little bit counterintuitive because what does language processing have to do with routing? But actually, the properties of these models, especially transformer models, are good at finding structure in language — connecting words in a way that they form sentences. For instance, in a language, you have a certain vocabulary, and that's fixed. It's a discrete set of possible words that you can use, and the challenge is to combine them in a meaningful way. In routing, it's similar. In Cambridge there are like 40,000 addresses that you can visit. Usually, it's a subset of these addresses that need to be visited, and the challenge is: How do we combine this subset — these "words" — in a sequence that makes sense?

That's kind of the novelty of our approach — leveraging that structure that has proven to be extremely effective in the language space and bringing it into combinatorial optimization. Routing is just a great test bed for us because it's the most fundamental problem in the logistics industry. 

Of course, there are already very good routing algorithms out there that emerged from decades of operations research. What we are trying to do in this project is show that with a completely different, purely machine learning-based methodological approach, we are able to predict routes that are pretty much as good as, or better than, the routes that you would get from running a state-of-the-art route optimization heuristic.

Q: What advantages does a method like yours have over other state-of-the-art OR techniques?

A: Right now, the best methods are still very hungry in terms of computational resources that are required to train these models, but you can front-load some of this effort. Then, the trained model is relatively efficient in producing a new solution as it becomes required. 

Another aspect to consider is that the operational environment of a route, especially in cities, is constantly changing. The available road infrastructure, or traffic rules and speed limits might be altered, the ideal parking lot may be occupied by something else, or a construction site might block a road. With a pure OR-based approach, you might actually be in trouble because you would have to basically resolve the entire problem instantly once new information about the problem becomes available. Since the operational environment is dynamically changing, you would have to do this over and over again. While if you have a well-trained model that has seen similar issues before, it could potentially suggest the next-best route to take, almost instantaneously. It's more of a tool that would help companies to adjust to increasingly unpredictable changes in the environment.

Moreover, optimization algorithms are often manually crafted to solve the specific problem of a given company. The quality of the solutions obtained from such explicit algorithms is bounded by the level of detail and sophistication that went into the design of the algorithm. A learning-based model, on the other hand, continuously learns a routing policy from data. Once you have defined the model structure, a well-designed route learning model will distill potential improvements to your routing policy from the vast amount of routes it is being trained on. Simply put, a learning-based routing tool will continue to find improvements to your routes without you having to invest into explicitly designing these improvements into the algorithm.

Lastly, optimization-based methods are typically limited to optimizing for a very clearly defined objective function, which often seeks to minimize cost or maximize profits. In reality, the objectives that companies and drivers face are much more complex than that, and often they are also somewhat contradictory. For instance, a company wants to find efficient routes, but it also wants to have a low emissions footprint. The driver also wants to be safe and have a convenient way of serving these customers. On top of all of that, companies also care about consistency. A well-designed route learning model can eventually capture these high-dimensional objectives by itself, and that is something that you would never be able to achieve in the same way with a traditional optimization approach.

So, this is the kind of machine learning application that can actually have a tangible real-world impact in industry, on society, and on the environment. The logistics industry has problems that are much more complex than this. For instance, if you want to optimize an entire supply chain — let's say, the flow of a product from the manufacturer in China through the network of different ports around the world, through the distribution network of a big retailer in North America to your store where you actually buy it — there are so many decisions involved in that, which obviously makes it a much harder task than optimizing a single vehicle route. Our hope is that with this initial work, we can lay the foundation for research and also private sector development efforts to build tools that will eventually enable better end-to-end supply chain optimization.

The Federal Communications Commission (FCC) has released draft rules to reinstate net neutrality, with a vote on adopting the rules to come on the 25th of April. The FCC needs to close some loopholes in the draft rules before then.

Proposed Rules on Throttling and Prioritization Allow for the Circumvention of Net Neutrality

Net neutrality is the principle that all ISPs should treat all traffic coming over their networks without discrimination. The effect of this principle is that customers decide for themselves how they’d like to experience the internet. Violations of this principle include, but are not limited to, attempts to block, speed up, or slow down certain content as means of controlling traffic.

Net neutrality is critical to ensuring that the internet remains a vibrant place to learn, organize, speak, and innovate, and the FCC recognizes this. The draft mostly reinstates the bright-line rules of the landmark 2015 net neutrality protections to ban blocking, throttling, and paid prioritization.

It falls short, though, in a critical way: the FCC seems to think that it’s not okay to favor certain sites or services by slowing down other traffic, but it might be okay to favor them by giving them access to so-called fast lanes such as 5G network slices. First of all, in a world with a certain amount of finite bandwidth, favoring some traffic necessarily impairs other traffic. Secondly, the harms to speech and competition would be the same even if an ISP could conjure more bandwidth from thin air to speed up traffic from its business partners. Whether your access to Spotify is faster than your access to Bandcamp because Spotify is sped up or because Bandcamp is slowed down doesn’t matter because the end result is the same: Spotify is faster than Bandcamp and so you are incentivized to use Spotify over Bandcamp.

The loophole is especially bizarre because the 2015 FCC already got this right, and there has been bipartisan support for net neutrality proposals that explicitly encompass both favoring and disfavoring certain traffic. It’s a distinction that doesn’t make logical sense, doesn’t seem to have partisan significance, and could potentially undermine the rules in the event of a court challenge by drawing a nonsensical distinction between what’s forbidden under the bright-line rules versus what goes through the multi-factor test for other potentially discriminatory conduct by ISPs.

The FCC needs to close this loophole for unpaid prioritization of certain applications or classes of traffic. Customers should be in charge of what they do online, rather than ISPs deciding that, say, it’s more important to consume streaming entertainment products than to participate in video calls or that one political party’s websites should be served faster than another’s.

The FCC Should Clearly Rule Preemption to be a Floor, Not a Ceiling

When the FCC under the previous administration abandoned net neutrality protections in 2017 with the so-called “Restoring Internet Freedom” order, many states—chief among them California—stepped in to pass state net neutrality laws. Laws more protective than federal net neutrality protections—like California's should be explicitly protected by the new rule.

The FCC currently finds that California’s law “generally tracks [with] the federal rules[being] restored. (269)” It goes on to find that state laws are fine so long as they do not “interfere with or frustrate…federal rules,” are not “inconsistent,” or are not “incompatible.” It then reserves the right to revisit any state law if evidence arises that a state policy is found to “interfere or [be] incompatible.”

States should be able to build on federal laws to be more protective of rights, not run into limits to available protections. California’s net neutrality is in some places stronger than the draft rules. Where the FCC means to evaluate zero-rating, the practice of exempting certain data from a user’s data cap, on a case-by-case basis, California outright bans the practice of zero rating select apps.

There is no guarantee that a Commission which finds California to “generally track” today will do the same in two years time. The language as written unnecessarily sets a low bar for a future Commission to find California’s, and other states’, net neutrality laws to be preempted. It also leaves open unnecessary room for the large internet service providers (ISPs) to challenge California’s law once again. After all, when California’s law was first passed, it was immediately taken to court by these same ISPs and only after years of litigation did the courts reject the industry’s arguments and allow enforcement of this gold standard law to begin.

We urge the Commission to clearly state that, not only is California consistent with the FCC’s rules, but that on the issue of preemption the FCC considers its rules to be  the floor to build on, and that further state protections are not inconsistent simply because they may go further than the FCC chooses to.

Overall, the order is a great step for net neutrality. Its rules go a distance in protecting internet users. But we need clear rules recognizing that the creation of fast lanes via positive discrimination and unpaid prioritization are violations of net neutrality just the same, and assurance that states will continue to be free to protect their residents even when the FCC won’t.

Tell the FCC to Fix the Net Neutrality Rules:

1. Go to this link
2. For "Proceeding" put 23-320
3. Fill out the form
4. In "brief comments" register your thoughts on net neutrality. We recommend this, which you can copy and paste or edit for yourself:

Net neutrality is the principle that all internet service providers treat all traffic coming through their networks without discrimination. The effect of this principle is that customers decide for themselves how they’d like to experience the internet. The Commission’s rules as currently written leave open the door for positive discrimination of content, that is, the supposed creation of fast lanes where some content is sped up relative to others. This isn’t how the internet works, but in any case, whether an ISP is speeding up or slowing down content, the end result is the same: the ISP picks the winners and losers on the internet. As such the Commission must create bright line rules against all forms of discrimination, speeding up or slowing down, against apps or classes of apps on general traffic in the internet.

Further, while the Commission currently finds state net neutrality rules, like California’s, to not be preempted because they “generally track” its own rules, it makes it easy to rule otherwise at a future date. But just as we received net neutrality in 2015 only to have it taken away in 2017, there is no guarantee that the Commission will continue to find state net neutrality laws passed post-2017 to be consistent with the rules. To safeguard net neutrality, the Commission must find that California’s law is wholly consistent with their rules and that preemption is taken as a floor, not a ceiling, so that states can go above and beyond the federal standard without it being considered inconsistent with the federal rule.

Take Action

Tell the FCC to Fix the Net Neutrality Rules

When MIT professor and now Computer Science and Artificial Intelligence Laboratory (CSAIL) member Peter Shor first demonstrated the potential of quantum computers to solve problems faster than classical ones, he inspired scientists to imagine countless possibilities for the emerging technology. Thirty years later, though, the quantum edge remains a peak not yet reached.

Unfortunately, the technology of quantum computing isn’t fully operational yet. One major challenge lies in translating quantum algorithms from abstract mathematical concepts into concrete code that can run on a quantum computer. Whereas programmers for regular computers have access to myriad languages such as Python and C++ with constructs that align with standard classical computing abstractions, quantum programmers have no such luxury; few quantum programming languages exist today, and they are comparatively difficult to use because quantum computing abstractions are still in flux. In their recent work, MIT researchers highlight that this disparity exists because quantum computers don’t follow the same rules for how to complete each step of a program in order — an essential process for all computers called control flow — and present a new abstract model for a quantum computer that could be easier to program.

In a paper soon to be presented at the ACM Conference on Object-oriented Programming, Systems, Languages, and Applications, the group outlines a new conceptual model for a quantum computer, called a quantum control machine, that could bring us closer to making programs as easy to write as those for regular classical computers. Such an achievement would help turbocharge tasks that are impossible for regular computers to efficiently complete, like factoring large numbers, retrieving information in databases, and simulating how molecules interact for drug discoveries.

“Our work presents the principles that govern how you can and cannot correctly program a quantum computer,” says lead author and CSAIL PhD student Charles Yuan SM ’22. “One of these laws implies that if you try to program a quantum computer using the same basic instructions as a regular classical computer, you’ll end up turning that quantum computer into a classical computer and lose its performance advantage. These laws explain why quantum programming languages are tricky to design and point us to a way to make them better.”

Old school vs. new school computing

One reason why classical computers are relatively easier to program today is that their control flow is fairly straightforward. The basic ingredients of a classical computer are simple: binary digits or bits, a simple collection of zeros and ones. These ingredients assemble into the instructions and components of the computer’s architecture. One important component is the program counter, which locates the next instruction in a program much like a chef following a recipe, by recalling the next direction from memory. As the algorithm sequentially navigates through the program, a control flow instruction called a conditional jump updates the program counter to make the computer either advance forward to the next instruction or deviate from its current steps.

By contrast, the basic ingredient of a quantum computer is a qubit, which is a quantum version of a bit. This quantum data exists in a state of zero and one at the same time, known as a superposition. Building on this idea, a quantum algorithm can choose to execute a superposition of two instructions at the same time — a concept called quantum control flow.

The problem is that existing designs of quantum computers don’t include an equivalent of the program counter or a conditional jump. In practice, that means programmers typically implement control flow by manually arranging logical gates that describe the computer’s hardware, which is a tedious and error-prone procedure. To provide these features and close the gap with classical computers, Yuan and his coauthors created the quantum control machine — an instruction set for a quantum computer that works like the classical idea of a virtual machine. In their paper, the researchers envision how programmers could use this instruction set to implement quantum algorithms for problems such as factoring numbers and simulating chemical interactions.

As the technical crux of this work, the researchers prove that a quantum computer cannot support the same conditional jump instruction as a classical computer, and show how to modify it to work correctly on a quantum computer. Specifically, the quantum control machine features instructions that are all reversible — they can run both forward and backward in time. A quantum algorithm needs all instructions, including those for control flow, to be reversible so that it can process quantum information without accidentally destroying its superposition and producing a wrong answer.

The hidden simplicity of quantum computers

According to Yuan, you don’t need to be a physicist or mathematician to understand how this  futuristic technology works. Quantum computers don’t necessarily have to be arcane machines, he says, that require scary equations to understand. With the quantum control machine, the CSAIL team aims to lower the barrier to entry for people to interact with a quantum computer by raising the unfamiliar concept of quantum control flow to a level that mirrors the familiar concept of control flow in classical computers. By highlighting the dos and don’ts of building and programming quantum computers, they hope to educate people outside of the field about the power of quantum technology and its ultimate limits.

Still, the researchers caution that as is the case for many other designs, it’s not yet possible to directly turn their work into a practical hardware quantum computer due to the limitations of today’s qubit technology. Their goal is to develop ways of implementing more kinds of quantum algorithms as programs that make efficient use of a limited number of qubits and logic gates. Doing so would bring us closer to running these algorithms on the quantum computers that could come online in the near future.

“The fundamental capabilities of models of quantum computation has been a central discussion in quantum computation theory since its inception,” says MIT-IBM Watson AI Lab researcher Patrick Rall, who was not involved in the paper. “Among the earliest of these models are quantum Turing machines which are capable of quantum control flow. However, the field has largely moved on to the simpler and more convenient circuit model, for which quantum lacks control flow. Yuan, Villanyi, and Carbin successfully capture the underlying reason for this transition using the perspective of programming languages. While control flow is central to our understanding of classical computation, quantum is completely different! I expect this observation to be critical for the design of modern quantum software frameworks as hardware platforms become more mature.”

The paper lists two additional CSAIL members as authors: PhD student Ági Villányi ’21 and Associate Professor Michael Carbin. Their work was supported, in part, by the National Science Foundation and the Sloan Foundation.

What better way to commemorate Women's History Month and International Women's Day than to give  three of the world’s most accomplished scientists an opportunity to talk about their careers? On March 7, MindHandHeart invited professors Paula Hammond, Ann Graybiel, and Sangeeta Bhatia to share their career journeys, from the progress they have witnessed to the challenges they have faced as women in STEM. Their conversation was moderated by Mary Fuller, chair of the faculty and professor of literature. 

Hammond, an Institute professor with appointments in the Department of Chemical Engineering and the Koch Institute for Integrative Cancer Research, reflected on the strides made by women faculty at MIT, while acknowledging ongoing challenges. “I think that we have advanced a great deal in the last few decades in terms of the numbers of women who are present, although we still have a long way to go,” Hammond noted in her opening. “We’ve seen a remarkable increase over the past couple of decades in our undergraduate population here at MIT, and now we’re beginning to see it in the graduate population, which is really exciting.” Hammond was recently appointed to the role of vice provost for faculty.

Ann Graybiel, also an Institute professor, who has appointments in the Department of Brain and Cognitive Sciences and the McGovern Institute for Brain Research, described growing up in the Deep South. “Girls can’t do science,” she remembers being told in school, and they “can’t do research.” Yet her father, a physician scientist, often took her with him to work and had her assist from a young age, eventually encouraging her directly to pursue a career in science. Graybiel, who first came to MIT in 1973, noted that she continued to face barriers and rejection throughout her career long after leaving the South, but that individual gestures of inspiration, generosity, or simple statements of “You can do it” from her peers helped her power through and continue in her scientific pursuits. 

Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, director of the Marble Center for Cancer Nanomedicine at the Koch Institute for Integrative Cancer Research, and a member of the Institute for Medical Engineering and Science, is also the mother of two teenage girls. She shared her perspective on balancing career and family life: “I wanted to pick up my kids from school and I wanted to know their friends. … I had a vision for the life that I wanted.” Setting boundaries at work, she noted, empowered her to achieve both personal and professional goals. Bhatia also described her collaboration with President Emerita Susan Hockfield and MIT Amgen Professor of Biology Emerita Nancy Hopkins to spearhead the Future Founders Initiative, which aims to boost the representation of female faculty members pursuing biotechnology ventures.

A video of the full panel discussion is available on the MindHandHeart YouTube channel.

To save on fuel and reduce aircraft emissions, engineers are looking to build lighter, stronger airplanes out of advanced composites. These engineered materials are made from high-performance fibers that are embedded in polymer sheets. The sheets can be stacked and pressed into one multilayered material and made into extremely lightweight and durable structures.

But composite materials have one main vulnerability: the space between layers, which is typically filled with polymer “glue” to bond the layers together. In the event of an impact or strike, cracks can easily spread between layers and weaken the material, even though there may be no visible damage to the layers themselves. Over time, as these hidden cracks spread between layers, the composite could suddenly crumble without warning.

Now, MIT engineers have shown they can prevent cracks from spreading between composite’s layers, using an approach they developed called “nanostitching,” in which they deposit chemically grown microscopic forests of carbon nanotubes between composite layers. The tiny, densely packed fibers grip and hold the layers together, like ultrastrong Velcro, preventing the layers from peeling or shearing apart.

In experiments with an advanced composite known as thin-ply carbon fiber laminate, the team demonstrated that layers bonded with nanostitching improved the material’s resistance to cracks by up to 60 percent, compared with composites with conventional polymers. The researchers say the results help to address the main vulnerability in advanced composites.

“Just like phyllo dough flakes apart, composite layers can peel apart because this interlaminar region is the Achilles’ heel of composites,” says Brian Wardle, professor of aeronautics and astronautics at MIT. “We’re showing that nanostitching makes this normally weak region so strong and tough that a crack will not grow there. So, we could expect the next generation of aircraft to have composites held together with this nano-Velcro, to make aircraft safer and have greater longevity.”

Wardle and his colleagues have published their results today in the journal ACS Applied Materials and Interfaces. The study’s first author is former MIT visiting graduate student and postdoc Carolina Furtado, along with Reed Kopp, Xinchen Ni, Carlos Sarrado, Estelle Kalfon-Cohen, and Pedro Camanho.

Forest growth

At MIT, Wardle is director of the necstlab (pronounced “next lab”), where he and his group first developed the concept for nanostitching. The approach involves “growing” a forest of vertically aligned carbon nanotubes — hollow fibers of carbon, each so small that tens of billions of the the nanotubes can stand in an area smaller than a fingernail. To grow the nanotubes, the team used a process of chemical vapor deposition to react various catalysts in an oven, causing carbon to settle onto a surface as tiny, hair-like supports. The supports are eventually removed, leaving behind a densely packed forest of microscopic, vertical rolls of carbon.

The lab has previously shown that the nanotube forests can be grown and adhered to layers of composite material, and that this fiber-reinforced compound improves the material’s overall strength. The researchers had also seen some signs that the fibers can improve a composite’s resistance to cracks between layers.

In their new study, the engineers took a more in-depth look at the between-layer region in composites to test and quantify how nanostitching would improve the region’s resistance to cracks. In particular, the study focused on an advanced composite material known as thin-ply carbon fiber laminates.

“This is an emerging composite technology, where each layer, or ply, is about 50 microns thin, compared to standard composite plies that are 150 microns, which is about the diameter of a human hair. There’s evidence to suggest they are better than standard-thickness composites. And we wanted to see whether there might be synergy between our nanostitching and this thin-ply technology, since it could lead to more resilient aircraft, high-value aerospace structures, and space and military vehicles,” Wardle says.

Velcro grip

The study’s experiments were led by Carolina Furtado, who joined the effort as part of the MIT-Portugal program in 2016, continued the project as a postdoc, and is now a professor at the University of Porto in Portugal, where her research focuses on modeling cracks and damage in advanced composites.

In her tests, Furtado used the group’s techniques of chemical vapor deposition to grow densely packed forests of vertically aligned carbon nanotubes. She also fabricated samples of thin-ply carbon fiber laminates. The resulting advanced composite was about 3 millimeters thick and comprised 60 layers, each made from stiff, horizontal fibers embedded in a polymer sheet.

She transferred and adhered the nanotube forest in between the two middle layers of the composite, then cooked the material in an autoclave to cure. To test crack resistance, the researchers placed a crack on the edge of the composite, right at the start of the region between the two middle layers.

“In fracture testing, we always start with a crack because we want to test whether and how far the crack will spread,” Furtado explains.

The researchers then placed samples of the nanotube-reinforced composite in an experimental setup to test their resilience to “delamination,” or the potential for layers to separate.

“There’s lots of ways you can get precursors to delamination, such as from impacts, like tool drop, bird strike, runway kickup in aircraft, and there could be almost no visible damage, but internally it has a delamination,” Wardle says. “Just like a human, if you’ve got a hairline fracture in a bone, it’s not good. Just because you can’t see it doesn’t mean it’s not impacting you. And damage in composites is hard to inspect.”

To examine nanostitching’s potential to prevent delamination, the team placed their samples in a setup to test three delamination modes, in which a crack could spread through the between-layer region and peel the layers apart or cause them to slide against each other, or do a combination of both. All three of these modes are the most common ways in which conventional composites can internally flake and crumble.

The tests, in which the researchers precisely measured the force required to peel or shear the composite’s layers, revealed that the nanostitched held fast, and the initial crack that the researchers made was unable to spread further between the layers. The nanostitched samples were up to 62 percent tougher and more resistant to cracks, compared with the same advanced composite material that was held together with conventional polymers.

“This is a new composite technology, turbocharged by our nanotubes,” Wardle says.

“The authors have demonsrated that thin plies and nanostitching together have made significant increase in toughness,” says Stephen Tsai, emeritus professor of aeronautics and astronautics at Stanford University. “Composites are degraded by their weak interlaminar strength. Any improvement shown in this work will increase the design allowable, and reduce the weight and cost of composites technology.”

The researchers envision that any vehicle or structure that incorporates conventional composites could be made lighter, tougher, and more resilient with nanostitching.

“You could have selective reinforcement of problematic areas, to reinforce holes or bolted joints, or places where delamination might happen,” Furtado says. “This opens a big window of opportunity.”

Brian Krebs reported that X (formerly known as Twitter) started automatically changing twitter.com links to x.com links. The problem is: (1) it changed any domain name that ended with “twitter.com,” and (2) it only changed the link’s appearance (anchortext), not the underlying URL. So if you were a clever phisher and registered fedetwitter.com, people would see the link as fedex.com, but it would send people to fedetwitter.com.

Thankfully, the problem has been fixed.