Laila Soueif has now been on hunger strike for 245 days. On Thursday night, she was taken to the hospital once again. Soueif’s hunger strike is a powerful act of protest against the failures of two governments. The Egyptian government continues to deny basic justice by keeping her son, Alaa Abd el-Fattah, behind bars—his only “crime” was sharing a Facebook post about the torture of a fellow detainee. Meanwhile, the British government, despite Alaa’s citizenship, has failed to secure even a single consular visit. Its muted response reflects an unacceptable unwillingness to stand up for the rights of its own citizens.

This is the second time this year that Soueif’s health has collapsed due to her hunger strike. Now, her condition is dire. Her blood sugar is dangerously low, and every day, her family fears it could be her last. Doctors say it’s a miracle she’s still alive.

Her protest is a call for accountability—a demand that both governments uphold the rule of law and protect human rights, not only in rhetoric, but through action.

Late last week, after an 18-month investigation, the United Nations Working Group on Arbitrary Detention (UNWGAD) issued its Opinion on Abd el-Fattah’s case, stating that he is being held unlawfully by the Egyptian government. That Egypt will not provide the United Kingdom with consular access to its citizen further violates the country’s obligations under international law. 

As stated in a letter to British Prime Minister Keir Starmer by 21 organizations, including EFF, the UK must now use every tool it has at its disposal to ensure that Alaa Abd el-Fattah is released immediately.

This spring, 25 MIT students and a postdoc traveled to Washington, where they met with congressional offices to advocate for federal science funding and specific, science-based policies based on insights from their research on pressing issues — including artificial intelligence, health, climate and ocean science, energy, and industrial decarbonization. Organized annually by the Science Policy Initiative (SPI), this year’s trip came at a particularly critical moment, as science agencies are facing unprecedented funding cuts.

Over the course of two days, the group met with 66 congressional offices across 35 states and select committees, advocating for stable funding for science agencies such as the Department of Energy, the National Oceanic and Atmospheric Administration, the National Science Foundation, NASA, and the Department of Defense.

Congressional Visit Days (CVD), organized by SPI, offer students and researchers a hands-on introduction to federal policymaking. In addition to meetings on Capitol Hill, participants connected with MIT alumni in government and explored potential career paths in science policy.

This year’s trip was co-organized by Mallory Kastner, a PhD student in biological oceanography at MIT and Woods Hole Oceanographic Institution (WHOI), and Julian Ufert, a PhD student in chemical engineering at MIT. Ahead of the trip, participants attended training sessions hosted by SPI, the MIT Washington Office, and the MIT Policy Lab. These sessions covered effective ways to translate scientific findings into policy, strategies for a successful advocacy meeting, and hands-on demos of a congressional meeting.

Participants then contacted their representatives’ offices in advance and tailored their talking points to each office’s committees and priorities. This structure gave participants direct experience initiating policy conversations with those actively working on issues they cared about.

Audrey Parker, a PhD student in civil and environmental engineering studying methane abatement, emphasizes the value of connecting scientific research with priorities in Congress: “Through CVD, I had the opportunity to contribute to conversations on science-backed solutions and advocate for the role of research in shaping policies that address national priorities — including energy, sustainability, and climate change.”

To many of the participants, stepping into the shoes of a policy advisor was a welcome diversion from their academic duties and scientific routine. For Alex Fan, an undergraduate majoring in electrical engineering and computer science, the trip was enlightening: “It showed me that student voices really do matter in shaping science policy. Meeting with lawmakers, especially my own representative, Congresswoman Bonamici, made the experience personal and inspiring. It has made me seriously consider a future at the intersection of research and policy.”

“I was truly impressed by the curiosity and dedication of our participants, as well as the preparation they brought to each meeting,” says Ufert. “It was inspiring to watch them grow into confident advocates, leveraging their experience as students and their expertise as researchers to advise on policy needs.”

Kastner adds: “It was eye-opening to see the disconnect between scientists and policymakers. A lot of knowledge we generate as scientists rarely makes it onto the desk of congressional staff, and even more rarely onto the congressperson’s. CVD was an incredibly empowering experience for me as a scientist — not only am I more motivated to broaden my scientific outreach to legislators, but I now also have the skills to do so.”

Funding is the bedrock that allows scientists to carry out research and make discoveries. In the United States, federal funding for science has enabled major technological breakthroughs and advancements in manufacturing and other industrial sectors, and led to important environmental protection standards. While participants found the degree of support for science funding variable among offices from across the political spectrum, they were reassured by the fact that many offices on both sides of the aisle still recognized the significance of science. 

When you’re trying to communicate or understand ideas, words don’t always do the trick. Sometimes the more efficient approach is to do a simple sketch of that concept — for example, diagramming a circuit might help make sense of how the system works.

But what if artificial intelligence could help us explore these visualizations? While these systems are typically proficient at creating realistic paintings and cartoonish drawings, many models fail to capture the essence of sketching: its stroke-by-stroke, iterative process, which helps humans brainstorm and edit how they want to represent their ideas.

A new drawing system from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Stanford University can sketch more like we do. Their method, called “SketchAgent,” uses a multimodal language model — AI systems that train on text and images, like Anthropic’s Claude 3.5 Sonnet — to turn natural language prompts into sketches in a few seconds. For example, it can doodle a house either on its own or through collaboration, drawing with a human or incorporating text-based input to sketch each part separately.

The researchers showed that SketchAgent can create abstract drawings of diverse concepts, like a robot, butterfly, DNA helix, flowchart, and even the Sydney Opera House. One day, the tool could be expanded into an interactive art game that helps teachers and researchers diagram complex concepts or give users a quick drawing lesson.

CSAIL postdoc Yael Vinker, who is the lead author of a paper introducing SketchAgent, notes that the system introduces a more natural way for humans to communicate with AI.

“Not everyone is aware of how much they draw in their daily life. We may draw our thoughts or workshop ideas with sketches,” she says. “Our tool aims to emulate that process, making multimodal language models more useful in helping us visually express ideas.”

SketchAgent teaches these models to draw stroke-by-stroke without training on any data — instead, the researchers developed a “sketching language” in which a sketch is translated into a numbered sequence of strokes on a grid. The system was given an example of how things like a house would be drawn, with each stroke labeled according to what it represented — such as the seventh stroke being a rectangle labeled as a “front door” — to help the model generalize to new concepts.

Vinker wrote the paper alongside three CSAIL affiliates — postdoc Tamar Rott Shaham, undergraduate researcher Alex Zhao, and MIT Professor Antonio Torralba — as well as Stanford University Research Fellow Kristine Zheng and Assistant Professor Judith Ellen Fan. They’ll present their work at the 2025 Conference on Computer Vision and Pattern Recognition (CVPR) this month.

Assessing AI’s sketching abilities

While text-to-image models such as DALL-E 3 can create intriguing drawings, they lack a crucial component of sketching: the spontaneous, creative process where each stroke can impact the overall design. On the other hand, SketchAgent’s drawings are modeled as a sequence of strokes, appearing more natural and fluid, like human sketches.

Prior works have mimicked this process, too, but they trained their models on human-drawn datasets, which are often limited in scale and diversity. SketchAgent uses pre-trained language models instead, which are knowledgeable about many concepts, but don’t know how to sketch. When the researchers taught language models this process, SketchAgent began to sketch diverse concepts it hadn’t explicitly trained on.

Still, Vinker and her colleagues wanted to see if SketchAgent was actively working with humans on the sketching process, or if it was working independently of its drawing partner. The team tested their system in collaboration mode, where a human and a language model work toward drawing a particular concept in tandem. Removing SketchAgent’s contributions revealed that their tool’s strokes were essential to the final drawing. In a drawing of a sailboat, for instance, removing the artificial strokes representing a mast made the overall sketch unrecognizable.

In another experiment, CSAIL and Stanford researchers plugged different multimodal language models into SketchAgent to see which could create the most recognizable sketches. Their default backbone model, Claude 3.5 Sonnet, generated the most human-like vector graphics (essentially text-based files that can be converted into high-resolution images). It outperformed models like GPT-4o and Claude 3 Opus.

“The fact that Claude 3.5 Sonnet outperformed other models like GPT-4o and Claude 3 Opus suggests that this model processes and generates visual-related information differently,” says co-author Tamar Rott Shaham.

She adds that SketchAgent could become a helpful interface for collaborating with AI models beyond standard, text-based communication. “As models advance in understanding and generating other modalities, like sketches, they open up new ways for users to express ideas and receive responses that feel more intuitive and human-like,” says Shaham. “This could significantly enrich interactions, making AI more accessible and versatile.”

While SketchAgent’s drawing prowess is promising, it can’t make professional sketches yet. It renders simple representations of concepts using stick figures and doodles, but struggles to doodle things like logos, sentences, complex creatures like unicorns and cows, and specific human figures.

At times, their model also misunderstood users’ intentions in collaborative drawings, like when SketchAgent drew a bunny with two heads. According to Vinker, this may be because the model breaks down each task into smaller steps (also called “Chain of Thought” reasoning). When working with humans, the model creates a drawing plan, potentially misinterpreting which part of that outline a human is contributing to. The researchers could possibly refine these drawing skills by training on synthetic data from diffusion models.

Additionally, SketchAgent often requires a few rounds of prompting to generate human-like doodles. In the future, the team aims to make it easier to interact and sketch with multimodal language models, including refining their interface. 

Still, the tool suggests AI could draw diverse concepts the way humans do, with step-by-step human-AI collaboration that results in more aligned final designs.

This work was supported, in part, by the U.S. National Science Foundation, a Hoffman-Yee Grant from the Stanford Institute for Human-Centered AI, the Hyundai Motor Co., the U.S. Army Research Laboratory, the Zuckerman STEM Leadership Program, and a Viterbi Fellowship.

The Hertz Foundation announced that it has awarded fellowships to eight MIT affiliates. The prestigious award provides each recipient with five years of doctoral-level research funding (up to a total of $250,000), which gives them an unusual measure of independence in their graduate work to pursue groundbreaking research.

The MIT-affiliated awardees are Matthew Caren ’25; April Qiu Cheng ’24; Arav Karighattam, who begins his PhD at the Institute this fall; Benjamin Lou ’25; Isabelle A. Quaye ’22, MNG ’24; Albert Qin ’24; Ananthan Sadagopan ’24; and Gianfranco (Franco) Yee ’24.

“Hertz Fellows embody the promise of future scientific breakthroughs, major engineering achievements and thought leadership that is vital to our future,” said Stephen Fantone, chair of the Hertz Foundation board of directors and president and CEO of Optikos Corp., in the announcement. “The newest recipients will direct research teams, serve in leadership positions in our government and take the helm of major corporations and startups that impact our communities and the world.”

In addition to funding, fellows receive access to Hertz Foundation programs throughout their lives, including events, mentoring, and networking. They join the ranks of over 1,300 former Hertz Fellows since the fellowship was established in 1963 who are leaders and scholars in a range of technology, science, and engineering fields. Former fellows have contributed to breakthroughs in such areas as advanced medical therapies, computational systems used by billions of people daily, global defense networks, and the recent launch of the James Webb Space Telescope.

This year’s MIT recipients are among a total of 19 Hertz Foundation Fellows scholars selected from across the United States.

Matthew Caren ’25 studied electrical engineering and computer science, mathematics, and music at MIT. His research focuses on computational models of how people use their voices to communicate sound at the Computer Science and Artificial Intelligence Lab (CSAIL) and interpretable real-time machine listening systems at the MIT Music Technology Lab. He spent several summers developing large language model systems and bioinformatics algorithms at Apple and a year researching expressive digital instruments at Stanford University’s Center for Computer Research in Music and Acoustics. He chaired the MIT Schwarzman College of Computing Undergraduate Advisory Group, where he led undergraduate committees on interdisciplinary computing AI and was a founding member of the MIT Voxel Lab for music and arts technology. In addition, Caren has invented novel instruments used by Grammy-winning musicians on international stages. He plans to pursue a doctorate at Stanford.

April Qiu Cheng ’24 majored in physics at MIT, graduating in just three years. Their research focused on black hole phenomenology, gravitational-wave inference, and the use of fast radio bursts as a statistical probe of large-scale structure. They received numerous awards, including an MIT Outstanding Undergraduate Research Award, the MIT Barrett Prize, the Astronaut Scholarship, and the Princeton President’s Fellowship. Cheng contributed to the physics department community by serving as vice president of advocacy for Undergraduate Women in Physics and as the undergraduate representative on the Physics Values Committee. In addition, they have participated in various science outreach programs for middle and high school students. Since graduating, they have been a Fulbright Fellow at the Max Planck Institute for Gravitational Physics, where they have been studying gravitational-wave cosmology. Cheng will begin a doctorate in astrophysics at Princeton in the fall.

Arav Karighattam was home schooled, and by age 14 had completed most of the undergraduate and graduate courses in physics and mathematics at the University of California at Davis. He graduated from Harvard University in 2024 with a bachelor’s degree in mathematics and will attend MIT to pursue a PhD, also in mathematics. Karighattam is fascinated by algebraic number theory and arithmetic geometry and seeks to understand the mysteries underlying the structure of solutions to Diophantine equations. He also wants to apply his mathematical skills to mitigating climate change and biodiversity loss. At a recent conference at MIT titled “Mordell’s Conjecture 100 Years Later,” Karighattam distinguished himself as the youngest speaker to present a paper among graduate students, postdocs, and faculty members.

Benjamin Lou ’25 graduated from MIT in May with a BS in physics and is interested in finding connections between fundamental truths of the universe. One of his research projects applies symplectic techniques to understand the nature of precision measurements using quantum states of light. Another is about geometrically unifying several theorems in quantum mechanics using the Prüfer transformation. For his work, Lou was honored with the Barry Goldwater Scholarship. Lou will pursue his doctorate at MIT, where he plans to work on unifying quantum mechanics and gravity, with an eye toward uncovering experimentally testable predictions. Living with the debilitating disease spinal muscular atrophy, which causes severe, full-body weakness and makes scratchwork unfeasible, Lou has developed a unique learning style emphasizing mental visualization. He also co-founded and helped lead the MIT Assistive Technology Club, dedicated to empowering those with disabilities using creative technologies. He is working on a robotic self-feeding device for those who cannot eat independently.

Isabelle A. Quaye ’22, MNG ’24 studied electrical engineering and computer science as an undergraduate at MIT, with a minor in economics. She was awarded competitive fellowships and scholarships from Hyundai, Intel, D. E. Shaw, and Palantir, and received the Albert G. Hill Prize, given to juniors and seniors who have maintained high academic standards and have made continued contributions to improving the quality of life for underrepresented students at MIT. While obtaining her master’s degree at MIT, she focused on theoretical computer science and systems. She is currently a software engineer at Apple, where she continues to develop frameworks that harness intelligence from data to improve systems and processes. Quaye also believes in contributing to the advancement of science and technology through teaching and has volunteered in summer programs to teach programming and informatics to high school students in the United States and Ghana.

Albert Qin ’24 majored in physics and mathematics at MIT. He also pursued an interest in biology, researching single-molecule approaches to study transcription factor diffusion in living cells and studying the cell circuits that control animal development. His dual interests have motivated him to find common ground between physics and biological fields. Inspired by his MIT undergraduate advisors, he hopes to become a teacher and mentor for aspiring young scientists. Qin is currently pursuing a PhD at Princeton University, addressing questions about the behavior of neural networks — both artificial and biological — using a variety of approaches and ideas from physics and neuroscience.

Ananthan Sadagopan ’24 is currently pursuing a doctorate in biological and biomedical science at Harvard University, focusing on chemical biology and the development of new therapeutic strategies for intractable diseases. He earned his BS at MIT in chemistry and biology in three years and led projects characterizing somatic perturbations of X chromosome inactivation in cancer, developing machine learning tools for cancer dependency prediction, using small molecules for targeted protein relocalization and creating a generalizable strategy to drug the most mutated gene in cancer (TP53). He published as the first author in top journals, such as Cell, during his undergraduate career. He also holds patents related to his work on cancer dependency prediction and drugging TP53. While at the Institute, he served as president of the Chemistry Undergraduate Association, winning both the First-Year and Senior Chemistry Achievement Awards, and was head of the events committee for the MIT Science Olympiad.

Gianfranco (Franco) Yee ’24 majored in biological engineering at MIT, conducting research in the Manalis Lab on chemical gradients in the gut microenvironment and helping to develop a novel gut-on-a-chip platform for culturing organoids under these gradients. His senior thesis extended this work to the microbiome, investigating host-microbe interactions linked to intestinal inflammation and metabolic disorders. Yee also earned a concentration in education at MIT, and is committed to increasing access to STEM resources in underserved communities. He co-founded Momentum AI, an educational outreach program that teaches computer science to high school students across Greater Boston. The inaugural program served nearly 100 students and included remote outreach efforts in Ukraine and China. Yee has also worked with MIT Amphibious Achievement and the MIT Office of Engineering Outreach Programs. He currently attends Gerstner Sloan Kettering Graduate School, where he plans to leverage the gut microbiome and immune system to develop innovative therapeutic treatments.

Former Hertz Fellows include two Nobel laureates; recipients of 11 Breakthrough Prizes and three MacArthur Foundation “genius awards;” and winners of the Turing Award, the Fields Medal, the National Medal of Technology, the National Medal of Science, and the Wall Street Journal Technology Innovation Award. In addition, 54 are members of the National Academies of Sciences, Engineering and Medicine, and 40 are fellows of the American Association for the Advancement of Science. Hertz Fellows hold over 3,000 patents, have founded more than 375 companies, and have created hundreds of thousands of science and technology jobs.

Every year, thousands of students take courses that teach them how to deploy artificial intelligence models that can help doctors diagnose disease and determine appropriate treatments. However, many of these courses omit a key element: training students to detect flaws in the training data used to develop the models.

Leo Anthony Celi, a senior research scientist at MIT’s Institute for Medical Engineering and Science, a physician at Beth Israel Deaconess Medical Center, and an associate professor at Harvard Medical School, has documented these shortcomings in a new paper and hopes to persuade course developers to teach students to more thoroughly evaluate their data before incorporating it into their models. Many previous studies have found that models trained mostly on clinical data from white males don’t work well when applied to people from other groups. Here, Celi describes the impact of such bias and how educators might address it in their teachings about AI models.

Q: How does bias get into these datasets, and how can these shortcomings be addressed?

A: Any problems in the data will be baked into any modeling of the data. In the past we have described instruments and devices that don’t work well across individuals. As one example, we found that pulse oximeters overestimate oxygen levels for people of color, because there weren’t enough people of color enrolled in the clinical trials of the devices. We remind our students that medical devices and equipment are optimized on healthy young males. They were never optimized for an 80-year-old woman with heart failure, and yet we use them for those purposes. And the FDA does not require that a device work well on this diverse of a population that we will be using it on. All they need is proof that it works on healthy subjects.

Additionally, the electronic health record system is in no shape to be used as the building blocks of AI. Those records were not designed to be a learning system, and for that reason, you have to be really careful about using electronic health records. The electronic health record system is to be replaced, but that’s not going to happen anytime soon, so we need to be smarter. We need to be more creative about using the data that we have now, no matter how bad they are, in building algorithms.

One promising avenue that we are exploring is the development of a transformer model of numeric electronic health record data, including but not limited to laboratory test results. Modeling the underlying relationship between the laboratory tests, the vital signs and the treatments can mitigate the effect of missing data as a result of social determinants of health and provider implicit biases.

Q: Why is it important for courses in AI to cover the sources of potential bias? What did you find when you analyzed such courses’ content?

A: Our course at MIT started in 2016, and at some point we realized that we were encouraging people to race to build models that are overfitted to some statistical measure of model performance, when in fact the data that we’re using is rife with problems that people are not aware of. At that time, we were wondering: How common is this problem?

Our suspicion was that if you looked at the courses where the syllabus is available online, or the online courses, that none of them even bothers to tell the students that they should be paranoid about the data. And true enough, when we looked at the different online courses, it’s all about building the model. How do you build the model? How do you visualize the data? We found that of 11 courses we reviewed, only five included sections on bias in datasets, and only two contained any significant discussion of bias.

That said, we cannot discount the value of these courses. I’ve heard lots of stories where people self-study based on these online courses, but at the same time, given how influential they are, how impactful they are, we need to really double down on requiring them to teach the right skillsets, as more and more people are drawn to this AI multiverse. It’s important for people to really equip themselves with the agency to be able to work with AI. We’re hoping that this paper will shine a spotlight on this huge gap in the way we teach AI now to our students.

Q: What kind of content should course developers be incorporating?

A: One, giving them a checklist of questions in the beginning. Where did this data came from? Who were the observers? Who were the doctors and nurses who collected the data? And then learn a little bit about the landscape of those institutions. If it’s an ICU database, they need to ask who makes it to the ICU, and who doesn’t make it to the ICU, because that already introduces a sampling selection bias. If all the minority patients don’t even get admitted to the ICU because they cannot reach the ICU in time, then the models are not going to work for them. Truly, to me, 50 percent of the course content should really be understanding the data, if not more, because the modeling itself is easy once you understand the data.

Since 2014, the MIT Critical Data consortium has been organizing datathons (data “hackathons”) around the world. At these gatherings, doctors, nurses, other health care workers, and data scientists get together to comb through databases and try to examine health and disease in the local context. Textbooks and journal papers present diseases based on observations and trials involving a narrow demographic typically from countries with resources for research. 

Our main objective now, what we want to teach them, is critical thinking skills. And the main ingredient for critical thinking is bringing together people with different backgrounds.

You cannot teach critical thinking in a room full of CEOs or in a room full of doctors. The environment is just not there. When we have datathons, we don’t even have to teach them how do you do critical thinking. As soon as you bring the right mix of people — and it’s not just coming from different backgrounds but from different generations — you don’t even have to tell them how to think critically. It just happens. The environment is right for that kind of thinking. So, we now tell our participants and our students, please, please do not start building any model unless you truly understand how the data came about, which patients made it into the database, what devices were used to measure, and are those devices consistently accurate across individuals?

When we have events around the world, we encourage them to look for data sets that are local, so that they are relevant. There’s resistance because they know that they will discover how bad their data sets are. We say that that’s fine. This is how you fix that. If you don’t know how bad they are, you’re going to continue collecting them in a very bad manner and they’re useless. You have to acknowledge that you’re not going to get it right the first time, and that’s perfectly fine. MIMIC (the Medical Information Marked for Intensive Care database built at Beth Israel Deaconess Medical Center) took a decade before we had a decent schema, and we only have a decent schema because people were telling us how bad MIMIC was.

We may not have the answers to all of these questions, but we can evoke something in people that helps them realize that there are so many problems in the data. I’m always thrilled to look at the blog posts from people who attended a datathon, who say that their world has changed. Now they’re more excited about the field because they realize the immense potential, but also the immense risk of harm if they don’t do this correctly.

A new Australian law requires larger companies to declare any ransomware payments they have made.

Faltering forecasts, fired experts and whipsawing policy changes are raising questions about how the Trump administration will respond to disasters this summer.

A new analysis credits the "pivotal transition" to substantial rate hikes and a state law restricting policyholder lawsuits against insurers.

Young people are suing the president over energy policies that could accelerate climate change.

The environmental group vouched for the tech giant — and carbon markets — in a greenwashing case involving the Apple Watch.

The Newsom administration was counting on high revenues from the program to backfill a state deficit.

With the federal government moving to dismantle clean car sales mandates, New York lawmakers are mulling a standard to transition the transportation sector away from fossil fuels.

The country claims to run the world's largest weather modification program and has increased investments as climate change heightens food security risks.

How glaciers collapse around the world can differ, scientists say. But in almost every instance, climate change is playing a role.

Nature Climate Change, Published online: 02 June 2025; doi:10.1038/s41558-025-02324-y

In this Perspective, the authors discuss how to robustly consider climate change impacts in ecosystem risk assessments. They highlight challenges in defining impacts, indicators and thresholds, in collating data, and in estimating and reporting risk, and propose solutions to inform conservation.

EFF has long advocated for affordable, accessible, and future-proof internet access for all. Digital equity, the condition in which everyone has access to technology that allows them to participate in society, is an issue that I’ve been proud to organize around. So, it’s awesome to connect with a group that's doing something to address it in their community.

Recently I got the chance to catch up with Maritza Grooms, Director of Community Relations at EFA member CCTV Cambridge, who told me about the results of their work and the impact it's having on their local community.

How’s your digital inclusion work going and what's been the results within the community?

CCTV has had a year of transition and change. One of the biggest was the establishing of the Digital Navigator Pilot Program in collaboration with multiple partners funded in part by Masshire Metro North Workforce Investment Board through the Mass Broadband Institute. This program has already had a great impact in Cambridge since its official launch in August 2024, serving 492 community members! This program demonstrates the clear need for digital navigator services in Cambridge and beyond. Our community has used this service to get devices that have allowed them restart their career journey or go back to school, and take digital literacy classes to gain new skills to help them along the way.

The Electronic Frontier Alliance works to uphold the principles of free expression, information security, privacy, creativity, and access to knowledge. What guides your organization and how does digital equity tie into it?

CCTV's mission is to nurture a strong, equitable, and diverse community by providing tools and training to foster free speech, civic engagement, access to knowledge, and creative expression. The Digital Navigator program fulfills this mission not only for the community we serve, but in the ripple effects that generate from our community members having the tools to participate in our society. The Digital Navigator Pilot Program aims to bridge the digital divide in Cambridge, specifically supporting BIPOC, immigrant, and low-income communities to enhance economic mobility.

How can people support and plug-in to what you’re doing?

We cannot do this alone. It takes a village, from partners in the work like our friends at EFF, and supporters alike. We encourage anyone to reach out to maritza@cctvcambridge.org to find out how you can support this program or visit cctvcambridge.org/support to support today and invite donations at your convenience. Follow us on social media @cctvcambridge!

Thanks again to Maritza for speaking with us. If you're inspired by CCTV Cambridge's work, consider joining a local EFA ally, or bringing your own group into the alliance today!

Below is the text of Melissa Nobles’ remarks, as prepared for delivery today.

Wow, thank you Emily and Andrew! Emily Jin on vocals and Andrew Li on saxophone, and their fellow musicians!

Class of 2025! Look at you, you’re looking really good in your regalia! It’s your graduation day! You did it! Congratulations!

And congratulations to all of your loved ones, all of the people who helped support you.

Your parents, your brothers and sisters, your aunties and your uncles, and your friends. This is a special day for them too. They are so proud of you!

A warm welcome to the loved ones who are here with us today on Killian Court — they’ve come here from all over to celebrate you!

And a special shout out to those who are watching from afar, wishing they could be here with you in person!

Class of 2025, you’ve made a lot of memories during your time here: from classes to crushes, from the East Campus REX build to the Simmons ball pit to Next Haunt, from UROPs to the Hobby Shop, and from the Outfinite to the Infinite!

So, I’d like to take you back to the fall of 2021, when you arrived here at MIT.

You traveled from all parts of this country and the world — from 62 countries, to be exact — and landed right here in Cambridge. Together, you became MIT’s Class of 2025.

And you arrived on campus — all bright-eyed and beaver-tailed — after missing a lot of in-person high school rituals, a lot of the high school experience. So, you were extra eager for college, and, more specifically, super excited to be MIT students!

Although the campus was officially fully open for the first time since the Covid shutdown — students, staff, and faculty were all here in person, with Zoom taking a back seat to meeting in real life — there were still a lot of protocols in place.

You had to get through all the Covid tests because we were still testing. Do you remember those Ziploc bags?

You swabbed and submitted attestations because you wanted the keys to unlock doors to labs, classrooms, and all the experiences that make MIT, MIT.

And once you gained access, you discovered a campus that was shiny and welcoming, yet dusty after being mostly empty for a long while. And there was no manual for how to reanimate this place.

You didn’t flinch.

You chose MIT because you like to solve problems, and your inner beaver came out to bring the campus back to life, to make it a home.

You were curious, you surveyed the landscape, and you started to dig into the past in order to build your future.

You sought out seniors, the Class of 2022, to read you in, to show you the ropes, and they really came through for you. They felt the urgency of their limited time left on campus, and they taught you “how to MIT.”

You also pored through archival records of clubs, soaking up history to guide you forward. You filled in the gaps by speaking with faculty and staff and alums. You evaluated the options, decided what you wanted to revive and what you wanted to scrap.

And true to your nature as MIT students, you launched new stuff. You innovated and invented.

And you built communities, from FPOPs and orientation through 8.01, 18.02, your HASS classes, and your p-set groups.

You built communities in your dorms and in your sororities and fraternities.

You built communities through your sports, through your hobbies and through the arts.

You built communities all across campus.

And you learned that building communities is not always easy and quick. It takes effort, patience, and a willingness to listen to and learn from others.

But, in the end, it is so worth it because you’ve met and made friends with really interesting people. Some with similar backgrounds and others from very different backgrounds. And from that interesting and diverse group, you’ve identified your crew — the people with whom you’ve shared not only interests — but your dreams, your fears, your concerns, laughs, and tears. You’ve made real connections — connections that lead to a lifetime of friendship.

And over the past four years, right before our eyes, you’ve demonstrated the enduring value and power of higher education to change lives.

Throughout your time at MIT, you ideated, prototyped, and tested. You created new knowledge, waded through ambiguity, worked collaboratively, and, of course, you optimized.

Now, on your graduation day, we send you on your way with enormous pride and hope.

But at the same time, we are sending you out into the world at a very difficult and challenging time. It’s a time when we all are being asked to focus on traditions that we should honor and defend. It’s also a time calling on us to create new traditions, better suited to human thriving in this century.

It’s a time when the issues are big, the answers are complex, the stakes are high, and the paths are uncharted.

But, Class of 2025, you are prepared to face these daunting conditions. In the words of one of your classmates: MIT taught the Class of 2025 to have “confidence in your competence.”

You are ready to assess your environment, diagnose what is stale and what is broken, learn from history, apply your talents and skills, and create new knowledge.

You are ready to tackle the toughest of problems! You are ready to shape the future.   

And while you are doing so, I ask that you keep MIT’s values and mission at the center of your efforts: to be bold and imaginative in tackling these big problems and to do so with compassion and generosity.

Now, more than ever, we — meaning the world’s people — need you to lean in.

Once again, Congratulations Class of 2025!

“Class of 2025, are you ready?”

This was the question Hashim Sarkis, dean of the MIT School of Architecture and Planning, posed to the graduating class at the school’s Advanced Degree Ceremony at Kresge Auditorium on May 29. The response was enthusiastic applause and cheers from the 224 graduates from the departments of Architecture and Urban Studies and Planning, the Program in Media Arts and Sciences, and the Center for Real Estate.

Following his welcome to an audience filled with family and friends of the graduates, Sarkis introduced the day’s guest speaker, whom he cited as the “perfect fit for this class.” Recognizing the “international rainbow of graduates,” Sarkis welcomed Mary Robinson, former president of Ireland and head of the Mary Robinson Foundation — Climate Justice to the podium. Robinson, a lawyer by training, has had a wide-ranging career that began with elected positions in Ireland followed by leadership roles in global causes for justice, human rights, and climate change.

Robinson laced her remarks with personal anecdotes from her career, from with earning a master’s in law at nearby Harvard University in 1968 — a year of political unrest in the United States — to founding The Elders in 2007 with world leaders: former South African President Nelson Mandela, anti-apartheid and human rights activist Desmond Tutu, and former U.S. President Jimmy Carter.

She described an “early lesson” in recounting her efforts to reform the laws of contraception in Ireland at the beginning of her career in the Irish legislature. Previously, women were not prescribed birth control unless they were married and had irregular menstrual cycles certified by their physicians. Robinson received thousands of letters of condemnation and threats that she would destroy the country of Ireland if she would allow contraception to be more broadly available. The legislation introduced was successful despite the “hate mail” she received, which was so abhorrent that her fiancé at the time, now her husband, burned it. That experience taught her to stand firm to her values.

“If you really believe in something, you must be prepared to pay a price,” she told the graduates.

In closing, Robinson urged the class to put their “skills and talent to work to address the climate crisis,” a problem she said she came late to in her career.

“You have had the privilege of being here at the School of Architecture and Planning at MIT,” said Robinson. “When you leave here, find ways to lead.”

In a chilling sign of how far law enforcement surveillance has encroached on personal liberties, 404 Media recently revealed that a sheriff’s office in Texas searched data from more than 83,000 automated license plate reader (ALPR) cameras to track down a woman suspected of self-managing an abortion. The officer searched 6,809 different camera networks maintained by surveillance tech company Flock Safety, including states where abortion access is protected by law, such as Washington and Illinois. The search record listed the reason plainly: “had an abortion, search for female.”

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Screenshot of data

After the U.S. Supreme Court’s 2022 Dobbs v. Jackson Women’s Health Organization decision overturned Roe v. Wade, states were given sweeping authority to ban and even criminalize abortion. In Texas—where the officer who conducted this search is based—abortion is now almost entirely banned. But in Washington and Illinois, where many of the searched Flock cameras are located, abortion remains legal and protected as a fundamental right up to fetal viability.

The post-Dobbs legal landscape has also opened the door for law enforcement to exploit virtually any form of data—license plates, phone records, geolocation data—to pursue individuals across state lines. EFF’s Atlas of Surveillance has documented more than 1,800 agencies have deployed ALPRs, but at least 4,000 agencies are able to run searches through some agencies in Flock's network. Many agencies share the data freely with other agencies across the country, with little oversight, restriction, or even standards for accessing data. 

While this particular data point explicitly mentioned an abortion, scores of others in the audit logs released through public records requests simply list "investigation" as the reason for the plate search, with no indication of the alleged offense. That means other searches targeting someone for abortion, or another protected right in that jurisdiction, could be effectively invisible.

This case underscores our growing concern: that the mass surveillance infrastructure—originally sold as a tool to find stolen cars or missing persons—is now being used to target people seeking reproductive healthcare. This unchecked, warrant-less access that allows law enforcement to surveil across state lines blurs the line between “protection” and persecution.

From Missing Cars to Monitoring Bodies

EFF has long warned about the dangers of ALPRs, which scan license plates, log time and location data, and build a detailed picture of people's movements. Companies like Flock Safety and Motorola Solutions offer law enforcement agencies access to nationwide databases of these readers, and in some cases, allow them to stake out locations like abortion clinics, or create “hot lists” of license plates to track in real time. Flock's technology also allows officers to search for a vehicle based on attributes like color, make and model, even without a plate number.

The threat is compounded by how investigations often begin. A report published by If/When/How on the criminalization of self-managed abortion found that about a quarter of adult cases (26%) were reported to law enforcement by acquaintances entrusted with information, such as “friends, parents, or intimate partners” and another 18% through “other” means. This means that with ALPR tech, a tip from anyone can instantly escalate into a nationwide manhunt. And as Kate Bertash of the Digital Defense Fund explained to 404 Media, anti-abortion activists have long been documenting the plates of patients and providers who visit reproductive health facilities—data that can now be easily cross-referenced with ALPR databases.

The 404 Media report proves that this isn’t a hypothetical concern. In 2023, a months-long EFF investigation involving hundreds of public records requests uncovered that many California police departments were sharing records containing detailed driving profiles of local residents with out-of-state agencies, despite state laws explicitly prohibiting this. This means that even in so-called “safe” states, your data might end up helping law enforcement in Texas or Idaho prosecute you—or your doctor. 

That’s why we demanded that 75 California police departments stop sharing ALPR data with anti-abortion states, an effort that has largely been successful.

Surveillance and Reproductive Freedom Cannot Coexist

We’ve said it before, and we’ll say it again: Lawmakers who support reproductive rights must recognize that abortion access and mass surveillance are incompatible. 

The systems built to track stolen cars and issue parking tickets have become tools to enforce the most personal and politically charged laws in the country. What began as a local concern over privacy has escalated into a national civil liberties crisis.

Yesterday’s license plate readers have morphed into today’s reproductive dragnet. Now, it’s time for decisive action. Our leaders must roll back the dangerous surveillance systems they've enabled. We must enact strong, enforceable state laws to limit data sharing, ensure proper oversight, and dismantle these surveillance pipelines before they become the new normal–or even just eliminate the systems altogether.

There’s a new cybersecurity awareness campaign: Take9. The idea is that people—you, me, everyone—should just pause for nine seconds and think more about the link they are planning to click on, the file they are planning to download, or whatever it is they are planning to share.

There’s a website—of course—and a video, well-produced and scary. But the campaign won’t do much to improve cybersecurity. The advice isn’t reasonable, it won’t make either individuals or nations appreciably safer, and it deflects blame from the real causes of our cyberspace insecurities...