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AI and the Evolution of Social Media

Schneier on Security - Tue, 03/19/2024 - 7:05am

Oh, how the mighty have fallen. A decade ago, social media was celebrated for sparking democratic uprisings in the Arab world and beyond. Now front pages are splashed with stories of social platforms’ role in misinformation, business conspiracy, malfeasance, and risks to mental health. In a 2022 survey, Americans blamed social media for the coarsening of our political discourse, the spread of misinformation, and the increase in partisan polarization.

Today, tech’s darling is artificial intelligence. Like social media, it has the potential to change the world in many ways, some favorable to democracy. But at the same time, it has the potential to do incredible damage to society...

Startup promises to build carbon removal ‘orchard’

ClimateWire News - Tue, 03/19/2024 - 7:00am
Spiritus says the facility would be in central Wyoming but declined to share other details about its plan.

Should NY adopt facility-specific emissions caps? Groups’ report says yes.

ClimateWire News - Tue, 03/19/2024 - 6:55am
The analysis by Resources for the Future and the New York City Environmental Justice Alliance focuses on potential designs of a cap-and-trade-style program.

Oregon county plants trees to honor victims of 2021 heat wave

ClimateWire News - Tue, 03/19/2024 - 6:54am
Three consecutive days of extraordinary temperatures in the Pacific Northwest shattered all-time records. Oregon blamed 116 deaths statewide on the heat.

South Africa can’t afford to climate-proof its infrastructure

ClimateWire News - Tue, 03/19/2024 - 6:54am
The country has experienced a significant rise in climate change-related natural disasters over recent years. It's also constrained by high levels of debt.

UK undershoots budget for making homes greener by $608M

ClimateWire News - Tue, 03/19/2024 - 6:53am
The spending shortfall was largely down to the poor takeup of programs to insulate homes and upgrade gas boilers to heat pumps.

Change to SEC climate rule opens door to mischief, experts say

ClimateWire News - Tue, 03/19/2024 - 6:26am
By not requiring companies to report certain emissions, bad actors could outsource some of their business to avoid transparency.

Lottery will decide which court hears SEC climate slugfest

ClimateWire News - Tue, 03/19/2024 - 6:25am
Lawsuits over the agency's new climate risk disclosure rule have been filed in at least a half-dozen federal appeals courts.

Harvard shuts down geoengineering experiment

ClimateWire News - Tue, 03/19/2024 - 6:25am
The beleaguered project failed to conduct field tests because of opposition from environmentalists and Indigenous residents.

Trump Fed contender: Bring on a carbon tax

ClimateWire News - Tue, 03/19/2024 - 6:24am
Art Laffer plans to suggest taxing carbon — in return for a flat tax rate — if nominated for Federal Reserve chair in a second Trump term.

A protein found in human sweat may protect against Lyme disease

MIT Latest News - Tue, 03/19/2024 - 6:00am

Lyme disease, a bacterial infection transmitted by ticks, affects nearly half a million people in the United States every year. In most cases, antibiotics effectively clear the infection, but for some patients, symptoms linger for months or years.

Researchers at MIT and the University of Helsinki have now discovered that human sweat contains a protein that can protect against Lyme disease. They also found that about one-third of the population carries a genetic variant of this protein that is associated with Lyme disease in genome-wide association studies.

It’s unknown exactly how the protein inhibits the growth of the bacteria that cause Lyme disease, but the researchers hope to harness the protein’s protective abilities to create skin creams that could help prevent the disease, or to treat infections that don’t respond to antibiotics.

“This protein may provide some protection from Lyme disease, and we think there are real implications here for a preventative and possibly a therapeutic based on this protein,” says Michal Caspi Tal, a principal research scientist in MIT’s Department of Biological Engineering and one of the senior authors of the new study.

Hanna Ollila, a senior researcher at the Institute for Molecular Medicine at the University of Helsinki and a researcher at the Broad Institute of MIT and Harvard, is also a senior author of the paper, which appears today in Nature Communications. The paper’s lead author is Satu Strausz, a postdoc at the Institute for Molecular Medicine at the University of Helsinki.

A surprising link

Lyme disease is most often caused by a bacterium called Borrelia burgdorferi. In the United States, this bacterium is spread by ticks that are carried by mice, deer, and other animals. Symptoms include fever, headache, fatigue, and a distinctive bulls-eye rash.

Most patients receive doxycycline, an antibiotic that usually clears up the infection. In some patients, however, symptoms such as fatigue, memory problems, sleep disruption, and body aches can persist for months or years.

Tal and Ollila, who were postdocs together at Stanford University, began this study a few years ago in hopes of finding genetic markers of susceptibility to Lyme disease. To that end, they decided to run a genome-wide association study (GWAS) on a Finnish dataset that contains genome sequences for 410,000 people, along with detailed information on their medical histories.

This dataset includes about 7,000 people who had been diagnosed with Lyme disease, allowing the researchers to look for genetic variants that were more frequently found in people who had had Lyme disease, compared with those who hadn’t.

This analysis revealed three hits, including two found in immune molecules that had been previously linked with Lyme disease. However, their third hit was a complete surprise — a secretoglobin called SCGB1D2.

Secretoglobins are a family of proteins found in tissues that line the lungs and other organs, where they play a role in immune responses to infection. The researchers discovered that this particular secretoglobin is produced primarily by cells in the sweat glands.

To find out how this protein might influence Lyme disease, the researchers created normal and mutated versions of SCGB1D2 and exposed them to Borrelia burgdorferi grown in the lab. They found that the normal version of the protein significantly inhibited the growth of Borrelia burgdorferi. However, when they exposed bacteria to the mutated version, twice as much protein was required to suppress bacterial growth.

The researchers then exposed bacteria to either the normal or mutated variant of SCGB1D2 and injected them into mice. Mice injected with the bacteria exposed to the mutant protein became infected with Lyme disease, but mice injected with bacteria exposed to the normal version of SCGB1D2 did not.

“In the paper we show they stayed healthy until day 10, but we followed the mice for over a month, and they never got infected. This wasn’t a delay, this was a full stop. That was really exciting,” Tal says.

Preventing infection

After the MIT and University of Helsinki researchers posted their initial findings on a preprint server, researchers in Estonia replicated the results of the genome-wide association study, using data from the Estonian Biobank. These data, from about 210,000 people, including 18,000 with Lyme disease, were later added to the final Nature Communications study.

The researchers aren’t sure yet how SCGB1D2 inhibits bacterial growth, or why the variant is less effective. However, they did find that the variant causes a shift from the amino acid proline to leucine, which may interfere with the formation of a helix found in the normal version.

They now plan to investigate whether applying the protein to the skin of mice, which do not naturally produce SCGB1D2, could prevent them from being infected by Borrelia burgdorferi. They also plan to explore the protein’s potential as a treatment for infections that don’t respond to antibiotics.

“We have fantastic antibiotics that work for 90 percent of people, but in the 40 years we’ve known about Lyme disease, we have not budged that,” Tal says. “Ten percent of people don’t recover after having antibiotics, and there’s no treatment for them.”

“This finding opens the door to a completely new approach to preventing Lyme disease in the first place, and it will be interesting to see if it could be useful for preventing other types of skin infections too,” says Kara Spiller, a professor of biomedical innovation in the School of Biomedical Engineering at Drexel University, who was not involved in the study.

The researchers note that people who have the protective version of SCGB1D2 can still develop Lyme disease, and they should not assume that they won’t. One factor that may play a role is whether the person happens to be sweating when they’re bitten by a tick carrying Borrelia burgdorferi.

SCGB1D2 is just one of 11 secretoglobin proteins produced by the human body, and Tal also plans to study what some of those other secretoglobins may be doing in the body, especially in the lungs, where many of them are found.

“The thing I’m most excited about is this idea that secretoglobins might be a class of antimicrobial proteins that we haven’t thought about. As immunologists, we talk nonstop about immunoglobulins, but I had never heard of a secretoglobin before this popped up in our GWAS study. This is why it’s so fun for me now. I want to know what they all do,” she says.

The research was funded, in part, by Emily and Malcolm Fairbairn, the Instrumentarium Science Foundation, the Academy of Finland, the Finnish Medical Foundation, the Younger Family, and the Bay Area Lyme Foundation.

Pushing material boundaries for better electronics

MIT Latest News - Tue, 03/19/2024 - 12:00am

Undergrads, take note: The lessons you learn in those intro classes could be the key to making your next big discovery. At least, that’s been the case for MIT’s Jeehwan Kim.

A recently tenured faculty member in MIT’s departments of Mechanical Engineering and Materials Science and Engineering, Kim has made numerous discoveries about the nanostructure of materials and is funneling them directly into the advancement of next-generation electronics.

His research aims to push electronics past the inherent limits of silicon — a material that has reliably powered transistors and most other electronic elements but is reaching a performance limit as more computing power is packed into ever smaller devices.

Today, Kim and his students at MIT are exploring materials, devices, and systems that could take over where silicon leaves off. Kim is applying his insights to design next-generation devices, including low-power, high-performance transistors and memory devices, artificial intelligence chips, ultra-high-definition micro-LED displays, and flexible electronic “skin.” Ultimately, he envisions such beyond-silicon devices could be built into supercomputers small enough to fit in your pocket.

The innovations that have come out of his research are recorded in more than 200 issued U.S. patents and 70 research papers — an extensive list that he and his students continue to grow.

Kim credits many of his breakthroughs to the fundamentals he learned in his university days. In fact, he has carried his college textbooks and notes with him with every move. Today, he keeps the undergraduate notes — written in a light and meticulous graphite and ink — on a shelf nearest to his MIT desk, close at hand. He references them in his own class lectures and presentations, and when brainstorming research solutions.

“These textbooks are all in my brain now,” Kim says. “I’ve learned that if you completely understand the fundamentals, you can solve any problem.”

Fundamental shift

Kim wasn’t always a model student. Growing up in Seoul, South Korea, he was fixed on a musical career. He had a passion for singing and was bored by most other high school subjects.

“It was very monotonic,” Kim recalls. “My motivation for high school subjects was very low.”

After graduating high school, he enrolled in a materials science program at Hongik University, where he was lucky to met professors who had graduated from MIT and who later motivated him to study in the United States. But, Kim spent his first year there trying to make it as a musician. He wrote and sang songs that he recorded and sent to promoters, and went to multiple auditions. But after a year, he was faced with no call-backs, and a hard question.

“What should I do? It was a crisis to me,” Kim says.

In his second year, he decided to give materials science a go. When he sat in on his first class, he was surprised to find that the subject — the structure and behavior of materials at the atomic scale — made him want to learn more.

“My first year, my GPA was almost zero because I didn’t attend class, and was going to be kicked out,” Kim says. “Then from my second year on, I really loved every single subject in materials science. People who saw me in the library were surprised: ‘What are you doing here, without a guitar?’ I must have read these textbooks more than 10 times, and felt I really understood everything fundamental.”

Back to basics

He took this newfound passion to Seoul National University, where he enrolled in the materials science master’s program and learned to apply the ideas he absorbed to hands-on research problems. Metallurgy was a dominant field at the time, and Kim was assigned to experiment with high-temperature alloys — mixing and melting metallic powders to create materials that could be used in high-performance engines.

After completing his master’s, Kim wanted to continue with a PhD, overseas. But to do so, he first had to serve in the military. He spent the next two and a half years in the Korean air force, helping to maintain and refuel aircraft, and inventory their parts. All the while, he prepared applications to graduate schools abroad.

In 2003, after completing his service, he headed overseas, where he was accepted to the materials science graduate program at the University of California at Los Angeles with a fellowship.

“When I came out of the airplane and went to the dorm for the first day, people were drinking Corona on the balcony, playing music, and there was beautiful weather, and I thought, this is where I’m supposed to be!” Kim recalls.

For his PhD, he began to dive into the microscopic world of electronic materials, seeking ways to manipulate them to make faster electronics. The subject was a focus for his advisor, who previously worked at Bell Labs, where many computing innovations originated at the time.

“A lot of the papers I was reading were from Bell Labs, and IBM T.J. Watson, and I was so impressed, and thought: I really want to be a scientist there. That was my dream,” Kim says.

During his PhD program, he reached out to a scientist at IBM whose name kept coming up in the papers Kim was reading. In his initial letter, Kim wrote with a question about his own PhD work, which tackled a hard industry problem: how to stretch, or “strain,” silicon to minimize defects that would occur as more transistors are packed on a chip. 

The query opened a dialogue, and Kim eventually inquired and was accepted to an internship at the IBM T.J. Watson Research Center, just outside New York City. Soon after he arrived, his manager pitched him a challenge: He might be hired full-time if he could solve a new, harder problem, having to do with replacing silicon.

At the time, the electronics industry was looking to germanium as a possible successor to silicon. The material can conduct electrons at even smaller scales, which would enable germanium to be made into even tinier transistors, for faster, smaller, and more powerful devices. But there was no reliable way for germanium to be “doped” — an essential process that replaces some of a material’s atoms with another type of atom in a way that controls how electrons flow through the material.

“My manager told me he didn’t expect me to solve this. But I really wanted the job,” Kim says. “So day and night, I thought, how to solve this? And I always went back to the textbooks.”

Those textbooks reminded him of a fundamental rule: Replacing one atom with another would work well if both atoms were of similar size. This revelation triggered an idea. Perhaps germanium could be doped with a combination of two different atoms with an average atomic size that is similar to germanium’s.

“I came up with this idea, and right after, IBM showed that it worked. I was so amazed,” Kim says. “From that point, research became my passion. I did it because it was just so fun. Singing is not so different from performing research.”

As promised, he was hired as a postdoc and soon after, promoted to research staff member — a title he carried, literally, with pride.

“I was feeling so happy to be there,” Kim says. “I even wore my IBM badge to restaurants, and everywhere I went.”

Throughout his time at IBM, he learned to focus on research that directly impacts everyday human life, and how to apply the fundamentals to develop next-generation products.

“IBM really raised me up as an engineer who can identify the problems in an industry and find creative solutions to tackle the challenges,” he says.

Cycle of life

And yet, Kim felt he could do more. He was working on boundary-pushing research at one of the leading innovation hubs in the country, where “out-of-the-box” thinking was encouraged, and experimentally tested. But he wanted to explore beyond the company’s research portfolio, and also, find a way to pursue research not just as a profession but as a passion.

“My experience taught me that you can lead a very happy life as an engineer or scientist if your research becomes your hobby,” Kim says. “I wanted to teach this cycle — of happiness, research, and passion — to young people and help PhD students develop like artists or singers.”

In 2015, he packed his bags for MIT, where he accepted a junior faculty position in the Department of Mechanical Engineering. His first impressions upon arriving at the Institute?

“Freedom,” Kim says. “For me, free thinking — to compose music, innovate something totally new — is the most important thing. And the people at MIT are very talented and curious of all the things.”

Since he’s put down roots on campus, he has built up a highly productive research group, focused on fabricating ultra-thin, stackable, high-performance electronic materials and devices, which Kim envisions could be used to build hybrid electronic systems as small as a fingernail and as powerful as a supercomputer. He credits the group’s many innovations to the more than 40 students, postdocs, and research scientists who have contributed to his lab.

“I hope this is where they can learn that research can be an art,” Kim says. “To students especially, I hope they see that, if they enjoy what they do, then they can be whatever they want to be.”

Effective climate action must integrate climate adaptation and mitigation

Nature Climate Change - Tue, 03/19/2024 - 12:00am

Nature Climate Change, Published online: 19 March 2024; doi:10.1038/s41558-024-01963-x

Mitigation and adaptation strategies have historically been, and continue to be, developed separately. The climate is already changing and integration of adaptation and mitigation in policy and practice is now urgently needed.

Trends in the global invention and international diffusion of methane abatement technologies

Nature Climate Change - Tue, 03/19/2024 - 12:00am

Nature Climate Change, Published online: 19 March 2024; doi:10.1038/s41558-024-01948-w

Analysis of patent data from 1990 to 2019 reveals a global decline in the invention and international diffusion of high-quality methane-targeted abatement technologies (MTATs) from 2010 to 2019. Moreover, there is a mismatch between where MTAT inventions are concentrated and the countries or regions expected to have most growth in future methane emissions.

Global trend of methane abatement inventions and widening mismatch with methane emissions

Nature Climate Change - Tue, 03/19/2024 - 12:00am

Nature Climate Change, Published online: 19 March 2024; doi:10.1038/s41558-024-01947-x

Innovations in methane-targeted abatement technologies (MTAT) are needed to curb climate change in the short term. This Analysis reveals the trend, distributions and diffusion of MTAT-related patents for the past few decades, highlighting the mismatch between emissions sources and technical capacity.

Decoding the California DMV's Mobile Driver's License

EFF: Updates - Mon, 03/18/2024 - 9:16pm

The State of California is currently rolling out a “mobile driver’s license” (mDL), a form of digital identification that raises significant privacy and equity concerns. This post explains the new smartphone application, explores the risks, and calls on the state and its vendor to focus more on protection of the users. 

What is the California DMV Wallet? 

The California DMV Wallet app came out in app stores last year as a pilot, offering the ability to store and display your mDL on your smartphone, without needing to carry and present a traditional physical document. Several features in this app replicate how we currently present the physical document with key information about our identity—like address, age, birthday, driver class, etc. 

However, other features in the app provide new ways to present the data on your driver’s license. Right now, we only take out our driver’s license occasionally throughout the week. However, with the app’s QR Code and “add-on” features, the incentive for frequency may grow. This concerns us, given the rise of age verification laws that burden everyone’s access to the internet, and the lack of comprehensive consumer data privacy laws that keep businesses from harvesting and selling identifying information and sensitive personal information. 

For now, you can use the California DMV Wallet app with TSA in airports, and with select stores that have opted in to an age verification feature called TruAge. That feature generates a separate QR Code for age verification on age-restricted items in stores, like alcohol and tobacco. This is not simply a one-to-one exchange of going from a physical document to an mDL. Rather, this presents a wider scope of possible usage of mDLs that needs expanded protections for those who use them. While California is not the first state to do this, this app will be used as an example to explain the current landscape.

What’s the QR Code? 

There are two ways to present your information on the mDL: 1) a human readable presentation, or 2) a QR code. 

The QR code with a normal QR code scanner will display an alphanumeric string of text that starts with “mdoc:”. For example: 

 “mdoc:owBjMS4wAY..." [shortened for brevity]

This “mobile document” (mdoc) text is defined by the International Organization for Standardization’s ISO/IEC18013-5. The string of text afterwards details driver’s license data that has been signed by the issuer (i.e., the California DMV), encrypted, and encoded. This data sequence includes technical specifications and standards, open and enclosed.  

In the digital identity space, including mDLs, the most referenced and utilized are the ISO standard above, the American Association of Motor Vehicle Administrators (AAMVA) standard, and the W3C’s Verified Credentials (VC). These standards are often not siloed, but rather used together since they offer directions on data formats, security, and methods of presentation that aren’t completely covered by just one. However, ISO and AAMVA are not open standards and are decided internally. VCs were created for digital credentials generally, not just for mDLs. These standards are relatively new and still need time to mature to address potential gaps.

The decrypted data could possibly look like this JSON blob:

         {"family_name":"Doe",
          "given_name":"John",
          "birth_date":"1980-10-10",
          "issue_date":"2020-08-10",
          "expiry_date":"2030-10-30",
          "issuing_country":"US",
          "issuing_authority":"CA DMV",
          "document_number":"I12345678",
          "portrait":"../../../../test/issuance/portrait.b64",
          "driving_privileges":[
            {
               "vehicle_category_code":"A",
               "issue_date":"2022-08-09",
               "expiry_date":"2030-10-20"
            },
            {
               "vehicle_category_code":"B",
               "issue_date":"2022-08-09",
               "expiry_date":"2030-10-20"
            }
          ],
          "un_distinguishing_sign":"USA",
          {
          "weight":70,
          "eye_colour":"hazel",
          "hair_colour":"red",
          "birth_place":"California",
          "resident_address":"2415 1st Avenue",
          "portrait_capture_date":"2020-08-10T12:00:00Z",
          "age_in_years":42,
          "age_birth_year":1980,
          "age_over_18":true,
          "age_over_21":true,
          "issuing_jurisdiction":"US-CA",
          "nationality":"US",
          "resident_city":"Sacramento",
          "resident_state":"California",
          "resident_postal_code":"95818",
          "resident_country": "US"}
}

Application Approach and Scope Problems 

California decided to contract a vendor to build a wallet app rather than use Google Wallet or Apple Wallet (not to be conflated with Google and Apple Pay). A handful of other states use Google and Apple, perhaps because many people have one or the other. There are concerns about large companies being contracted by the states to deliver mDLs to the public, such as their controlling the public image of digital identity and device compatibility.  

This isn’t the first time a state contracted with a vendor to build a digital credential application without much public input or consensus. For example, New York State contracted with IBM to roll out the Excelsior app during the beginning of COVID-19 vaccination availability. At the time, EFF raised privacy and other concerns about this form of digital proof of vaccination. The state ultimately paid the vendor a staggering $64 million. While initially proprietary, the application later opened to the SMART Health Card standard, which is based on the W3C’s VCs. The app was sunset last year. It’s not clear what effect it had on public health, but it’s good that it wound down as social distancing measures relaxed. The infrastructure should be dismantled, and the persistent data should be discarded. If another health crisis emerges, at least a law in New York now partially protects the privacy of this kind of data. NY state legislature is currently working on a bill around mDLs after a round-table on their potential pilot. However, the New York DMV has already entered into a $1.75 million dollar contract with the digital identity vendor IDEMIA. It will be a race to see if protections will be established prior to pilot deployment. 

Scope is also a concern with California’s mDL. The state contracted with Spruce ID to build this app. The company states that its purpose is to empower “organizations to manage the entire lifecycle of digital credentials, such as mobile driver’s licenses, software audit statements, professional certifications, and more.” In the “add-ons” section of the app, TruAge’s age verification QR code is available.  

Another issue is selective disclosure, meaning the technical ability for the identity credential holder to choose which information to disclose to a person or entity asking for information from their credential. This is a long-time promise from enthusiasts of digital identity. The most used example is verification that the credential holder is over 21, without showing anything else about the holder, such as their name and address that appear on the face of their traditional driver’s license. But the California DMV wallet app, has a lack of options for selective disclosure: 

  • The holder has to agree to TruAge’s terms and service and generate a separate TruAge QR Code.  
  • There is already an mDL reader option for age verification for the QR Code of an mDL. 
  • There is no current option for the holder to use selective disclosure for their mDL. But it is planned for future release, according to the California DMV via email. 
  • Lastly, if selective disclosure is coming, this makes the TruAge add-on redundant. 

The over-21 example is only as meaningful as its implementation; including the convenience, privacy, and choice given to the mDL holder. 

TruAge appears to be piloting its product in at least 6 states. With “add-ons”, the scope of the wallet app indicates expansion beyond simply presenting your driver’s license. According to the California DMV’s Office of Public Affairs via email: 

The DMV is exploring the possibility of offering additional services including disabled person parking placard ID, registration card, vehicle ownership and occupational license in the add-ons in the coming months.” 

This clearly displays how the scope of this pilot may expand and how the mDL could eventually be housed within an entire ecosystem of identity documentation. There are privacy preserving ways to present mDLs, like unlinkable proofs. These mechanisms help mitigate verifier-issuer collusion from establishing if the holder was in different places with their mDL. 

Privacy and Equity First 

At the time of this post, about 325,000 California residents have the pilot app. We urge states to take their time with creating mDLs, and even wait for verification methods that are more privacy considerate to mature. Deploying mDLs should prioritize holder control, privacy, and transparency. The speed of these pilots is possibly influenced by other factors, like the push for mDLs from the U.S. Department of Homeland Security. 

Digital wallet initiatives like eIDAS in the European Union are forging conversations on what user control mechanisms might look like. These might include, for example, “bringing your own wallet” and using an “open wallet” that is secure, private, interoperable, and portable. 

We also need governance that properly limits law enforcement access to information collected by mDLs, and to other information in the smartphones where holders place their mDLs. Further, we need safeguards against these state-created wallets being wedged into problematic realms like age verification mandates as a condition of accessing the internet. 

We should be speed running privacy and provide better access for all to public services and government-issued documentation. That includes a right to stick with traditional paper or plastic identification, and accommodation of cases where a phone may not be accessible.  

We urge the state to implement selective disclosure and other privacy preserving tools. The app is not required anywhere. It should remain that way no matter how cryptographically secure the system purports to be, or how robust the privacy policies. We also urge all governments to remain transparent and cautious about how they sign on vendors during pilot programs. If a contract takes away the public’s input on future protections, then that is a bad start. If a state builds a pilot without much patience for privacy and public input, then that is also turbulent ground for protecting users going forward.  

Just because digital identity may feel inevitable, doesn’t mean the dangers have to be. 

EFF to California Appellate Court: Reject Trial Judge’s Ruling That Would Penalize Beneficial Features and Tools on Social Media

EFF: Updates - Mon, 03/18/2024 - 7:22pm

EFF legal intern Jack Beck contributed to this post.

A California trial court recently departed from wide-ranging precedent and held that Snap, Inc., the maker of Snapchat, the popular social media app, had created a “defective” product by including features like disappearing messages, the ability to connect with people through mutual friends, and even the well-known “Stories” feature. We filed an amicus brief in the appeal, Neville v. Snap, Inc., at the California Court of Appeal, and are calling for the reversal of the earlier decision, which jeopardizes protections for online intermediaries and thus the free speech of all internet users.

At issue in the case is Section 230, without which the free and open internet as we know it would not exist. Section 230 provides that online intermediaries are generally not responsible for harmful user-generated content. Rather, responsibility for what a speaker says online falls on the person who spoke.

The plaintiffs are a group of parents whose children overdosed on fentanyl-laced drugs obtained through communications enabled by Snapchat. Even though the harm they suffered was premised on user-generated content—messages between the drug dealers and their children—the plaintiffs argued that Snapchat is a “defective product.” They highlighted various features available to all users on Snapchat, including disappearing messages, arguing that the features facilitate illegal drug deals.

Snap sought to have the case dismissed, arguing that the plaintiffs’ claims were barred by Section 230. The trial court disagreed, narrowly interpreting Section 230 and erroneously holding that the plaintiffs were merely trying to hold the company responsible for its own “independent tortious conduct—independent, that is, of the drug sellers’ posted content.” In so doing, the trial court departed from congressional intent and wide-ranging California and federal court precedent.

In a petition for a writ of mandate, Snap urged the appellate court to correct the lower court’s distortion of Section 230. The petition rightfully contends that the plaintiffs are trying to sidestep Section 230 through creative pleading. The petition argues that Section 230 protects online intermediaries from liability not only for hosting third-party content, but also for crucial editorial decisions like what features and tools to offer content creators and how to display their content.

We made two arguments in our brief supporting Snap’s appeal.

First, we explained that the features the plaintiffs targeted—and which the trial court gave no detailed analysis of—are regular parts of Snapchat’s functionality with numerous legitimate uses. Take Snapchat’s option to have messages disappear after a certain period of time. There are times when the option to make messages disappear can be crucial for protecting someone’s safety—for example, dissidents and journalists operating in repressive regimes, or domestic violence victims reaching out for support. It’s also an important privacy feature for everyday use. Simply put: the ability for users to exert control over who can see their messages and for how long, advances internet users’ privacy and security under legitimate circumstances.

Second, we highlighted in our brief that this case is about more than concerned families challenging a big tech company. Our modern communications are mediated by private companies, and so any weakening of Section 230 immunity for internet platforms would stifle everyone’s ability to communicate. Should the trial court’s ruling stand, Snapchat and similar platforms will be incentivized to remove features from their online services, resulting in bland and sanitized—and potentially more privacy invasive and less secure—communications platforms. User experience will be degraded as internet platforms are discouraged from creating new features and tools that facilitate speech. Companies seeking to minimize their legal exposure for harmful user-generated content will also drastically increase censorship of their users, and smaller platforms trying to get off the ground will fail to get funding or will be forced to shut down.

There’s no question that what happened in this case was tragic, and people are right to be upset about some elements of how big tech companies operate. But Section 230 is the wrong target. We strongly advocate for Section 230, yet when a tech company does something legitimately irresponsible, the statute still allows for them to be liable—as Snap knows from a lawsuit that put an end to its speed filter.

If the trial court’s decision is upheld, internet platforms would not have a reliable way to limit liability for the services they provide and the content they host. They would face too many lawsuits that cost too much money to defend. They would be unable to operate in their current capacity, and ultimately the internet would cease to exist in its current form. Billions of internet users would lose.

New algorithm unlocks high-resolution insights for computer vision

MIT Latest News - Mon, 03/18/2024 - 3:10pm

Imagine yourself glancing at a busy street for a few moments, then trying to sketch the scene you saw from memory. Most people could draw the rough positions of the major objects like cars, people, and crosswalks, but almost no one can draw every detail with pixel-perfect accuracy. The same is true for most modern computer vision algorithms: They are fantastic at capturing high-level details of a scene, but they lose fine-grained details as they process information.

Now, MIT researchers have created a system called “FeatUp” that lets algorithms capture all of the high- and low-level details of a scene at the same time — almost like Lasik eye surgery for computer vision.

When computers learn to “see” from looking at images and videos, they build up “ideas” of what's in a scene through something called “features.” To create these features, deep networks and visual foundation models break down images into a grid of tiny squares and process these squares as a group to determine what's going on in a photo. Each tiny square is usually made up of anywhere from 16 to 32 pixels, so the resolution of these algorithms is dramatically smaller than the images they work with. In trying to summarize and understand photos, algorithms lose a ton of pixel clarity. 

The FeatUp algorithm can stop this loss of information and boost the resolution of any deep network without compromising on speed or quality. This allows researchers to quickly and easily improve the resolution of any new or existing algorithm. For example, imagine trying to interpret the predictions of a lung cancer detection algorithm with the goal of localizing the tumor. Applying FeatUp before interpreting the algorithm using a method like class activation maps (CAM) can yield a dramatically more detailed (16-32x) view of where the tumor might be located according to the model. 

FeatUp not only helps practitioners understand their models, but also can improve a panoply of different tasks like object detection, semantic segmentation (assigning labels to pixels in an image with object labels), and depth estimation. It achieves this by providing more accurate, high-resolution features, which are crucial for building vision applications ranging from autonomous driving to medical imaging.

“The essence of all computer vision lies in these deep, intelligent features that emerge from the depths of deep learning architectures. The big challenge of modern algorithms is that they reduce large images to  very small grids of 'smart' features, gaining intelligent insights but losing the finer details,” says Mark Hamilton, an MIT PhD student in electrical engineering and computer science, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) affiliate, and a co-lead author on a paper about the project. “FeatUp helps enable the best of both worlds: highly intelligent representations with the original image’s resolution. These high-resolution features significantly boost performance across a spectrum of computer vision tasks, from enhancing object detection and improving depth prediction to providing a deeper understanding of your network's decision-making process through high-resolution analysis.” 

Resolution renaissance 

As these large AI models become more and more prevalent, there’s an increasing need to explain what they’re doing, what they’re looking at, and what they’re thinking. 

But how exactly can FeatUp discover these fine-grained details? Curiously, the secret lies in wiggling and jiggling images. 

In particular, FeatUp applies minor adjustments (like moving the image a few pixels to the left or right) and watches how an algorithm responds to these slight movements of the image. This results in hundreds of deep-feature maps that are all slightly different, which can be combined into a single crisp, high-resolution, set of deep features. “We imagine that some high-resolution features exist, and that when we wiggle them and blur them, they will match all of the original, lower-resolution features from the wiggled images. Our goal is to learn how to refine the low-resolution features into high-resolution features using this 'game' that lets us know how well we are doing,” says Hamilton. This methodology is analogous to how algorithms can create a 3D model from multiple 2D images by ensuring that the predicted 3D object matches all of the 2D photos used to create it. In FeatUp’s case, they predict a high-resolution feature map that’s consistent with all of the low-resolution feature maps formed by jittering the original image.

The team notes that standard tools available in PyTorch were insufficient for their needs, and introduced a new type of deep network layer in their quest for a speedy and efficient solution. Their custom layer, a special joint bilateral upsampling operation, was over 100 times more efficient than a naive implementation in PyTorch. The team also showed this new layer could improve a wide variety of different algorithms including semantic segmentation and depth prediction. This layer improved the network’s ability to process and understand high-resolution details, giving any algorithm that used it a substantial performance boost. 

“Another application is something called small object retrieval, where our algorithm allows for precise localization of objects. For example, even in cluttered road scenes algorithms enriched with FeatUp can see tiny objects like traffic cones, reflectors, lights, and potholes where their low-resolution cousins fail. This demonstrates its capability to enhance coarse features into finely detailed signals,” says Stephanie Fu ’22, MNG ’23, a PhD student at the University of California at Berkeley and another co-lead author on the new FeatUp paper. “This is especially critical for time-sensitive tasks, like pinpointing a traffic sign on a cluttered expressway in a driverless car. This can not only improve the accuracy of such tasks by turning broad guesses into exact localizations, but might also make these systems more reliable, interpretable, and trustworthy.”

What next?

Regarding future aspirations, the team emphasizes FeatUp’s potential widespread adoption within the research community and beyond, akin to data augmentation practices. “The goal is to make this method a fundamental tool in deep learning, enriching models to perceive the world in greater detail without the computational inefficiency of traditional high-resolution processing,” says Fu.

“FeatUp represents a wonderful advance towards making visual representations really useful, by producing them at full image resolutions,” says Cornell University computer science professor Noah Snavely, who was not involved in the research. “Learned visual representations have become really good in the last few years, but they are almost always produced at very low resolution — you might put in a nice full-resolution photo, and get back a tiny, postage stamp-sized grid of features. That’s a problem if you want to use those features in applications that produce full-resolution outputs. FeatUp solves this problem in a creative way by combining classic ideas in super-resolution with modern learning approaches, leading to beautiful, high-resolution feature maps.”

“We hope this simple idea can have broad application. It provides high-resolution versions of image analytics that we’d thought before could only be low-resolution,” says senior author William T. Freeman, an MIT professor of electrical engineering and computer science professor and CSAIL member.

Lead authors Fu and Hamilton are accompanied by MIT PhD students Laura Brandt SM ’21 and Axel Feldmann SM ’21, as well as Zhoutong Zhang SM ’21, PhD ’22, all current or former affiliates of MIT CSAIL. Their research is supported, in part, by a National Science Foundation Graduate Research Fellowship, by the National Science Foundation and Office of the Director of National Intelligence, by the U.S. Air Force Research Laboratory, and by the U.S. Air Force Artificial Intelligence Accelerator. The group will present their work in May at the International Conference on Learning Representations.

Five MIT faculty members take on Cancer Grand Challenges

MIT Latest News - Mon, 03/18/2024 - 10:15am

Cancer Grand Challenges recently announced five winning teams for 2024, which included five researchers from MIT: Michael Birnbaum, Regina Barzilay, Brandon DeKosky, Seychelle Vos, and Ömer Yilmaz. Each team is made up of interdisciplinary cancer researchers from across the globe and will be awarded $25 million over five years. 

Birnbaum, an associate professor in the Department of Biological Engineering, leads Team MATCHMAKERS and is joined by co-investigators Barzilay, the School of Engineering Distinguished Professor for AI and Health in the Department of Electrical Engineering and Computer Science and the AI faculty lead at the MIT Abdul Latif Jameel Clinic for Machine Learning in Health; and DeKosky, Phillip and Susan Ragon Career Development Professor of Chemical Engineering. All three are also affiliates of the Koch Institute for Integrative Cancer Research At MIT.

Team MATCHMAKERS will take advantage of recent advances in artificial intelligence to develop tools for personalized immunotherapies for cancer patients. Cancer immunotherapies, which recruit the patient’s own immune system against the disease, have transformed treatment for some cancers, but not for all types and not for all patients. 

T cells are one target for immunotherapies because of their central role in the immune response. These immune cells use receptors on their surface to recognize protein fragments called antigens on cancer cells. Once T cells attach to cancer antigens, they mark them for destruction by the immune system. However, T cell receptors are exceptionally diverse within one person’s immune system and from person to person, making it difficult to predict how any one cancer patient will respond to an immunotherapy.  

Team MATCHMAKERS will collect data on T cell receptors and the different antigens they target and build computer models to predict antigen recognition by different T cell receptors. The team’s overarching goal is to develop tools for predicting T cell recognition with simple clinical lab tests and designing antigen-specific immunotherapies. “If successful, what we learn on our team could help transform prediction of T cell receptor recognition from something that is only possible in a few sophisticated laboratories in the world, for a few people at a time, into a routine process,” says Birnbaum. 

“The MATCHMAKERS project draws on MIT’s long tradition of developing cutting-edge artificial intelligence tools for the benefit of society,” comments Ryan Schoenfeld, CEO of The Mark Foundation for Cancer Research. “Their approach to optimizing immunotherapy for cancer and many other diseases is exemplary of the type of interdisciplinary research The Mark Foundation prioritizes supporting.” In addition to The Mark Foundation, the MATCHMAKERS team is funded by Cancer Research UK and the U.S. National Cancer Institute.

Vos, the Robert A. Swanson (1969) Career Development Professor of Life Sciences and HHMI Freeman Hrabowksi Scholar in the Department of Biology, will be a co-investigator on Team KOODAC. The KOODAC team will develop new treatments for solid tumors in children, using protein degradation strategies to target previously “undruggable” drivers of cancers. KOODAC is funded by Cancer Research UK, France's Institut National Du Cancer, and KiKa (Children Cancer Free Foundation) through Cancer Grand Challenges. 

As a co-investigator on team PROSPECT, Yilmaz, who is also a Koch Institute affiliate, will help address early-onset colorectal cancers, an emerging global problem among individuals younger than 50 years. The team seeks to elucidate pathways, risk factors, and molecules involved in the disease’s development. Team PROSPECT is supported by Cancer Research UK, the U.S. National Cancer Institute, the Bowelbabe Fund for Cancer Research UK, and France's Institut National Du Cancer through Cancer Grand Challenges.  

Unlocking the quantum future

MIT Latest News - Mon, 03/18/2024 - 9:55am

Quantum computing is the next frontier for faster and more powerful computing technologies. It has the potential to better optimize routes for shipping and delivery, speed up battery development for electric vehicles, and more accurately predict trends in financial markets. But to unlock the quantum future, scientists and engineers need to solve outstanding technical challenges while continuing to explore new applications.

One place where they’re working towards this future is the MIT Interdisciplinary Quantum Hackathon, or iQuHACK for short (pronounced “i-quack,” like a duck). Each year, a community of quhackers (quantum hackers) gathers at iQuHACK to work on quantum computing projects using real quantum computers and simulators. This year, the hackathon was held both in-person at MIT and online over three days in February.

Quhackers worked in teams to advance the capability of quantum computers and to investigate promising applications. Collectively, they tackled a wide range of projects, such as running a quantum-powered dating service, building an organ donor matching app, and breaking into quantum vaults. While working, quhackers could consult with scientists and engineers in attendance from sponsoring companies. Many sponsors also received feedback and ideas from quhackers to help improve their quantum platforms.

But organizing iQuHACK 2024 was no easy feat. Co-chairs Alessandro Buzzi and Daniela Zaidenberg led a committee of nine members to hold the largest iQuHACK yet. “It wouldn’t have been possible without them,” Buzzi said. The hackathon hosted 260 in-person quhackers and 1,000 remote quhackers, representing 77 countries in total. More than 20 scientists and engineers from sponsoring companies also attended in person as mentors for quhackers.

Each team of quhackers tackled one of 10 challenges posed by the hackathon’s eight major sponsoring companies. Some challenges asked quhackers to improve computing performance, such as by making quantum algorithms faster and more accurate. Other challenges asked quhackers to explore applying quantum computing to other fields, such as finance and machine learning. The sponsors worked with the iQuHACK committee to craft creative challenges with industry relevance and societal impact. “We wanted people to be able to address an interesting challenge [that has] applications in the real world,” says Zaidenberg.

One team of quhackers looked for potential quantum applications and found one close to home: dating. A team member, Liam Kronman, had previously built dating apps but disliked that matching algorithms for normal classical computers “require [an overly] strict setup.” With these classical algorithms, people must be split into two groups — for example, men and women — and matches can only be made between these groups. But with quantum computers, matching algorithms are more flexible and can consider all possible combinations, enabling the inclusion of multiple genders and gender preferences. 

Kronman and his team members leveraged these quantum algorithms to build a quantum-powered dating platform called MITqute (pronounced “meet cute”). To date, the platform has matched at least 240 people from the iQuHACK and MIT undergrad communities. In a follow-up survey, 13 out of 41 respondents reported having talked with their match, with at least two pairs setting up dates. “I really lucked out with this one,” one respondent wrote. 

Another team of quhackers also based their project on quantum matching algorithms but instead leveraged the algorithms’ power for medical care. The team built a mobile app that matches organ donors to patients, earning them the hackathon’s top social impact award. 

But they almost didn’t go through with their project. “At one point, we were considering scrapping the whole thing because we thought we couldn’t implement the algorithm,” says Alma Alex, one of the developers. After talking with their hackathon mentor for advice, though, the team learned that another group was working on a similar type of project — incidentally, the MITqute team. Knowing that others were tackling the same problem inspired them to persevere.

A sense of community also helped to motivate other quhackers. For one of the challenges, quhackers were tasked with hacking into 13 virtual quantum vaults. Teams could see each other’s progress on each vault in real time on a leaderboard, and this knowledge informed their strategies. When the first vault was successfully hacked by a team, progress from many other teams spiked on that vault and slowed down on others, says Daiwei Zhu, a quantum applications scientist at IonQ and one of the challenge’s two architects.

The vault challenge may appear to be just a fun series of puzzles, but the solutions can be used in quantum computers to improve their efficiency and accuracy. To hack into a vault, quhackers had to first figure out its secret key — an unknown quantum state — using a maximum of 20 probing tests. Then, they had to change the key’s state to a target state. These types of characterizations and modifications of quantum states are “fundamental” for quantum computers to work, says Jason Iaconis, a quantum applications engineer at IonQ and the challenge’s other architect. 

But the best way to characterize and modify states is not yet clear. “Some of the [vaults] we [didn’t] even know how to solve ourselves,” Zhu says. At the end of the hackathon, six vaults had at least one team mostly hack into them. (In the quantum world where gray areas exist, it’s possible to partly hack into a vault.)

The community of scientists and engineers formed at iQuHACK persists beyond the weekend, and many members continue to grow the community outside the hackathon. Inspired quhackers have gone on to start their own quantum computing clubs at their universities. A few years ago, a group of undergraduate quhackers from different universities formed a Quantum Coalition that now hosts their own quantum hackathons. “It’s crazy to see how the hackathon itself spreads and how many people start their own initiatives,” co-chair Zaidenberg says. 

The three-day hackathon opened with a keynote from MIT Professor Will Oliver, which included an overview of basic quantum computing concepts, current challenges, and computing technologies. Following that were industry talks and a panel of six industry and academic quantum experts, including MIT Professor Peter Shor, who is known for developing one of the most famous quantum algorithms. The panelists discussed current challenges, future applications, the importance of collaboration, and the need for ample testing.

Later, sponsors held technical workshops where quhackers could learn the nitty-gritty details of programming on specific quantum platforms. Day one closed out with a talk by research scientist Xinghui Yin on the role of quantum technology at LIGO, the Laser Interferometer Gravitational-Wave Observatory that first detected gravitational waves. The next day, the hackathon’s challenges were announced at 10 a.m., and hacking kicked off at the MIT InnovationHQ. In the afternoon, attendees could also tour MIT quantum computing labs.

Hacking continued overnight at the MIT Museum and ended back at MIT iHQ at 10 a.m. on the final day. Quhackers then presented their projects to panels of judges. Afterward, industry speakers gave lightning talks about each of their company’s latest quantum technologies and future directions. The hackathon ended with a closing ceremony, where sponsors announced the awards for each of the 10 challenges. 

The hackathon was captured in a three-part video by Albert Figurt, a resident artist at MIT. Figurt shot and edited the footage in parallel with the hackathon. Each part represented one day of the hackathon and was released on the subsequent day.

Throughout the weekend, quhackers and sponsors consistently praised the hackathon’s execution and atmosphere. “That was amazing … never felt so much better, one of the best hackathons I did from over 30 hackathons I attended,” Abdullah Kazi, a quhacker, wrote on the iQuHACK Slack.

Ultimately, “[we wanted to] help people to meet each other,” co-chair Buzzi says. “The impact [of iQuHACK] is scientific in some way, but it’s very human at the most important level.”

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