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This is how we lost control of our faces

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This is how we lost control of our faces


Deborah Raji, a fellow at nonprofit Mozilla, and Genevieve Fried, who advises members of the US Congress on algorithmic accountability, examined over 130 facial-recognition data sets compiled over 43 years. They found that researchers, driven by the exploding data requirements of deep learning, gradually abandoned asking for people’s consent. This has led more and more of people’s personal photos to be incorporated into systems of surveillance without their knowledge.

It has also led to far messier data sets: they may unintentionally include photos of minors, use racist and sexist labels, or have inconsistent quality and lighting. The trend could help explain the growing number of cases in which facial-recognition systems have failed with troubling consequences, such as the false arrests of two Black men in the Detroit area last year.

People were extremely cautious about collecting, documenting, and verifying face data in the early days, says Raji. “Now we don’t care anymore. All of that has been abandoned,” she says. “You just can’t keep track of a million faces. After a certain point, you can’t even pretend that you have control.”

A history of facial-recognition data

The researchers identified four major eras of facial recognition, each driven by an increasing desire to improve the technology. The first phase, which ran until the 1990s, was largely characterized by manually intensive and computationally slow methods.

But then, spurred by the realization that facial recognition could track and identify individuals more effectively than fingerprints, the US Department of Defense pumped $6.5 million into creating the first large-scale face data set. Over 15 photography sessions in three years, the project captured 14,126 images of 1,199 individuals. The Face Recognition Technology (FERET) database was released in 1996.

The following decade saw an uptick in academic and commercial facial-recognition research, and many more data sets were created. The vast majority were sourced through photo shoots like FERET’s and had full participant consent. Many also included meticulous metadata, Raji says, such as the age and ethnicity of subjects, or illumination information. But these early systems struggled in real-world settings, which drove researchers to seek larger and more diverse data sets.

In 2007, the release of the Labeled Faces in the Wild (LFW) data set opened the floodgates to data collection through web search. Researchers began downloading images directly from Google, Flickr, and Yahoo without concern for consent. LFW also relaxed standards around the inclusion of minors, using photos found with search terms like “baby,” “juvenile,” and “teen” to increase diversity. This process made it possible to create significantly larger data sets in a short time, but facial recognition still faced many of the same challenges as before. This pushed researchers to seek yet more methods and data to overcome the technology’s poor performance.

Then, in 2014, Facebook used its user photos to train a deep-learning model called DeepFace. While the company never released the data set, the system’s superhuman performance elevated deep learning to the de facto method for analyzing faces. This is when manual verification and labeling became nearly impossible as data sets grew to tens of millions of photos, says Raji. It’s also when really strange phenomena start appearing, like auto-generated labels that include offensive terminology.

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Donald ’67, SM ’69, and Glenda Mattes

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Donald ’67, SM ’69, and Glenda Mattes


Don Mattes started giving to the Picower Institute for Learning and Memory at MIT before he himself was diagnosed with Alzheimer’s disease. Since his death in 2020, his wife, Glenda, has carried forward Don’s passion for its work. “My wish is that no one ever has to go through the horrors of Alzheimer’s disease ever again,” Glenda says. The Matteses have also supported the Koch Institute for Integrative Cancer Research at MIT.

Legacy sparks hope. An early key employee of Andover Controls who later ran the company’s European operations, Don visited six continents with Glenda during their 30-year marriage—often to ski or bicycle. “Don’s was a life well lived, just too short,” Glenda says. The couple made provisions in their estate plan to support the Picower Institute. After Don died, Glenda made a gift to MIT of real estate that established both endowed and current-use funds there to support research on Alzheimer’s, dementia, and other neurodegenerative diseases. Glenda is a cancer survivor, and the gift also endowed a fund in the couple’s name at the Koch Institute.

Great discoveries being made at MIT: “Don always said the best thing he got from MIT was being taught how to think,” Glenda says. “MIT is an amazing place. Picower Institute director Li-Huei Tsai and her team are doing more than looking for a treatment for Alzheimer’s. They’re looking for the root cause of the disease. I am also fascinated with the Koch’s melding of engineering and biology. The chances they are going to solve the cancer issue someday are very high.” 

Help MIT build a better world.
For more information, contact Amy Goldman: (617) 253-4082;  goldmana@mit.edu. Or visit giving.mit.edu/planned-giving.

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Investing in women pays off

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Investing in women pays off


“Starting a business is a privilege,” says Burton O’Toole, who worked at various startups before launching and later selling AdMass, her own marketing technology company. The company gave her access to the HearstLab program in 2016, but she soon discovered that she preferred the investment aspect and became a vice president at HearstLab a year later. “To empower some of the smartest women to do what they love is great,” she says. But in addition to rooting for women, Burton O’Toole loves the work because it’s a great market opportunity. 

“Research shows female-led teams see two and a half times higher returns compared to male-led teams,” she says, adding that women and people of color tend to build more diverse teams and therefore benefit from varied viewpoints and perspectives. She also explains that companies with women on their founding teams are likely to get acquired or go public sooner. “Despite results like this, just 2.3% of venture capital funding goes to teams founded by women. It’s still amazing to me that more investors aren’t taking this data more seriously,” she says. 

Burton O’Toole—who earned a BS from Duke in 2007 before getting an MS and PhD from MIT, all in mechanical engineering—has been a “data nerd” since she can remember. In high school she wanted to become an actuary. “Ten years ago, I never could have imagined this work; I like the idea of doing something in 10 more years I couldn’t imagine now,” she says. 

When starting a business, Burton O’Toole says, “women tend to want all their ducks in a row before they act. They say, ‘I’ll do it when I get this promotion, have enough money, finish this project.’ But there’s only one good way. Make the jump.”

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Preparing for disasters, before it’s too late

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Preparing for disasters, before it’s too late


All too often, the work of developing global disaster and climate resiliency happens when disaster—such as a hurricane, earthquake, or tsunami—has already ravaged entire cities and torn communities apart. But Elizabeth Petheo, MBA ’14, says that recently her work has been focused on preparedness. 

It’s hard to get attention for preparedness efforts, explains Petheo, a principal at Miyamoto International, an engineering and disaster risk reduction consulting firm. “You can always get a lot of attention when there’s a disaster event, but at that point it’s too late,” she adds. 

Petheo leads the firm’s projects and partnerships in the Asia-Pacific region and advises globally on international development and humanitarian assistance. She also works on preparedness in the Asia-Pacific region with the United States Agency for International Development. 

“We’re doing programming on the engagement of the private sector in disaster risk management in Indonesia, which is a very disaster-prone country,” she says. “Smaller and medium-sized businesses are important contributors to job creation and economic development. When they go down, the impact on lives, livelihoods, and the community’s ability to respond and recover effectively is extreme. We work to strengthen their own understanding of their risk and that of their surrounding community, lead them through an action-planning process to build resilience, and link that with larger policy initiatives at the national level.”

Petheo came to MIT with international leadership experience, having managed high-profile global development and risk mitigation initiatives at the World Bank in Washington, DC, as well as with US government agencies and international organizations leading major global humanitarian responses and teams in Sri Lanka and Haiti. But she says her time at Sloan helped her become prepared for this next phase in her career. “Sloan was the experience that put all the pieces together,” she says.

Petheo has maintained strong connections with MIT. In 2018, she received the Margaret L.A. MacVicar ’65, ScD ’67, Award in recognition of her role starting and leading the MIT Sloan Club in Washington, DC, and her work as an inaugural member of the Graduate Alumni Council (GAC). She is also a member of the Friends of the MIT Priscilla King Gray Public Service Center.

“I believe deeply in the power and impact of the Institute’s work and people,” she says. “The moment I graduated, my thought process was, ‘How can I give back, and how can I continue to strengthen the experience of those who will come after me?’”

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