The (robotic) doctor will see you now

In the era of social distancing, using robots for some health care interactions is a promising way to reduce in-person contact between health care workers and sick patients. However, a key question that needs to be answered is how patients will react to a robot entering the exam room.

Researchers from MIT and Brigham and Women’s Hospital recently set out to answer that question. In a study performed in the emergency department at Brigham and Women’s, the team found that a large majority of patients reported that interacting with a health care provider via a video screen mounted on a robot was similar to an in-person interaction with a health care worker.

“We’re actively working on robots that can help provide care to maximize the safety of both the patient and the health care workforce. The results of this study give us some confidence that people are ready and willing to engage with us on those fronts,” says Giovanni Traverso, an MIT assistant professor of mechanical engineering, a gastroenterologist at Brigham and Women’s Hospital, and the senior author of the study.

In a larger online survey conducted nationwide, the researchers also found that a majority of respondents were open to having robots not only assist with patient triage but also perform minor procedures such as taking a nose swab.

Peter Chai, an assistant professor of emergency medicine at Brigham and Women’s Hospital and a research affiliate in Traverso’s lab, is the lead author of the study, which appears today in JAMA Network Open.

Triage by robot

After the Covid-19 pandemic began early last year, Traverso and his colleagues turned their attention toward new strategies to minimize interactions between potentially sick patients and health care workers. To that end, they worked with Boston Dynamics to create a mobile robot that could interact with patients as they waited in the emergency department. The robots were equipped with sensors that allow them to measure vital signs, including skin temperature, breathing rate, pulse rate, and blood oxygen saturation. The robots also carried an iPad that allowed for remote video communication with a health care provider.

This kind of robot could reduce health care workers’ risk of exposure to Covid-19 and help to conserve the personal protective equipment that is needed for each interaction. However, the question still remained whether patients would be receptive to this type of interaction.

“Often as engineers, we think about different solutions, but sometimes they may not be adopted because people are not fully accepting of them,” Traverso says. “So, in this study we were trying to tease that out and understand if the population is receptive to a solution like this one.”

The researchers first conducted a nationwide survey of about 1,000 people, working with a market research company called YouGov. They asked questions regarding the acceptability of robots in health care, including whether people would be comfortable with robots performing not only triage but also other tasks such as performing nasal swabs, inserting a catheter, or turning a patient over in bed. On average, the respondents stated that they were open to these types of interactions.

The researchers then tested one of their robots in the emergency department at Brigham and Women’s Hospital last spring, when Covid-19 cases were surging in Massachusetts. Fifty-one patients were approached in the waiting room or a triage tent and asked if they would be willing to participate in the study, and 41 agreed. These patients were interviewed about their symptoms via video connection, using an iPad carried by a quadruped, dog-like robot developed by Boston Dynamics. More than 90 percent of the participants reported that they were satisfied with the robotic system.

“For the purposes of gathering quick triage information, the patients found the experience to be similar to what they would have experienced talking to a person,” Chai says.

Robotic assistants

The numbers from the study suggest that it could be worthwhile to try to develop robots that can perform procedures that currently require a lot of human effort, such as turning a patient over in bed, the researchers say. Turning Covid-19 patients onto their stomachs, also known as “proning,” has been shown to boost their blood oxygen levels and make breathing easier. Currently the process requires several people to perform. Administering Covid-19 tests is another task that requires a lot of time and effort from health care workers, who could be deployed for other tasks if robots could help perform swabs.

“Surprisingly, people were pretty accepting of the idea of having a robot do a nasal swab, which suggests that potential engineering efforts could go into thinking about building some of these systems,” Chai says.

The MIT team is continuing to develop sensors that can obtain vital sign data from patients remotely, and they are working on integrating these systems into smaller robots that could operate in a variety of environments, such as field hospitals or ambulances.

Other authors of the paper include Farah Dadabhoy, Hen-wei Huang, Jacqueline Chu, Annie Feng, Hien Le, Joy Collins, Marco da Silva, Marc Raibert, Chin Hur, and Edward Boyer. The research was funded by the National Institutes of Health, the Hans and Mavis Lopater Psychosocial Foundation, e-ink corporation, the Karl Van Tassel (1925) Career Development Professorship, MIT’s Department of Mechanical Engineering, and the Brigham and Women’s Hospital Division of Gastroenterology.

When more Covid-19 data doesn’t equal more understanding

Since the start of the Covid-19 pandemic, charts and graphs have helped communicate information about infection rates, deaths, and vaccinations. In some cases, such visualizations can encourage behaviors that reduce virus transmission, like wearing a mask. Indeed, the pandemic has been hailed as the breakthrough moment for data visualization.

But new findings suggest a more complex picture. A study from MIT shows how coronavirus skeptics have marshalled data visualizations online to argue against public health orthodoxy about the benefits of mask mandates. Such “counter-visualizations” are often quite sophisticated, using datasets from official sources and state-of-the-art visualization methods.

The researchers combed through hundreds of thousands of social media posts and found that coronavirus skeptics often deploy counter-visualizations alongside the same “follow-the-data” rhetoric as public health experts, yet the skeptics argue for radically different policies. The researchers conclude that data visualizations aren’t sufficient to convey the urgency of the Covid-19 pandemic, because even the clearest graphs can be interpreted through a variety of belief systems.  

“A lot of people think of metrics like infection rates as objective,” says Crystal Lee. “But they’re clearly not, based on how much debate there is on how to think about the pandemic. That’s why we say data visualizations have become a battleground.”

The research will be presented at the ACM Conference on Human Factors in Computing Systems in May. Lee is the study’s lead author and a PhD student in MIT’s History, Anthropology, Science, Technology, and Society (HASTS) program and MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), as well as a fellow at Harvard University’s Berkman Klein Center for Internet and Society. Co-authors include Graham Jones, a Margaret MacVicar Faculty Fellow in Anthropology; Arvind Satyanarayan, the NBX Career Development Assistant Professor in the Department of Electrical Engineering and Computer Science and CSAIL; Tanya Yang, an MIT undergraduate; and Gabrielle Inchoco, a Wellesley College undergraduate.

As data visualizations rose to prominence early in the pandemic, Lee and her colleagues set out to understand how they were being deployed throughout the social media universe. “An initial hypothesis was that if we had more data visualizations, from data collected in a systematic way, then people would be better informed,” says Lee. To test that hypothesis, her team blended computational techniques with innovative ethnographic methods.

They used their computational approach on Twitter, scraping nearly half a million tweets that referred to both “Covid-19” and “data.” With those tweets, the researchers generated a network graph to find out “who’s retweeting whom and who likes whom,” says Lee. “We basically created a network of communities who are interacting with each other.” Clusters included groups like the “American media community” or “antimaskers.” The researchers found that antimask groups were creating and sharing data visualizations as much as, if not more than, other groups.

And those visualizations weren’t sloppy. “They are virtually indistinguishable from those shared by mainstream sources,” says Satyanarayan. “They are often just as polished as graphs you would expect to encounter in data journalism or public health dashboards.”

“It’s a very striking finding,” says Lee. “It shows that characterizing antimask groups as data-illiterate or not engaging with the data, is empirically false.”

Lee says this computational approach gave them a broad view of Covid-19 data visualizations. “What is really exciting about this quantitative work is that we’re doing this analysis at a huge scale. There’s no way I could have read half a million tweets.”

But the Twitter analysis had a shortcoming. “I think it misses a lot of the granularity of the conversations that people are having,” says Lee. “You can’t necessarily follow a single thread of conversation as it unfolds.” For that, the researchers turned to a more traditional anthropology research method — with an internet-age twist.

Lee’s team followed and analyzed conversations about data visualizations in antimask Facebook groups — a practice they dubbed “deep lurking,” an online version of the ethnographic technique called “deep hanging out.” Lee says “understanding a culture requires you to observe the day-to-day informal goings-on — not just the big formal events. Deep lurking is a way to transpose these traditional ethnography approaches to digital age.”

The qualitative findings from deep lurking appeared consistent with the quantitative Twitter findings. Antimaskers on Facebook weren’t eschewing data. Rather, they discussed how different kinds of data were collected and why. “Their arguments are really quite nuanced,” says Lee. “It’s often a question of metrics.” For example, antimask groups might argue that visualizations of infection numbers could be misleading, in part because of the wide range of uncertainty in infection rates, compared to measurements like the number of deaths. In response, members of the group would often create their own counter-visualizations, even instructing each other in data visualization techniques.

“I’ve been to livestreams where people screen share and look at the data portal from the state of Georgia,” says Lee. “Then they’ll talk about how to download the data and import it into Excel.”

Jones says the antimask groups’ “idea of science is not listening passively as experts at a place like MIT tell everyone else what to believe.” He adds that this kind of behavior marks a new turn for an old cultural current. “Antimaskers’ use of data literacy reflects deep-seated American values of self-reliance and anti-expertise that date back to the founding of the country, but their online activities push those values into new arenas of public life.”

He adds that “making sense of these complex dynamics would have been impossible” without Lee’s “visionary leadership in masterminding an interdisciplinary collaboration that spanned SHASS and CSAIL.”

The mixed methods research “advances our understanding of data visualizations in shaping public perception of science and politics,” says Jevin West, a data scientist at the University of Washington, who was not involved with the research. Data visualizations “carry a veneer of objectivity and scientific precision. But as this paper shows, data visualizations can be used effectively on opposite sides of an issue,” he says. “It underscores the complexity of the problem — that it is not enough to ‘just teach media literacy.’ It requires a more nuanced sociopolitical understanding of those creating and interpreting data graphics.”

Combining computational and anthropological insights led the researchers to a more nuanced understanding of data literacy. Lee says their study reveals that, compared to public health orthodoxy, “antimaskers see the pandemic differently, using data that is quite similar. I still think data analysis is important. But it’s certainly not the salve that I thought it was in terms of convincing people who believe that the scientific establishment is not trustworthy.” Lee says their findings point to “a larger rift in how we think about science and expertise in the U.S.” That same rift runs through issues like climate change and vaccination, where similar dynamics often play out in social media discussions.

To make these results accessible to the public, Lee and her collaborator, CSAIL PhD student Jonathan Zong, led a team of seven MIT undergraduate researchers to develop an interactive narrative where readers can explore the visualizations and conversations for themselves.

Lee describes the team’s research as a first step in making sense of the role of data and visualizations in these broader debates. “Data visualization is not objective. It’s not absolute. It is in fact an incredibly social and political endeavor. We have to be attentive to how people interpret them outside of the scientific establishment.”

This research was funded, in part, by the National Science Foundation and the Social Science Research Council.

MIT and Danish university students unite to envision a more sustainable future

Climate action is among the top priorities for the Institute and one that demands global solutions. With Denmark’s reputation as a leader in sustainable thinking, finding a way to bring the two together presented a natural synergy for the MIT-Denmark program. Part of MIT International Science and Technology Initiatives (MISTI), MIT-Denmark connects students and faculty with institutions and industry in Denmark to advance critical research, build new technologies, and create innovative partnerships. Despite the recent challenges due to pandemic-imposed travel restrictions, developing these meaningful international collaborations continues to be a top priority for both MIT students and their counterparts abroad.

The Green Campus Challenge was launched with these goals in mind, tasking student teams to develop proposals to make a more sustainable campus and also broaden their cross-cultural competencies and learn about how sustainability is perceived in another culture.

“We need to work together to make our future more sustainable, and our campuses are the perfect place to start,” says Madeline Smith, program manager for MIT-Denmark. Smith hosted the event alongside the Confederation of Danish Industry (Dansk Industri) with additional collaboration from the MIT Office of Sustainability and the MIT Design for America Club. In the challenge, students ideated solutions and developed plans to make their university campus more sustainable within the areas of architecture/community spaces, energy, and food/waste. They tackled these issues from a global perspective, working in teams that included both MIT and Danish university students.

MIT students joining the challenge came from a variety of class years and majors, from first-year students to PhD candidates, with interests ranging from computer science to civil engineering to urban planning. Danish university students came from top universities across the country, including Aalborg University (AAU), Copenhagen Business School (CBS), the Technical University of Denmark (DTU), University of Copenhagen (KU), and Southern Denmark University (SDU).

Beyond science and technology

Challenge organizers enhanced the experience by providing student teams with mentorship from campus stakeholders, experts in academia and entrepreneurship, and some of Denmark’s most innovative companies. Danfoss advised students on district energy solutions, while mentors from KU and MIT Office of Sustainability provided information about food and waste systems. Other mentors included representatives from Rambøll, SPACE10, Blue Lobster, EcoTree, and DTU Skylab.

“Working on this event was very exciting for us,” says Miha Bobič, vice president of business development and product portfolio at Danfoss, who joined the Green Campus Challenge both as a mentor and on the jury for finalist pitches. “Due to current circumstances, we could not get the experience of face-to-face meetings and mentorship, but students still showed a great deal of engagement and developed innovative ideas, which, if properly developed, could end up as new startups.”

In between mentorship and team brainstorming, there were workshops to help students develop innovative thinking processes, consider project stakeholders, and learn how to pitch their idea to a sustainability-minded audience. Students found time for some fun as well and joined together for MIT and Denmark-themed trivia, yoga, and even a food waste-preventing cooking class organized by Danish startup, Too Good To Go.  

“It was a great experience diving into ideation, collaborating with our international teammates, learning more about their culture and approach to innovation and sustainability,” says Allison Lee, a master of city planning candidate at MIT.

The event culminated with teams presenting their pitches to a panel of judges from the U.S. and Denmark, including Franklin Carrero-Martinez (U.S. National Academy of Sciences, Engineering, and Math), Kinga Christensen (Dansk Industri), Susy Jones (MIT Sustainability), and Tomas Refslund Poulsen (KU Green Campus Initiative), as well as a jury from Danfoss, which selected a winner to recognize within the field of energy innovation.

“It was inspiring to see talented students from MIT and Danish universities pitching their ideas to create sustainable campuses for the future,” says Kinga Christensen, deputy director general for the Confederation of Danish Industry. “By bringing together their skills and perspectives, alongside the mentorship they received from Danish companies and university experts, they were able to develop some truly innovative sustainability proposals.”

Teams find winning solutions

Winning the grand prize was team Green-(In)-Spire, who proposed a campus sustainability world fair. Their plan would include a designated space on campus to showcase technologies and inventions that address campus sustainability through events and “world fairs.” The team members were Allison Lee (MIT), Anna Worning (AAU), Erik Koors (SDU), John Liu (MIT), and Kiara Wahnschafft (MIT).

Team FreeCyclers received runner-up honors for their idea to create a centralized freecycle space. This space would allow students to donate and pick up items too good to throw away, such as books, kitchen equipment, clothing, and more. The team included Eva Smerekanych (MIT), Isabel Dolp (CBS), Niklas Ludvigsen (CBS), Melissa Møller (AAU), and Shristi Rijal (SDU).

For innovations in energy, the Danfoss Prize was awarded to the team UniGreen Farmers for their idea to develop UniGreen Farms, university-led urban rooftop research facilities where interdisciplinary research could take place between senior and entry-level researchers and students. Team members were Brian Li (MIT), Federico D’Ascanio (KU), Frederik Bøllingtoft (AAU), Julia Romero (KU), and Kosmas Subashi (KU).

“This pandemic hasn’t made international collaboration easy,” says Smith. “But seeing students from MIT and Danish universities finish the Green Campus Challenge both eager to make a sustainability impact on their campus community and excited about the international network they’ve developed demonstrates the value of these types of cross-cultural experiences.”

With support from the Danish Industry Foundation and the Confederation of Danish Industry, MIT-Denmark connects MIT students and faculty with institutions and industry in Denmark. MISTI’s global experiential learning programs are made possible through the generosity of individuals, corporations, and foundations. For more information, email misti@mit.edu or contact country program managers directly. MISTI is an experiential program in the Center for International Studies within the School of Humanities, Arts, and Social Sciences.

Helping soft robots turn rigid on demand

Imagine a robot.

Perhaps you’ve just conjured a machine with a rigid, metallic exterior. While robots armored with hard exoskeletons are common, they’re not always ideal. Soft-bodied robots, inspired by fish or other squishy creatures, might better adapt to changing environments and work more safely with people.

Roboticists generally have to decide whether to design a hard- or soft-bodied robot for a particular task. But that tradeoff may no longer be necessary.

Working with computer simulations, MIT researchers have developed a concept for a soft-bodied robot that can turn rigid on demand. The approach could enable a new generation of robots that combine the strength and precision of rigid robots with the fluidity and safety of soft ones.

“This is the first step in trying to see if we can get the best of both worlds,” says James Bern, the paper’s lead author and a postdoc in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

Bern will present the research at the IEEE International Conference on Soft Robotics next month. Bern’s advisor, Daniela Rus, who is the CSAIL director and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, is the paper’s other author.

Roboticists have experimented with myriad mechanisms to operate soft robots, including inflating balloon-like chambers in a robot’s arm or grabbing objects with vacuum-sealed coffee grounds. However, a key unsolved challenge for soft robotics is control — how to drive the robot’s actuators in order to achieve a given goal.

Until recently, most soft robots were controlled manually, but in 2017 Bern and his colleagues proposed that an algorithm could take the reigns. Using a simulation to help control a cable-driven soft robot, they picked a target position for the robot and had a computer figure out how much to pull on each of the cables in order to get there. A similar sequence happens in our bodies each time we reach for something: A target position for our hand is translated into contractions of the muscles in our arm.

Now, Bern and his colleagues are using similar techniques to ask a question that goes beyond the robot’s movement: “If I pull the cables in just the right way, can I get the robot to act stiff?” Bern says he can — at least in a computer simulation — thanks to inspiration from the human arm. While contracting the biceps alone can bend your elbow to a certain degree, contracting the biceps and triceps simultaneously can lock your arm rigidly in that position. Put simply, “you can get stiffness by pulling on both sides of something,” says Bern. So, he applied the same principle to his robots.

The researchers’ paper lays out a way to simultaneously control the position and stiffness of a cable-driven soft robot. The method takes advantage of the robots’ multiple cables — using some to twist and turn the body, while using others to counterbalance each other to tweak the robot’s rigidity. Bern emphasizes that the advance isn’t a revolution in mechanical engineering, but rather a new twist on controlling cable-driven soft robots.

“This is an intuitive way of expanding how you can control a soft robot,” he says. “It’s just encoding that idea [of on-demand rigidity] into something a computer can work with.” Bern hopes his roadmap will one day allow users to control a robot’s rigidity as easily as its motion.

On the computer, Bern used his roadmap to simulate movement and rigidity adjustment in robots of various shapes. He tested how well the robots, when stiffened, could resist displacement when pushed. Generally, the robots remained rigid as intended, though they were not equally resistant from all angles.

“Dual-mode materials that can change stiffness are always fascinating,” says Muhammad Hussain, an electrical engineer at the University of California at Berkeley, who was not involved with the research. He suggested potential applications in health care, where soft robots could one day travel through the blood stream then stiffen to perform microsurgery at a particular site in the body. Hussain say Bern’s demonstration “shows a viable path toward that future.”

Bern is building a prototype robot to test out his rigidity-on-demand control system. But he hopes to one day take the technology out of the lab. “Interacting with humans is definitely a vision for soft robotics,” he says. Bern points to potential applications in caring for human patients, where a robot’s softness could enhance safety, while its ability to become rigid could allow for lifting when necessary.

“The core message is to make it easy to control robots’ stiffness,” says Bern. “Let’s start making soft robots that are safe but can also act rigid on demand, and expand the spectrum of tasks robots can perform.”

Helping soft robots turn rigid on demand

Imagine a robot.

Perhaps you’ve just conjured a machine with a rigid, metallic exterior. While robots armored with hard exoskeletons are common, they’re not always ideal. Soft-bodied robots, inspired by fish or other squishy creatures, might better adapt to changing environments and work more safely with people.

Roboticists generally have to decide whether to design a hard- or soft-bodied robot for a particular task. But that tradeoff may no longer be necessary.

Working with computer simulations, MIT researchers have developed a concept for a soft-bodied robot that can turn rigid on demand. The approach could enable a new generation of robots that combine the strength and precision of rigid robots with the fluidity and safety of soft ones.

“This is the first step in trying to see if we can get the best of both worlds,” says James Bern, the paper’s lead author and a postdoc in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

Bern will present the research at the IEEE International Conference on Soft Robotics next month. Bern’s advisor, Daniela Rus, who is the CSAIL director and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, is the paper’s other author.

Roboticists have experimented with myriad mechanisms to operate soft robots, including inflating balloon-like chambers in a robot’s arm or grabbing objects with vacuum-sealed coffee grounds. However, a key unsolved challenge for soft robotics is control — how to drive the robot’s actuators in order to achieve a given goal.

Until recently, most soft robots were controlled manually, but in 2017 Bern and his colleagues proposed that an algorithm could take the reigns. Using a simulation to help control a cable-driven soft robot, they picked a target position for the robot and had a computer figure out how much to pull on each of the cables in order to get there. A similar sequence happens in our bodies each time we reach for something: A target position for our hand is translated into contractions of the muscles in our arm.

Now, Bern and his colleagues are using similar techniques to ask a question that goes beyond the robot’s movement: “If I pull the cables in just the right way, can I get the robot to act stiff?” Bern says he can — at least in a computer simulation — thanks to inspiration from the human arm. While contracting the biceps alone can bend your elbow to a certain degree, contracting the biceps and triceps simultaneously can lock your arm rigidly in that position. Put simply, “you can get stiffness by pulling on both sides of something,” says Bern. So, he applied the same principle to his robots.

The researchers’ paper lays out a way to simultaneously control the position and stiffness of a cable-driven soft robot. The method takes advantage of the robots’ multiple cables — using some to twist and turn the body, while using others to counterbalance each other to tweak the robot’s rigidity. Bern emphasizes that the advance isn’t a revolution in mechanical engineering, but rather a new twist on controlling cable-driven soft robots.

“This is an intuitive way of expanding how you can control a soft robot,” he says. “It’s just encoding that idea [of on-demand rigidity] into something a computer can work with.” Bern hopes his roadmap will one day allow users to control a robot’s rigidity as easily as its motion.

On the computer, Bern used his roadmap to simulate movement and rigidity adjustment in robots of various shapes. He tested how well the robots, when stiffened, could resist displacement when pushed. Generally, the robots remained rigid as intended, though they were not equally resistant from all angles.

“Dual-mode materials that can change stiffness are always fascinating,” says Muhammad Hussain, an electrical engineer at the University of California at Berkeley, who was not involved with the research. He suggested potential applications in health care, where soft robots could one day travel through the blood stream then stiffen to perform microsurgery at a particular site in the body. Hussain say Bern’s demonstration “shows a viable path toward that future.”

Bern is building a prototype robot to test out his rigidity-on-demand control system. But he hopes to one day take the technology out of the lab. “Interacting with humans is definitely a vision for soft robotics,” he says. Bern points to potential applications in caring for human patients, where a robot’s softness could enhance safety, while its ability to become rigid could allow for lifting when necessary.

“The core message is to make it easy to control robots’ stiffness,” says Bern. “Let’s start making soft robots that are safe but can also act rigid on demand, and expand the spectrum of tasks robots can perform.”

Fostering ethical thinking in computing

Traditional computer scientists and engineers are trained to develop solutions for specific needs, but aren’t always trained to consider their broader implications. Each new technology generation, and particularly the rise of artificial intelligence, leads to new kinds of systems, new ways of creating tools, and new forms of data, for which norms, rules, and laws frequently have yet to catch up. The kinds of impact that such innovations have in the world has often not been apparent until many years later.

As part of the efforts in Social and Ethical Responsibilities of Computing (SERC) within the MIT Stephen A. Schwarzman College of Computing, a new case studies series examines social, ethical, and policy challenges of present-day efforts in computing with the aim of facilitating the development of responsible “habits of mind and action” for those who create and deploy computing technologies.

“Advances in computing have undeniably changed much of how we live and work. Understanding and incorporating broader social context is becoming ever more critical,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing. “This case study series is designed to be a basis for discussions in the classroom and beyond, regarding social, ethical, economic, and other implications so that students and researchers can pursue the development of technology across domains in a holistic manner that addresses these important issues.”

A modular system

By design, the case studies are brief and modular to allow users to mix and match the content to fit a variety of pedagogical needs. Series editors David Kaiser and Julie Shah, who are the associate deans for SERC, structured the cases primarily to be appropriate for undergraduate instruction across a range of classes and fields of study.

“Our goal was to provide a seamless way for instructors to integrate cases into an existing course or cluster several cases together to support a broader module within a course. They might also use the cases as a starting point to design new courses that focus squarely on themes of social and ethical responsibilities of computing,” says Kaiser, the Germeshausen Professor of the History of Science and professor of physics.

Shah, an associate professor of aeronautics and astronautics and a roboticist who designs systems in which humans and machines operate side by side, expects that the cases will also be of interest to those outside of academia, including computing professionals, policy specialists, and general readers. In curating the series, Shah says that “we interpret ‘social and ethical responsibilities of computing’ broadly to focus on perspectives of people who are affected by various technologies, as well as focus on perspectives of designers and engineers.”

The cases are not limited to a particular format and can take shape in various forms — from a magazine-like feature article or Socratic dialogues to choose-your-own-adventure stories or role-playing games grounded in empirical research. Each case study is brief, but includes accompanying notes and references to facilitate more in-depth exploration of a given topic. Multimedia projects will also be considered. “The main goal is to present important material — based on original research — in engaging ways to broad audiences of non-specialists,” says Kaiser.

The SERC case studies are specially commissioned and written by scholars who conduct research centrally on the subject of the piece. Kaiser and Shah approached researchers from within MIT as well as from other academic institutions to bring in a mix of diverse voices on a spectrum of topics. Some cases focus on a particular technology or on trends across platforms, while others assess social, historical, philosophical, legal, and cultural facets that are relevant for thinking critically about current efforts in computing and data sciences.

The cases published in the inaugural issue place readers in various settings that challenge them to consider the social and ethical implications of computing technologies, such as how social media services and surveillance tools are built; the racial disparities that can arise from deploying facial recognition technology in unregulated, real-world settings; the biases of risk prediction algorithms in the criminal justice system; and the politicization of data collection.

“Most of us agree that we want computing to work for social good, but which good? Whose good? Whose needs and values and worldviews are prioritized and whose are overlooked?” says Catherine D’Ignazio, an assistant professor of urban science and planning and director of the Data + Feminism Lab at MIT.

D’Ignazio’s case for the series, co-authored with Lauren Klein, an associate professor in the English and Quantitative Theory and Methods departments at Emory University, introduces readers to the idea that while data are useful, they are not always neutral. “These case studies help us understand the unequal histories that shape our technological systems as well as study their disparate outcomes and effects. They are an exciting step towards holistic, sociotechnical thinking and making.”

Rigorously reviewed

Kaiser and Shah formed an editorial board composed of 55 faculty members and senior researchers associated with 19 departments, labs, and centers at MIT, and instituted a rigorous peer-review policy model commonly adopted by specialized journals. Members of the editorial board will also help commission topics for new cases and help identify authors for a given topic.

For each submission, the series editors collect four to six peer reviews, with reviewers mostly drawn from the editorial board. For each case, half the reviewers come from fields in computing and data sciences and half from fields in the humanities, arts, and social sciences, to ensure balance of topics and presentation within a given case study and across the series.

“Over the past two decades I’ve become a bit jaded when it comes to the academic review process, and so I was particularly heartened to see such care and thought put into all of the reviews,” says Hany Farid, a professor at the University of California at Berkeley with a joint appointment in the Department of Electrical Engineering and Computer Sciences and the School of Information. “The constructive review process made our case study significantly stronger.”

Farid’s case, “The Dangers of Risk Prediction in the Criminal Justice System,” which he penned with Julia Dressel, recently a student of computer science at Dartmouth College, is one of the four commissioned pieces featured in the inaugural issue.

Cases are additionally reviewed by undergraduate volunteers, who help the series editors gauge each submission for balance, accessibility for students in multiple fields of study, and possibilities for adoption in specific courses. The students also work with them to create original homework problems and active learning projects to accompany each case study, to further facilitate adoption of the original materials across a range of existing undergraduate subjects.

“I volunteered to work with this group because I believe that it’s incredibly important for those working in computer science to include thinking about ethics not as an afterthought, but integrated into every step and decision that is made, says Annie Snyder, a mathematical economics sophomore and a member of the MIT Schwarzman College of Computing’s Undergraduate Advisory Group. “While this is a massive issue to take on, this project is an amazing opportunity to start building an ethical culture amongst the incredibly talented students at MIT who will hopefully carry it forward into their own projects and workplace.”

New sets of case studies, produced with support from the MIT Press’ Open Publishing Services program, will be published twice a year via the Knowledge Futures Group’s PubPub platform. The SERC case studies are made available for free on an open-access basis, under Creative Commons licensing terms. Authors retain copyright, enabling them to reuse and republish their work in more specialized scholarly publications.

“It was important to us to approach this project in an inclusive way and lower the barrier for people to be able to access this content. These are complex issues that we need to deal with, and we hope that by making the cases widely available, more people will engage in social and ethical considerations as they’re studying and developing computing technologies,” says Shah.

Fostering ethical thinking in computing

Traditional computer scientists and engineers are trained to develop solutions for specific needs, but aren’t always trained to consider their broader implications. Each new technology generation, and particularly the rise of artificial intelligence, leads to new kinds of systems, new ways of creating tools, and new forms of data, for which norms, rules, and laws frequently have yet to catch up. The kinds of impact that such innovations have in the world has often not been apparent until many years later.

As part of the efforts in Social and Ethical Responsibilities of Computing (SERC) within the MIT Stephen A. Schwarzman College of Computing, a new case studies series examines social, ethical, and policy challenges of present-day efforts in computing with the aim of facilitating the development of responsible “habits of mind and action” for those who create and deploy computing technologies.

“Advances in computing have undeniably changed much of how we live and work. Understanding and incorporating broader social context is becoming ever more critical,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing. “This case study series is designed to be a basis for discussions in the classroom and beyond, regarding social, ethical, economic, and other implications so that students and researchers can pursue the development of technology across domains in a holistic manner that addresses these important issues.”

A modular system

By design, the case studies are brief and modular to allow users to mix and match the content to fit a variety of pedagogical needs. Series editors David Kaiser and Julie Shah, who are the associate deans for SERC, structured the cases primarily to be appropriate for undergraduate instruction across a range of classes and fields of study.

“Our goal was to provide a seamless way for instructors to integrate cases into an existing course or cluster several cases together to support a broader module within a course. They might also use the cases as a starting point to design new courses that focus squarely on themes of social and ethical responsibilities of computing,” says Kaiser, the Germeshausen Professor of the History of Science and professor of physics.

Shah, an associate professor of aeronautics and astronautics and a roboticist who designs systems in which humans and machines operate side by side, expects that the cases will also be of interest to those outside of academia, including computing professionals, policy specialists, and general readers. In curating the series, Shah says that “we interpret ‘social and ethical responsibilities of computing’ broadly to focus on perspectives of people who are affected by various technologies, as well as focus on perspectives of designers and engineers.”

The cases are not limited to a particular format and can take shape in various forms — from a magazine-like feature article or Socratic dialogues to choose-your-own-adventure stories or role-playing games grounded in empirical research. Each case study is brief, but includes accompanying notes and references to facilitate more in-depth exploration of a given topic. Multimedia projects will also be considered. “The main goal is to present important material — based on original research — in engaging ways to broad audiences of non-specialists,” says Kaiser.

The SERC case studies are specially commissioned and written by scholars who conduct research centrally on the subject of the piece. Kaiser and Shah approached researchers from within MIT as well as from other academic institutions to bring in a mix of diverse voices on a spectrum of topics. Some cases focus on a particular technology or on trends across platforms, while others assess social, historical, philosophical, legal, and cultural facets that are relevant for thinking critically about current efforts in computing and data sciences.

The cases published in the inaugural issue place readers in various settings that challenge them to consider the social and ethical implications of computing technologies, such as how social media services and surveillance tools are built; the racial disparities that can arise from deploying facial recognition technology in unregulated, real-world settings; the biases of risk prediction algorithms in the criminal justice system; and the politicization of data collection.

“Most of us agree that we want computing to work for social good, but which good? Whose good? Whose needs and values and worldviews are prioritized and whose are overlooked?” says Catherine D’Ignazio, an assistant professor of urban science and planning and director of the Data + Feminism Lab at MIT.

D’Ignazio’s case for the series, co-authored with Lauren Klein, an associate professor in the English and Quantitative Theory and Methods departments at Emory University, introduces readers to the idea that while data are useful, they are not always neutral. “These case studies help us understand the unequal histories that shape our technological systems as well as study their disparate outcomes and effects. They are an exciting step towards holistic, sociotechnical thinking and making.”

Rigorously reviewed

Kaiser and Shah formed an editorial board composed of 55 faculty members and senior researchers associated with 19 departments, labs, and centers at MIT, and instituted a rigorous peer-review policy model commonly adopted by specialized journals. Members of the editorial board will also help commission topics for new cases and help identify authors for a given topic.

For each submission, the series editors collect four to six peer reviews, with reviewers mostly drawn from the editorial board. For each case, half the reviewers come from fields in computing and data sciences and half from fields in the humanities, arts, and social sciences, to ensure balance of topics and presentation within a given case study and across the series.

“Over the past two decades I’ve become a bit jaded when it comes to the academic review process, and so I was particularly heartened to see such care and thought put into all of the reviews,” says Hany Farid, a professor at the University of California at Berkeley with a joint appointment in the Department of Electrical Engineering and Computer Sciences and the School of Information. “The constructive review process made our case study significantly stronger.”

Farid’s case, “The Dangers of Risk Prediction in the Criminal Justice System,” which he penned with Julia Dressel, recently a student of computer science at Dartmouth College, is one of the four commissioned pieces featured in the inaugural issue.

Cases are additionally reviewed by undergraduate volunteers, who help the series editors gauge each submission for balance, accessibility for students in multiple fields of study, and possibilities for adoption in specific courses. The students also work with them to create original homework problems and active learning projects to accompany each case study, to further facilitate adoption of the original materials across a range of existing undergraduate subjects.

“I volunteered to work with this group because I believe that it’s incredibly important for those working in computer science to include thinking about ethics not as an afterthought, but integrated into every step and decision that is made, says Annie Snyder, a mathematical economics sophomore and a member of the MIT Schwarzman College of Computing’s Undergraduate Advisory Group. “While this is a massive issue to take on, this project is an amazing opportunity to start building an ethical culture amongst the incredibly talented students at MIT who will hopefully carry it forward into their own projects and workplace.”

New sets of case studies, produced with support from the MIT Press’ Open Publishing Services program, will be published twice a year via the Knowledge Futures Group’s PubPub platform. The SERC case studies are made available for free on an open-access basis, under Creative Commons licensing terms. Authors retain copyright, enabling them to reuse and republish their work in more specialized scholarly publications.

“It was important to us to approach this project in an inclusive way and lower the barrier for people to be able to access this content. These are complex issues that we need to deal with, and we hope that by making the cases widely available, more people will engage in social and ethical considerations as they’re studying and developing computing technologies,” says Shah.

Fostering ethical thinking in computing

Traditional computer scientists and engineers are trained to develop solutions for specific needs, but aren’t always trained to consider their broader implications. Each new technology generation, and particularly the rise of artificial intelligence, leads to new kinds of systems, new ways of creating tools, and new forms of data, for which norms, rules, and laws frequently have yet to catch up. The kinds of impact that such innovations have in the world has often not been apparent until many years later.

As part of the efforts in Social and Ethical Responsibilities of Computing (SERC) within the MIT Stephen A. Schwarzman College of Computing, a new case studies series examines social, ethical, and policy challenges of present-day efforts in computing with the aim of facilitating the development of responsible “habits of mind and action” for those who create and deploy computing technologies.

“Advances in computing have undeniably changed much of how we live and work. Understanding and incorporating broader social context is becoming ever more critical,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing. “This case study series is designed to be a basis for discussions in the classroom and beyond, regarding social, ethical, economic, and other implications so that students and researchers can pursue the development of technology across domains in a holistic manner that addresses these important issues.”

A modular system

By design, the case studies are brief and modular to allow users to mix and match the content to fit a variety of pedagogical needs. Series editors David Kaiser and Julie Shah, who are the associate deans for SERC, structured the cases primarily to be appropriate for undergraduate instruction across a range of classes and fields of study.

“Our goal was to provide a seamless way for instructors to integrate cases into an existing course or cluster several cases together to support a broader module within a course. They might also use the cases as a starting point to design new courses that focus squarely on themes of social and ethical responsibilities of computing,” says Kaiser, the Germeshausen Professor of the History of Science and professor of physics.

Shah, an associate professor of aeronautics and astronautics and a roboticist who designs systems in which humans and machines operate side by side, expects that the cases will also be of interest to those outside of academia, including computing professionals, policy specialists, and general readers. In curating the series, Shah says that “we interpret ‘social and ethical responsibilities of computing’ broadly to focus on perspectives of people who are affected by various technologies, as well as focus on perspectives of designers and engineers.”

The cases are not limited to a particular format and can take shape in various forms — from a magazine-like feature article or Socratic dialogues to choose-your-own-adventure stories or role-playing games grounded in empirical research. Each case study is brief, but includes accompanying notes and references to facilitate more in-depth exploration of a given topic. Multimedia projects will also be considered. “The main goal is to present important material — based on original research — in engaging ways to broad audiences of non-specialists,” says Kaiser.

The SERC case studies are specially commissioned and written by scholars who conduct research centrally on the subject of the piece. Kaiser and Shah approached researchers from within MIT as well as from other academic institutions to bring in a mix of diverse voices on a spectrum of topics. Some cases focus on a particular technology or on trends across platforms, while others assess social, historical, philosophical, legal, and cultural facets that are relevant for thinking critically about current efforts in computing and data sciences.

The cases published in the inaugural issue place readers in various settings that challenge them to consider the social and ethical implications of computing technologies, such as how social media services and surveillance tools are built; the racial disparities that can arise from deploying facial recognition technology in unregulated, real-world settings; the biases of risk prediction algorithms in the criminal justice system; and the politicization of data collection.

“Most of us agree that we want computing to work for social good, but which good? Whose good? Whose needs and values and worldviews are prioritized and whose are overlooked?” says Catherine D’Ignazio, an assistant professor of urban science and planning and director of the Data + Feminism Lab at MIT.

D’Ignazio’s case for the series, co-authored with Lauren Klein, an associate professor in the English and Quantitative Theory and Methods departments at Emory University, introduces readers to the idea that while data are useful, they are not always neutral. “These case studies help us understand the unequal histories that shape our technological systems as well as study their disparate outcomes and effects. They are an exciting step towards holistic, sociotechnical thinking and making.”

Rigorously reviewed

Kaiser and Shah formed an editorial board composed of 55 faculty members and senior researchers associated with 19 departments, labs, and centers at MIT, and instituted a rigorous peer-review policy model commonly adopted by specialized journals. Members of the editorial board will also help commission topics for new cases and help identify authors for a given topic.

For each submission, the series editors collect four to six peer reviews, with reviewers mostly drawn from the editorial board. For each case, half the reviewers come from fields in computing and data sciences and half from fields in the humanities, arts, and social sciences, to ensure balance of topics and presentation within a given case study and across the series.

“Over the past two decades I’ve become a bit jaded when it comes to the academic review process, and so I was particularly heartened to see such care and thought put into all of the reviews,” says Hany Farid, a professor at the University of California at Berkeley with a joint appointment in the Department of Electrical Engineering and Computer Sciences and the School of Information. “The constructive review process made our case study significantly stronger.”

Farid’s case, “The Dangers of Risk Prediction in the Criminal Justice System,” which he penned with Julia Dressel, recently a student of computer science at Dartmouth College, is one of the four commissioned pieces featured in the inaugural issue.

Cases are additionally reviewed by undergraduate volunteers, who help the series editors gauge each submission for balance, accessibility for students in multiple fields of study, and possibilities for adoption in specific courses. The students also work with them to create original homework problems and active learning projects to accompany each case study, to further facilitate adoption of the original materials across a range of existing undergraduate subjects.

“I volunteered to work with this group because I believe that it’s incredibly important for those working in computer science to include thinking about ethics not as an afterthought, but integrated into every step and decision that is made, says Annie Snyder, a mathematical economics sophomore and a member of the MIT Schwarzman College of Computing’s Undergraduate Advisory Group. “While this is a massive issue to take on, this project is an amazing opportunity to start building an ethical culture amongst the incredibly talented students at MIT who will hopefully carry it forward into their own projects and workplace.”

New sets of case studies, produced with support from the MIT Press’ Open Publishing Services program, will be published twice a year via the Knowledge Futures Group’s PubPub platform. The SERC case studies are made available for free on an open-access basis, under Creative Commons licensing terms. Authors retain copyright, enabling them to reuse and republish their work in more specialized scholarly publications.

“It was important to us to approach this project in an inclusive way and lower the barrier for people to be able to access this content. These are complex issues that we need to deal with, and we hope that by making the cases widely available, more people will engage in social and ethical considerations as they’re studying and developing computing technologies,” says Shah.

MIT Solve announces 2021 global challenges

On March 1, MIT Solve launched its 2021 Global Challenges, with over $1.5 million in prize funding available to innovators worldwide.

Solve seeks tech-based solutions from social entrepreneurs around the world that address five challenges. Anyone, anywhere can apply to address the challenges by the June 16 deadline. Solve also announced Eric Yuan, founder and CEO of Zoom, and Karlie Kloss, founder and CEO of Kode with Klossy, as 2021 Challenge Ambassadors. 

To help with the challenge application process, Solve runs a course with MITx entitled “Business and Impact Planning for Social Enterprises,” which introduces core business model and theory-of-change concepts to early stage entrepreneurs. 

Finalists will be invited to attend Solve Challenge Finals on Sept. 19 in New York during U.N. General Assembly week. At the event, they will pitch their solutions to Solve’s Challenge Leadership Groups, judging panels comprised of industry leaders and MIT faculty. The judges will select the most promising solutions as Solver teams.

“After a year of turmoil, including a major threat to our collective health, disruption in schooling, lack of access to digital connectivity and meaningful work, a reckoning in the U.S. after centuries of institutionalized racism, or worsening natural hazards — supporting diverse innovators who are solving these challenges is more urgent than ever,” says Alex Amouyel, executive director of MIT Solve. “Solve is committed to bolstering communities in the U.S. and across the world by supporting innovators who are addressing our 2021 Global Challenges — wherever they are — through funding, mentorship, and an MIT-backed community. Whether you’re a prospective Solve partner or applicant, we hope you’ll join us!” 

Solver teams participate in a nine-month program that connects them to the resources they need to scale. Thanks to its partners, to date Solve has provided over $40 million in commitments for Solver teams and entrepreneurs.

Solve’s challenge design process collects insights and ideas from industry leaders, MIT faculty, and local community voices alike. 

Solve’s 2021 Global Challenges are:

Funders include the Patrick J. McGovern Foundation, General Motors, Comcast NBCUniversal, Vodafone Americas Foundation, HP, Ewing Marion Kauffman Foundation, American Student Assistance, The Robert Wood Johnson Foundation, Andan Foundation, Good Energies Foundation and the Elevate Prize Foundation. The Solve community will convene at Virtual Solve at MIT on May 3-4 with 2020 Solver teams, Solve members, and partners to build partnerships and tackle global challenges in real-time. 

As a marketplace for social impact innovation, Solve’s mission is to solve world challenges. Solve finds promising tech-based social entrepreneurs around the world, then brings together MIT’s innovation ecosystem and a community of members to fund and support these entrepreneurs to help scale their impact. Organizations interested in joining the Solve community can learn more and apply for membership here.

MIT team improving gene therapies wins Sloan health care prize

The MIT team Kano Therapeutics won the 2021 Sloan Healthcare Innovations Prize Thursday with its novel approach for producing single stranded DNA (ssDNA). The technology could make gene therapies safer, more personalized, and cheaper.

Most gene therapies utilize double-stranded DNA, which can miss its target in the body and produce unwanted side effects. Single-stranded DNA has the potential to more precisely deliver genetic material to cells, but manufacturing ssDNA is currently expensive and inflexible.

Kano uses a novel approach to make ssDNA production more practical for applications like engineering immune cells to fight disease and altering genomes with CRISPR.

“Sustainable biomanufacturing of long single-stranded DNA can open doors to gene and cell therapies we currently only dream of,” says Kano team member Floris Engelhardt, who is currently a postdoc at MIT. “Not only do we think long ssDNA can improve the safety and efficacy of cell and gene therapies — while unlocking new indications — it may also be able to increase the efficiency and speed of manufacturing, shortening the time it takes to get therapies to patients.”

The team’s technology is based on the research of Engelhardt, whose team also includes John Vroom, a first-year MBA candidate at MIT’s Sloan School of Management.

Kano’s production process uses two versions of a type of DNA molecule called a plasmid to program a replicating virus called a bacteriophage. One plasmid holds the code to get into the bacteriophage, and the other carries the desired genetic code to be harvested.

“Cell and gene therapy currently is a little like assembling furniture before Ikea came along,” Vroom says. “The pieces don’t always fit together, assembly is rarely successful, and it can be incredibly frustrating for the builders. Kano aims to be a little like the Ikea of cell and gene therapy.”

Kano, which earned $20,000 as part of the prize, was one of eight finalists to pitch at the competition. Each team had five minutes to give their presentations, which were judged based on categories including the solution’s impact, novelty, market opportunity, feasibility, and traction. The annual pitch competition is a student-led event at MIT Sloan and is part of the Sloan Healthcare and BioInnovations Conference that was held Feb. 25 and 26.

The $4,000 second-place prize went to Blue Ocean Therapeutics, a company working to identify biomarkers that could help treat a type of epilepsy known as Focal Cortical Dysplasia type II (FCD II). Using advances in gene sequencing and machine learning to identify diseased cells, the company is hoping to improve the precision of current treatments as well as develop treatments of its own.

In third place was Hive Health, a startup using data science to provide a more effective, affordable health insurance option to Filipino employees. Through a partnership with the Filipino government, the company is using health care data to broaden access to coverage in the country while maintaining profitability.

Beyond the prize money, each of the eight finalists received feedback from both the judges and other industry experts who were made available to the teams via “office hours” in the weeks leading up to the final pitch.

“The teams already won regardless of the outcome,” says Zen Chu, a professor in the MIT Sloan School of Management who helped review applications. “This process of pitching and honing their ideas and getting feedback from a broad array of investors and buyers, whether they’re physicians or insurance companies or others, really informs and improves their outcomes.”

Irena King, the founder of Surgicure Technologies, which is developing a device to secure medical tubes in patient’s mouths when they’re intubated, says the competition helped her team to think through business processes and to network, adding that she’s been eager to connect with more female founders and advisors.

“It’s always great to get additional feedback on how we can strengthen our business model,” King says. “Any connections we can make with the industry and investors are super helpful. Also, the additional credibility we get from going through a screening and competition helps a lot.”

Other finalists included Cupid Health, which helps heart-failure patients manage medications while providing clinical insights to providers; Global Newborn Solutions, which is working to improve neonatal health in low-resource settings; Demos, which has developed a new drug-injection technique to broaden access to biological drugs; and Glyphic Biotechnologies, which is decoding the proteins in the human body at single-molecule resolution to improve diagnostics and therapeutics.

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