Community

Subterms

    Latest story

    138 Shares159 Views

    Creating new skills and new connections with MIT’s Quantitative Methods Workshop

    by

    Starting on New Year’s Day, when many people were still clinging to holiday revelry, scores of students and faculty members from about a dozen partner universities instead flipped open their laptops for MIT’s Quantitative Methods Workshop, a jam-packed, weeklong introduction to how computational and mathematical techniques can be applied to neuroscience and biology research. But don’t think of QMW as a “crash course.” Instead the program’s purpose is to help elevate each participant’s scientific outlook, both through the skills and concepts it imparts and the community it creates.

    “It broadens their horizons, it shows them significant applications they’ve never thought of, and introduces them to people whom as researchers they will come to know and perhaps collaborate with one day,” says Susan L. Epstein, a Hunter College computer science professor and education coordinator of MIT’s Center for Brains, Minds, and Machines, which hosts the program with the departments of Biology and Brain and Cognitive Sciences and The Picower Institute for Learning and Memory. “It is a model of interdisciplinary scholarship.”

    This year 83 undergraduates and faculty members from institutions that primarily serve groups underrepresented in STEM fields took part in the QMW, says organizer Mandana Sassanfar, senior lecturer and director of diversity and science outreach across the four hosting MIT entities. Since the workshop launched in 2010, it has engaged more than 1,000 participants, of whom more than 170 have gone on to participate in MIT Summer Research Programs (such as MSRP-BIO), and 39 have come to MIT for graduate school.

    Individual goals, shared experience

    Undergraduates and faculty in various STEM disciplines often come to QMW to gain an understanding of, or expand their expertise in, computational and mathematical data analysis. Computer science- and statistics-minded participants come to learn more about how such techniques can be applied in life sciences fields. In lectures; in hands-on labs where they used the computer programming language Python to process, analyze, and visualize data; and in less formal settings such as tours and lunches with MIT faculty, participants worked and learned together, and informed each other’s perspectives.

    Brain and Cognitive Sciences Professor Nancy Kanwisher delivers a lecture in MIT’s Building 46 on functional brain imaging to QMW participants.

    Photo: Mandana Sassanfar

    Previous item
    Next item

    And regardless of their field of study, participants made connections with each other and with the MIT students and faculty who taught and spoke over the course of the week.

    Hunter College computer science sophomore Vlad Vostrikov says that while he has already worked with machine learning and other programming concepts, he was interested to “branch out” by seeing how they are used to analyze scientific datasets. He also valued the chance to learn the experiences of the graduate students who teach QMW’s hands-on labs.

    “This was a good way to explore computational biology and neuroscience,” Vostrikov says. “I also really enjoy hearing from the people who teach us. It’s interesting to hear where they come from and what they are doing.”

    Jariatu Kargbo, a biology and chemistry sophomore at University of Maryland Baltimore County, says when she first learned of the QMW she wasn’t sure it was for her. It seemed very computation-focused. But her advisor Holly Willoughby encouraged Kargbo to attend to learn about how programming could be useful in future research — currently she is taking part in research on the retina at UMBC. More than that, Kargbo also realized it would be a good opportunity to make connections at MIT in advance of perhaps applying for MSRP this summer.

    “I thought this would be a great way to meet up with faculty and see what the environment is like here because I’ve never been to MIT before,” Kargbo says. “It’s always good to meet other people in your field and grow your network.”

    QMW is not just for students. It’s also for their professors, who said they can gain valuable professional education for their research and teaching.

    Fayuan Wen, an assistant professor of biology at Howard University, is no stranger to computational biology, having performed big data genetic analyses of sickle cell disease (SCD). But she’s mostly worked with the R programming language and QMW’s focus is on Python. As she looks ahead to projects in which she wants analyze genomic data to help predict disease outcomes in SCD and HIV, she says a QMW session delivered by biology graduate student Hannah Jacobs was perfectly on point.

    “This workshop has the skills I want to have,” Wen says.

    Moreover, Wen says she is looking to start a machine-learning class in the Howard biology department and was inspired by some of the teaching materials she encountered at QMW — for example, online curriculum modules developed by Taylor Baum, an MIT graduate student in electrical engineering and computer science and Picower Institute labs, and Paloma Sánchez-Jáuregui, a coordinator who works with Sassanfar.

    Tiziana Ligorio, a Hunter College computer science doctoral lecturer who together with Epstein teaches a deep machine-learning class at the City University of New York campus, felt similarly. Rather than require a bunch of prerequisites that might drive students away from the class, Ligorio was looking to QMW’s intense but introductory curriculum as a resource for designing a more inclusive way of getting students ready for the class.

    Instructive interactions

    Each day runs from 9 a.m. to 5 p.m., including morning and afternoon lectures and hands-on sessions. Class topics ranged from statistical data analysis and machine learning to brain-computer interfaces, brain imaging, signal processing of neural activity data, and cryogenic electron microscopy.

    “This workshop could not happen without dedicated instructors — grad students, postdocs, and faculty — who volunteer to give lectures, design and teach hands-on computer labs, and meet with students during the very first week of January,” Saassanfar says.

    MIT assistant professor of biology Brady Weissbourd (center) converses with QMW student participants during a lunch break.

    Photo: Mandana Sassanfar

    Previous item
    Next item

    The sessions surround student lunches with MIT faculty members. For example, at midday Jan. 2, assistant professor of biology Brady Weissbourd, an investigator in the Picower Institute, sat down with seven students in one of Building 46’s curved sofas to field questions about his neuroscience research in jellyfish and how he uses quantitative techniques as part of that work. He also described what it’s like to be a professor, and other topics that came to the students’ minds.

    Then the participants all crossed Vassar Street to Building 26’s Room 152, where they formed different but similarly sized groups for the hands-on lab “Machine learning applications to studying the brain,” taught by Baum. She guided the class through Python exercises she developed illustrating “supervised” and “unsupervised” forms of machine learning, including how the latter method can be used to discern what a person is seeing based on magnetic readings of brain activity.

    As students worked through the exercises, tablemates helped each other by supplementing Baum’s instruction. Ligorio, Vostrikov, and Kayla Blincow, assistant professor of biology at the University of the Virgin Islands, for instance, all leapt to their feet to help at their tables.

    Hunter College lecturer of computer science Tiziana Ligorio (standing) explains a Python programming concept to students at her table during a workshop session.

    Photo: David Orenstein

    Previous item
    Next item

    At the end of the class, when Baum asked students what they had learned, they offered a litany of new knowledge. Survey data that Sassanfar and Sánchez-Jáuregui use to anonymously track QMW outcomes, revealed many more such attestations of the value of the sessions. With a prompt asking how one might apply what they’ve learned, one respondent wrote: “Pursue a research career or endeavor in which I apply the concepts of computer science and neuroscience together.”

    Enduring connections

    While some new QMW attendees might only be able to speculate about how they’ll apply their new skills and relationships, Luis Miguel de Jesús Astacio could testify to how attending QMW as an undergraduate back in 2014 figured into a career where he is now a faculty member in physics at the University of Puerto Rico Rio Piedras Campus. After QMW, he returned to MIT that summer as a student in the lab of neuroscientist and Picower Professor Susumu Tonegawa. He came back again in 2016 to the lab of physicist and Francis Friedman Professor Mehran Kardar. What’s endured for the decade has been his connection to Sassanfar. So while he was once a student at QMW, this year he was back with a cohort of undergraduates as a faculty member.

    Michael Aldarondo-Jeffries, director of academic advancement programs at the University of Central Florida, seconded the value of the networking that takes place at QMW. He has brought students for a decade, including four this year. What he’s observed is that as students come together in settings like QMW or UCF’s McNair program, which helps to prepare students for graduate school, they become inspired about a potential future as researchers.

    “The thing that stands out is just the community that’s formed,” he says. “For many of the students, it’s the first time that they’re in a group that understands what they’re moving toward. They don’t have to explain why they’re excited to read papers on a Friday night.”

    Or why they are excited to spend a week including New Year’s Day at MIT learning how to apply quantitative methods to life sciences data. More

    More stories

    • 113 Shares99 Views

      in Data Management & Statistics

      3 Questions: Renaud Fournier on transforming MIT’s digital landscape

      by

      Renaud Fournier SM ’95 joined the Institute in September 2023 in the newly established role of chief officer for business and digital transformation and is leading a team focused on simplifying business operations and systems for the MIT community. Fournier has extensive experience implementing systems and solving data challenges, both in higher education and the private sector — most recently, leading the digital transformation effort at New York University. Here, Fournier speaks about how he and his team will work closely with members of the MIT community to chart a course for MIT’s digital evolution.

      Q: What are MIT’s enterprise systems and how are they challenging for our community?

      A: The MIT community relies on our enterprise systems for a range of activities — everything from hiring and evaluating employees to managing research grants and facilities projects to maintaining student information. SAP is our current enterprise resource planning system for human resources, finance, and facilities management, and it’s integrated with other systems that provide additional business functionality. Some of these systems are purchased, like Coupa, while others are partially or fully homegrown, like Kuali Coeus and NIMBUS. Along with SAP, our other core systems — for example, Advance and MITSIS — feed data into a central data warehouse to support reporting.

      MIT’s enterprise systems and data landscape has evolved organically over 30 years. The Institute has become considerably more complicated since then, and they no longer represent the best practices or technology in the IT market.

      Q: What digital transformation projects are you most focused on?

      A: Our primary goal is to free up our community’s time so that they can achieve their greatest impact. The vision is to create easy-to-use and well-integrated systems, along with comprehensible and accessible data for reporting and analysis. To accomplish this, we will be taking a series of actions. These include modernizing our enterprise systems and data architecture to take advantage of better technology and functionality, within a cohesive and well-integrated landscape, and simplifying our business processes. To make our data accessible and actionable, we will implement more robust data governance, assigning clear ownership and accountability. And we will offer IT support that enables our community to accomplish its objectives. We need to address systems, processes, data, and support holistically, while engaging and assisting our community every step of the way.    

      Q: What are your next steps?

      A: Over the next few months, I will be building a team to guide the community on this journey, in partnership with IS&T [Information Systems and Technology], other central units, and our academic areas. Together, we will be developing a thoughtful and actionable multi-year roadmap of digital transformation projects, which will help us to produce a steady stream of improvements for our community. We have not selected any systems yet or determined the order in which they will be implemented. Engagement with stakeholders from central, academic, and research areas will inform how we prioritize projects over the next few years. Once we have created the roadmap to guide us, we look forward to the next phase — getting started on the work itself. More

    • 125 Shares99 Views

      in Data Management & Statistics

      MIT campus goals in food, water, waste support decarbonization efforts

      by

      With the launch of Fast Forward: MIT’s Climate Action Plan for the Decade, the Institute committed to decarbonize campus operations by 2050 — an effort that touches on every corner of MIT, from building energy use to procurement and waste. At the operational level, the plan called for establishing a set of quantitative climate impact goals in the areas of food, water, and waste to inform the campus decarbonization roadmap. After an 18-month process that engaged staff, faculty, and researchers, the goals — as well as high-level strategies to reach them — were finalized in spring 2023.

      The goal development process was managed by a team representing the areas of campus food, water, and waste, respectively, and includes Director of Campus Dining Mark Hayes and Senior Sustainability Project Manager Susy Jones (food), Director of Utilities Janine Helwig (water), Assistant Director of Campus Services Marty O’Brien, and Assistant Director of Sustainability Brain Goldberg (waste) to co-lead the efforts. The group worked together to set goals that leverage ongoing campus sustainability efforts. “It was important for us to collaborate in order to identify the strategies and goals,” explains Goldberg. “It allowed us to set goals that not only align, but build off of one another, enabling us to work more strategically.”

      In setting the goals, each team relied on data, community insight, and best practices. The co-leads are sharing their process to help others at the Institute understand the roles they can play in supporting these objectives.  

      Sustainable food systems

      The primary food impact goal aims for a 25 percent overall reduction in the greenhouse gas footprint of food purchases starting with academic year 2021-22 as a baseline, acknowledging that beef purchases make up a significant share of those emissions. Additionally, the co-leads established a goal to recover all edible food waste in dining hall and retail operations where feasible, as that reduces MIT’s waste impact and acknowledges that redistributing surplus food to feed people is critically important.

      The work to develop the food goal was uniquely challenging, as MIT works with nine different vendors — including main vendor Bon Appetit — to provide food on campus, with many vendors having their own sustainability targets. The goal-setting process began by understanding vendor strategies and leveraging their climate commitments. “A lot of this work is not about reinventing the wheel, but about gathering data,” says Hayes. “We are trying to connect the dots of what is currently happening on campus and to better understand food consumption and waste, ensuring that we area reaching these targets.”

      In identifying ways to reach and exceed these targets, Jones conducted listening sessions around campus, balancing input with industry trends, best-available science, and institutional insight from Hayes. “Before we set these goals and possible strategies, we wanted to get a grounding from the community and understand what would work on our campus,” says Jones, who recently began a joint role that bridges the Office of Sustainability and MIT Dining in part to support the goal work.

      By establishing the 25 percent reduction in the greenhouse gas footprint of food purchases across MIT residential dining menus, Jones and Hayes saw goal-setting as an opportunity to add more sustainable, local, and culturally diverse foods to the menu. “If beef is the most carbon-intensive food on the menu, this enables us to explore and expand so many recipes and menus from around the globe that incorporate alternatives,” Jones says.

      Strategies to reach the climate food goals focus on local suppliers, more plant-forward meals, food recovery, and food security. In 2019, MIT was a co-recipient of the New England Food Vision Prize provided by the Kendall Foundation to increase the amount of local food served on campus in partnership with CommonWealth Kitchen in Dorchester. While implementation of that program was put on pause due to the pandemic, work resumed this year. Currently, the prize is funding a collaborative effort to introduce falafel-like, locally manufactured fritters made from Maine-grown yellow field peas to dining halls at MIT and other university campuses, exemplifying the efforts to meet the climate impact goal, serve as a model for others, and provide demonstrable ways of strengthening the regional food system.

      “This sort of innovation is where we’re a leader,” says Hayes. “In addition to the Kendall Prize, we are looking to focus on food justice, growing our BIPOC [Black, Indigenous, and people of color] vendors, and exploring ideas such as local hydroponic and container vegetable growing companies, and how to scale these types of products into institutional settings.”

      Reduce and reuse for campus water

      The 2030 water impact goal aims to achieve a 10 percent reduction in water use compared to the 2019 baseline and to update the water reduction goal to align with the new metering program and proposed campus decarbonization plans as they evolve.

      When people think of campus water use, they may think of sprinklers, lab sinks, or personal use like drinking water and showers. And while those uses make up around 60 percent of campus water use, the Central Utilities Plant (CUP) accounts for the remaining 40 percent. “The CUP generates electricity and delivers heating and cooling to the campus through steam and chilled water — all using what amounts to a large percentage of water use on campus,” says Helwig. As such, the water goal focuses as much on reuse as reduction, with one approach being to expand water capture from campus cooling towers for reuse in CUP operations. “People often think of water use and energy separately, but they often go hand-in-hand,” Helwig explains.

      Data also play a central part in the water impact goal — that’s why a new metering program is called for in the implementation strategy. “We have access to a lot of data at MIT, but in reviewing the water data to inform the goal, we learned that it wasn’t quite where we needed it,” explains Helwig. “By ensuring we have the right meter and submeters set up, we can better set boundaries to understand where there is the potential to reduce water use.” Irrigation on campus is one such target with plans to soon release new campuswide landscaping standards that minimize water use.

      Reducing campus waste

      The waste impact goal aims to reduce campus trash by 30 percent compared to 2019 baseline totals. Additionally, the goal outlines efforts to improve the accuracy of indicators tracking campus waste; reduce the percentage of food scraps in trash and percent of recycling in trash in select locations; reduce the percentage of trash and recycling comprised of single use items; and increase the percentage of residence halls and other campus spaces where food is consumed at scale, implementing an MIT food scrap collection program.

      In setting the waste goals, Goldberg and O’Brien studied available campus waste data from past waste audits, pilot programs, and MIT’s waste haulers. They factored in state and city policies that regulate things like the type and amount of waste large institutions can transport. “Looking at all the data it became clear that a 30 percent trash reduction goal will make a tremendous impact on campus and help us drive toward the goal of completely designing out waste from campus,” Goldberg says. The strategies to reach the goals include reducing the amount of materials that come into campus, increasing recycling rates, and expanding food waste collection on campus.

      While reducing the waste created from material sources is outlined in the goals, food waste is a special focus on campus because it comprises approximately 40 percent of campus trash, it can be easily collected separately from trash and recycled locally, and decomposing food waste is one of the largest sources of greenhouse gas emissions found in landfills. “There is a lot of greenhouse gas emissions that result from production, distribution, transportation, packaging, processing, and disposal of food,” explains Goldberg. “When food travels to campus, is removed from campus as waste, and then breaks down in a landfill, there are emissions every step of the way.”

      To reduce food waste, Goldberg and O’Brien outlined strategies that include working with campus suppliers to identify ordering volumes and practices to limit waste. Once materials are on campus, another strategy kicks in, with a new third stream of waste collection that joins recycling and trash — food waste. By collecting the food waste separately — in bins that are currently rolling out across campus — the waste can be reprocessed into fertilizer, compost, and/or energy without the off-product of greenhouse gases. The waste impact goal also relies on behavioral changes to reduce waste, with education materials part of the process to reduce waste and decontaminate reprocessing streams.

      Tracking progress

      As work toward the goals advances, community members can monitor progress in the Sustainability DataPool Material Matters and Campus Water Use dashboards, or explore the Impact Goals in depth.

      “From food to water to waste, everyone on campus interacts with these systems and can grapple with their impact either from a material they need to dispose of, to water they’re using in a lab, or leftover food from an event,” says Goldberg. “By setting these goals we as an institution can lead the way and help our campus community understand how they can play a role, plug in, and make an impact.” More

    • 125 Shares179 Views

      in Data Management & Statistics

      MIT welcomes nine MLK Visiting Professors and Scholars for 2023-24

      by

      Established in 1990, the MLK Visiting Professors and Scholars Program at MIT welcomes outstanding scholars to the Institute for visiting appointments. MIT aspires to attract candidates who are, in the words of Martin Luther King Jr., “trailblazers in human, academic, scientific and religious freedom.” The program honors King’s life and legacy by expanding and extending the reach of our community. 

      The MLK Scholars Program has welcomed more than 140 professors, practitioners, and professionals at the forefront of their respective fields to MIT. They contribute to the growth and enrichment of the community through their interactions with students, staff, and faculty. They pay tribute to Martin Luther King Jr.’s life and legacy of service and social justice, and they embody MIT’s values: excellence and curiosity, openness and respect, and belonging and community.  

      Each new cohort of scholars actively participates in community engagement and supports MIT’s mission of “advancing knowledge and educating students in science, technology, and other areas of scholarship that will best serve the nation and the world in the 21st century.” 

      The 2023-2024 MLK Scholars:

      Tawanna Dillahunt is an associate professor at the University of Michigan’s School of Information with a joint appointment in their electrical engineering and computer science department. She is joining MIT at the end of a one-year visiting appointment as a Harvard Radcliffe Fellow. Her faculty hosts at the Institute are Catherine D’Ignazio in the Department of Urban Studies and Planning and Fotini Christia in the Institute for Data, Systems, and Society (IDSS). Dillahunt’s research focuses on equitable and inclusive computing. During her appointment, she will host a podcast to explore ethical and socially responsible ways to engage with communities, with a special emphasis on technology. 

      Kwabena Donkor is an assistant professor of marketing at Stanford Graduate School of Business; he is hosted by Dean Eckles, an associate professor of marketing at MIT Sloan School of Management. Donkor’s work bridges economics, psychology, and marketing. His scholarship combines insights from behavioral economics with data and field experiments to study social norms, identity, and how these constructs interact with policy in the marketplace.

      Denise Frazier joins MIT from Tulane University, where she is an assistant director in the New Orleans Center for the Gulf South. She is a researcher and performer and brings a unique interdisciplinary approach to her work at the intersection of cultural studies, environmental justice, and music. Frazier is hosted by Christine Ortiz, the Morris Cohen Professor in the Department of Materials Science and Engineering. 

      Wasalu Jaco, an accomplished performer and artist, is renewing his appointment at MIT for a second year; he is hosted jointly by Nick Montfort, a professor of digital media in the Comparative Media Studies Program/Writing, and Mary Fuller, a professor in the Literature Section and the current chair of the MIT faculty. In his second year, Jaco will work on Cyber/Cypher Rapper, a research project to develop a computational system that participates in responsive and improvisational rap.

      Morgane Konig first joined the Center for Theoretical Physics at MIT in December 2021 as a postdoc. Now a member of the 2023–24 MLK Visiting Scholars Program cohort, she will deepen her ties with scholars and research groups working in cosmology, primarily on early-universe inflation and late-universe signatures that could enable the scientific community to learn more about the mysterious nature of dark matter and dark energy. Her faculty hosts are David Kaiser, the Germeshausen Professor of the History of Science and professor of physics, and Alan Guth, the Victor F. Weisskopf Professor of Physics, both from the Department of Physics.

      The former minister of culture for Colombia and a transformational leader dedicated to environmental protection, Angelica Mayolo-Obregon joins MIT from Buenaventura, Colombia. During her time at MIT, she will serve as an advisor and guest speaker, and help MIT facilitate gatherings of environmental leaders committed to addressing climate action and conserving biodiversity across the Americas, with a special emphasis on Afro-descendant communities. Mayolo-Obregon is hosted by John Fernandez, a professor of building technology in the Department of Architecture and director of MIT’s Environmental Solutions Initiative, and by J. Phillip Thompson, an associate professor in the Department of Urban Studies and Planning (and a former MLK Scholar).

      Jean-Luc Pierite is a member of the Tunica-Biloxi Tribe of Louisiana and the president of the board of directors of North American Indian Center of Boston. While at MIT, Pierite will build connections between MIT and the local Indigenous communities. His research focuses on enhancing climate resilience planning by infusing Indigenous knowledge and ecological practices into scientific and other disciplines. His faculty host is Janelle Knox-Hayes, the Lister Brothers Professor of Economic Geography and Planning in the Department of Urban Studies and Planning.

      Christine Taylor-Butler ’81 is a children’s book author who has written over 90 books; she is hosted by Graham Jones, an associate professor of anthropology. An advocate for literacy and STEAM education in underserved urban and rural schools, Taylor-Butler will partner with community organizations in the Boston area. She is also completing the fourth installment of her middle-grade series, “The Lost Tribe.” These books follow a team of five kids as they use science and technology to crack codes and solve mysteries.

      Angelino Viceisza, a professor of economics at Spelman College, joins MIT Sloan as an MLK Visiting Professor and the Phyllis Wallace Visiting Professor; he is hosted by Robert Gibbons, Sloan Distinguished Professor of Management, and Ray Reagans, Alfred P. Sloan Professor of Management, professor of organization studies, and associate dean for diversity, equity, and inclusion at MIT Sloan. Viceisza has strong, ongoing connections with MIT. His research focuses on remittances, retirement, and household finance in low-income countries and is relevant to public finance and financial economics, as well as the development and organizational economics communities at MIT. 

      Javit Drake, Moriba Jah, and Louis Massiah, members of last year’s cohort of MLK Scholars, will remain at MIT through the end of 2023.

      There are multiple opportunities throughout the year to meet our MLK Visiting Scholars and learn more about their research projects and their social impact. 

      For more information about the MLK Visiting Professors and Scholars Program and upcoming events, visit the website. More

    • 88 Shares169 Views

      in Data Management & Statistics

      Day of AI curriculum meets the moment

      by

      MIT Responsible AI for Social Empowerment and Education (RAISE) recently celebrated the second annual Day of AI with two flagship local events. The Edward M. Kennedy Institute for the U.S. Senate in Boston hosted a human rights and data policy-focused event that was streamed worldwide. Dearborn STEM Academy in Roxbury, Massachusetts, hosted a student workshop in collaboration with Amazon Future Engineer. With over 8,000 registrations across all 50 U.S. states and 108 countries in 2023, participation in Day of AI has more than doubled since its inaugural year.

      Day of AI is a free curriculum of lessons and hands-on activities designed to teach kids of all ages and backgrounds the basics and responsible use of artificial intelligence, designed by researchers at MIT RAISE. This year, resources were available for educators to run at any time and in any increments they chose. The curriculum included five new modules to address timely topics like ChatGPT in School, Teachable Machines, AI and Social Media, Data Science and Me, and more. A collaboration with the International Society for Technology in Education also introduced modules for early elementary students. Educators across the world shared photos, videos, and stories of their students’ engagement, expressing excitement and even relief over the accessible lessons.

      Professor Cynthia Breazeal, director of RAISE, dean for digital learning at MIT, and head of the MIT Media Lab’s Personal Robots research group, said, “It’s been a year of extraordinary advancements in AI, and with that comes necessary conversations and concerns about who and what this technology is for. With our Day of AI events, we want to celebrate the teachers and students who are putting in the work to make sure that AI is for everyone.”

      Reflecting community values and protecting digital citizens

      Play video

      On May 18, 2023, MIT RAISE hosted a global Day of AI celebration featuring a flagship local event focused on human rights and data policy at the Edward M. Kennedy Institute for the U.S. Senate. Students from the Warren Prescott Middle School and New Mission High School heard from speakers the City of Boston, Liberty Mutual, and MIT to discuss the many benefits and challenges of artificial intelligence education. Video: MIT Open Learning

      MIT President Sally Kornbluth welcomed students from Warren Prescott Middle School and New Mission High School to the Day of AI program at the Edward M. Kennedy Institute. Kornbluth reflected on the exciting potential of AI, along with the ethical considerations society needs to be responsible for.

      “AI has the potential to do all kinds of fantastic things, including driving a car, helping us with the climate crisis, improving health care, and designing apps that we can’t even imagine yet. But what we have to make sure it doesn’t do is cause harm to individuals, to communities, to us — society as a whole,” she said.

      This theme resonated with each of the event speakers, whose jobs spanned the sectors of education, government, and business. Yo Deshpande, technologist for the public realm, and Michael Lawrence Evans, program director of new urban mechanics from the Boston Mayor’s Office, shared how Boston thinks about using AI to improve city life in ways that are “equitable, accessible, and delightful.” Deshpande said, “We have the opportunity to explore not only how AI works, but how using AI can line up with our values, the way we want to be in the world, and the way we want to be in our community.”

      Adam L’Italien, chief innovation officer at Liberty Mutual Insurance (one of Day of AI’s founding sponsors), compared our present moment with AI technologies to the early days of personal computers and internet connection. “Exposure to emerging technologies can accelerate progress in the world and in your own lives,” L’Italien said, while recognizing that the AI development process needs to be inclusive and mitigate biases.

      Human policies for artificial intelligence

      So how does society address these human rights concerns about AI? Marc Aidinoff ’21, former White House Office of Science and Technology Policy chief of staff, led a discussion on how government policy can influence the parameters of how technology is developed and used, like the Blueprint for an AI Bill of Rights. Aidinoff said, “The work of building the world you want to see is far harder than building the technical AI system … How do you work with other people and create a collective vision for what we want to do?” Warren Prescott Middle School students described how AI could be used to solve problems that humans couldn’t. But they also shared their concerns that AI could affect data privacy, learning deficits, social media addiction, job displacement, and propaganda.

      In a mock U.S. Senate trial activity designed by Daniella DiPaola, PhD student at the MIT Media Lab, the middle schoolers investigated what rights might be undermined by AI in schools, hospitals, law enforcement, and corporations. Meanwhile, New Mission High School students workshopped the ideas behind bill S.2314, the Social Media Addiction Reduction Technology (SMART) Act, in an activity designed by Raechel Walker, graduate research assistant in the Personal Robots Group, and Matt Taylor, research assistant at the Media Lab. They discussed what level of control could or should be introduced at the parental, educational, and governmental levels to reduce the risks of internet addiction.

      “Alexa, how do I program AI?”

      Play video

      The 2023 Day of AI celebration featured a flagship local event at the Dearborn STEM Academy in Roxbury in collaboration with Amazon Future Engineer. Students participated in a hands-on activity using MIT App Inventor as part of Day of AI’s Alexa lesson. Video: MIT Open Learning

      At Dearborn STEM Academy, Amazon Future Engineer helped students work through the Intro to Voice AI curriculum module in real-time. Students used MIT App Inventor to code basic commands for Alexa. In an interview with WCVB, Principal Darlene Marcano said, “It’s important that we expose our students to as many different experiences as possible. The students that are participating are on track to be future computer scientists and engineers.”

      Breazeal told Dearborn students, “We want you to have an informed voice about how you want AI to be used in society. We want you to feel empowered that you can shape the world. You can make things with AI to help make a better world and a better community.”

      Rohit Prasad ’08, senior vice president and head scientist for Alexa at Amazon, and Victor Reinoso ’97, global director of philanthropic education initiatives at Amazon, also joined the event. “Amazon and MIT share a commitment to helping students discover a world of possibilities through STEM and AI education,” said Reinoso. “There’s a lot of current excitement around the technological revolution with generative AI and large language models, so we’re excited to help students explore careers of the future and navigate the pathways available to them.” To highlight their continued investment in the local community and the school program, Amazon donated a $25,000 Innovation and Early College Pathways Program Grant to the Boston Public School system.

      Day of AI down under

      Not only was the Day of AI program widely adopted across the globe, Australian educators were inspired to adapt their own regionally specific curriculum. An estimated 161,000 AI professionals will be needed in Australia by 2030, according to the National Artificial Intelligence Center in the Commonwealth Scientific and Industrial Research Organization (CSIRO), an Australian government agency and Day of AI Australia project partner. CSIRO worked with the University of New South Wales to develop supplementary educational resources on AI ethics and machine learning. Day of AI Australia reached 85,000 students at 400-plus secondary schools this year, sparking curiosity in the next generation of AI experts.

      The interest in AI is accelerating as fast as the technology is being developed. Day of AI offers a unique opportunity for K-12 students to shape our world’s digital future and their own.

      “I hope that some of you will decide to be part of this bigger effort to help us figure out the best possible answers to questions that are raised by AI,” Kornbluth told students at the Edward M. Kennedy Institute. “We’re counting on you, the next generation, to learn how AI works and help make sure it’s for everyone.” More

    • 150 Shares109 Views

      in Data Management & Statistics

      Learner in Afghanistan reaches beyond barriers to pursue career in data science

      by

      Tahmina S. was a junior studying computer engineering at a top university in Afghanistan when a new government policy banned women from pursuing education. In August 2021, the Taliban prohibited girls from attending school beyond the sixth grade. While women were initially allowed to continue to attend universities, by October 2021, an order from the Ministry of Higher Education declared that all women in Afghanistan were suspended from attending public and private centers of higher education.

      Determined to continue her studies and pursue her ambitions, Tahmina found the MIT Refugee Action Hub (ReACT) and was accepted to its Certificate in Computer Science and Data Science program in 2022.

      “ReACT helped me realize that I can do big things and be a part of big things,” she says.

      MIT ReACT provides education and professional opportunities to learners from refugee and forcibly displaced communities worldwide. ReACT’s core pillars include academic development, human skills development, employment pathways, and network building. Since 2017, ReACT has offered its Certificate in Computer and Data Science (CDS) program free-of-cost to learners wherever they live. In 2022, ReACT welcomed its largest and most diverse cohort to date — 136 learners from 29 countries — including 25 learners from Afghanistan, more than half of whom are women.

      Tahmina was able to select her classes in the program, and especially valued learning Python — which has led to her studying other programming languages and gaining more skills in data science. She’s continuing to take online courses in hopes of completing her undergraduate degree, and someday pursuing a masters degree in computer science and becoming a data scientist.

      “It’s an important and fun career. I really love data,” she says. “If this is my only time for this experience, I will bring to the table what I have, and do my best.”

      In addition to the education ban, Tahmina also faced the challenge of accessing an internet connection, which is expensive where she lives. But she regularly studies between 12 and 14 hours a day to achieve her dreams.

      The ReACT program offers a blend of asynchronous and synchronous learning. Learners complete a curated series of online, rigorous MIT coursework through MITx with the support of teaching assistants and collaborators, and also participate in a series of interactive online workshops in interpersonal skills that are critical to success in education and careers.

      ReACT learners engage with MIT’s global network of experts including MIT staff, faculty, and alumni — as well as collaborators across technology, humanitarian, and government sectors.

      “I loved that experience a lot, it was a huge achievement. I’m grateful ReACT gave me a chance to be a part of that team of amazing people. I’m amazed I completed that program, because it was really challenging.”

      Theory into practice

      Tahmina was one of 10 students from the ReACT cohort accepted to the highly competitive MIT Innovation Leadership Bootcamp program. She worked on a team of five people who initiated a business proposal and took the project through each phase of the development process. Her team’s project was creating an app for finance management for users aged 23-51 — including all the graphic elements and a final presentation. One valuable aspect of the boot camp, Tahmina says, was presenting their project to real investors who then provided business insights and actionable feedback.

      As part of this ReACT cohort, Tahmina also participated in the Global Apprenticeship Program (GAP) pilot, an initiative led by Talanta and with the participation of MIT Open Learning as curriculum provider. The GAP initiative focuses on improving diverse emerging talent job preparedness and exploring how companies can successfully recruit, onboard, and retain this talent through remote, paid internships. Through the GAP pilot, Tahmina received training in professional skills, resume and interview preparation, and was matched with a financial sector firm for a four-month remote internship in data science.

      To prepare Tahmina and other learners for these professional experiences, ReACT trains its cohorts to work with people who have diverse backgrounds, experiences, and challenges. The nonprofit Na’amal offered workshops covering areas such as problem-solving, innovation and ideation, goal-setting, communication, teamwork, and infrastructure and info security. Tahmina was able to access English classes and learn valuable career skills, such as writing a resume.“This was an amazing part for me. There’s a huge difference going from theoretical to practical,” she says. “Not only do you have to have the theoretical experience, you have to have soft skills. You have to communicate everything you learn to other people, because other people in the business might not have that knowledge, so you have to tell the story in a way that they can understand.”

      ReACT wanted the women in the program to be mentored by women who were not only leaders in the tech field, but working in the same geographic region as learners. At the start of the internship, Na’amal connected Tahmina with a mentor, Maha Gad, who is head of talent development at Talabat and lives in Dubai. Tahmina met with Gad at the beginning and end of each month, giving her the opportunity to ask expansive questions. Tahmina says Gad encouraged her to research and plan first, and then worked with her to explore new tools, like Trello.

      Wanting to put her skills to use locally, Tahmina volunteered at the nonprofit Rumie, a community for Afghan women and girls, working as a learning designer, translator, team leader, and social media manager. She currently volunteers at Correspondents of the World as a story ambassador, helping Afghan people share stories, community, and culture — especially telling the stories of Afghan women and the changes they’ve made in the world.

      “It’s been the most beautiful journey of my life that I will never forget,” says Tahmina. “I found ReACT at a time when I had nothing, and I found the most valuable thing.” More

    • 125 Shares199 Views

      in Data Management & Statistics

      Festival of Learning 2023 underscores importance of well-designed learning environments

      by

      During its first in-person gathering since 2020, MIT’s Festival of Learning 2023 explored how the learning sciences can inform the Institute on how to best support students. Co-sponsored by MIT Open Learning and the Office of the Vice Chancellor (OVC), this annual event celebrates teaching and learning innovations with MIT instructors, students, and staff.

      Bror Saxberg SM ’85, PhD ’89, founder of LearningForge LLC and former chief learning officer at Kaplan, Inc., was invited as keynote speaker, with opening remarks by MIT Chancellor Melissa Nobles and Vice President for Open Learning Eric Grimson, and discussion moderated by Senior Associate Dean of Open Learning Christopher Capozzola. This year’s festival focused on how creating well-designed learning environments using learning engineering can increase learning success.

      Play video

      2023 Festival of Learning: Highlights

      Well-designed learning environments are key

      In his keynote speech “Learning Engineering: What We Know, What We Can Do,” Saxberg defined “learning engineering” as the practical application of learning sciences to real-world problems at scale. He said, “High levels can be reached by all learners, given access to well-designed instruction and motivation for enough practice opportunities.”

      Informed by decades of empirical evidence from the field of learning science, Saxberg’s own research, and insights from Kaplan, Inc., Saxberg finds that a hands-on strategy he calls “prepare, practice, perform” delivers better learning outcomes than a traditional “read, write, discuss” approach. Saxberg recommends educators devote at least 60 percent of learning time to hands-on approaches, such as producing, creating, and engaging. Only 20-30 percent of learning time should be spent in the more passive “knowledge acquisition” modes of listening and reading.

      “Here at MIT, a place that relies on data to make informed decisions, learning engineering can provide a framework for us to center in on the learner to identify the challenges associated with learning, and to apply the learning sciences in data-driven ways to improve instructional approaches,” said Nobles. During their opening remarks, Nobles and Grimson both emphasized how learning engineering at MIT is informed by the Institute’s commitment to educating the whole student, which encompasses student well-being and belonging in addition to academic rigor. “What lessons can we take away to change the way we think about education moving forward? This is a chance to iterate,” said Grimson.

      Well-designed learning environments are informed by understanding motivation, considering the connection between long-term and working memory, identifying the range of learners’ prior experience, grounding practice in authentic contexts (i.e., work environments), and using data-driven instructional approaches to iterate and improve.

      Play video

      2023 Festival of Learning: Keynote by Bror Saxberg

      Understand learner motivation

      Saxberg asserted that before developing course structures and teaching approaches known to encourage learning, educators must first examine learner motivation. Motivation doesn’t require enjoyment of the subject or task to spur engagement. Similar to how a well-designed physical training program can change your muscle cells, if a learner starts, persists, and exerts mental effort in a well-designed learning environment, they can change their neurons — they learn. Saxberg described four main barriers to learner motivation, and solutions for each:

      The learner doesn’t see the value of the lesson. Ways to address this include helping the learners find value; leveraging the learner’s expertise in another area to better understand the topic at hand; and making the activity itself enjoyable. “Finding value” could be as simple as explaining the practical applications of this knowledge in their future work in the field, or how this lesson prepares learners for their advanced level courses. 
      Self-efficacy for learners who don’t think they’re capable. Educators can point to parallel experiences with similar goals that students may have already achieved in another context. Alternatively, educators can share stories of professionals who have successfully transitioned from one area of expertise to another. 
      “Something” in the learner’s way, such as not having the time, space, or correct materials. This is an opportunity to demonstrate how a learner can use problem-solving skills to find a solution to their perceived problem. As with the barrier of self-efficacy, educators can assure learners that they are in control of the situation by sharing similar stories of those who’ve encountered the same problem and the solution they devised.
      The learner’s emotional state. This is no small barrier to motivation. If a learner is angry, depressed, scared, or grieving, it will be challenging for them to switch their mindset into learning mode. A wide array of emotions require a wide array of possible solutions, from structured conversation techniques to recommending professional help.
      Consider the cognitive load

      Saxberg has found that learning occurs when we use working memory to problem-solve, but our working memory can only process three to five verbal or conscious thoughts at a time. Long-term memory stores knowledge that can be accessed non-verbally and non-consciously, which is why experts appear to remember information effortlessly. Until a learner develops that expertise, extraneous information in a lesson will occupy space in their working memory, running the risk of distracting the learner from the desired learning outcome.

      To accommodate learners’ finite cognitive load, Saxberg suggested the solution of reevaluating which material is essential, then simplifying the exercise or removing unnecessary material accordingly. “That notion of, ‘what do we really need students to be able to do?’ helps you focus,” said Saxberg.

      Another solution is to leverage the knowledge, skills, and interests learners already bring to the course — these long-term memories can scaffold the new material. “What do you have in your head already, what do you love, what’s easy to draw from long-term memory? That would be the starting point for challenging new skills. It’s not the ending point because you want to use your new skills to then find out new things,” Saxberg said. Finally, consider how your course engages with the syllabi. Do you explain the reasoning behind the course structure? Do you show how the exercises or material will be applied to future courses or the field? Do you share best practices for engaging working memory and learning? By acknowledging and empathizing with the practical challenges that learners face, you can remove a barrier from their cognitive load.

      Ground practice in authentic contexts

      Saxberg stated that few experts read textbooks to learn new information — they discover what they need to know while working in the field, using those relevant facts in context. As such, students will have an easier time remembering facts if they’re practicing in relevant or similar environments to their future work.

      If students can practice classifying problems in real work contexts rather than theoretical practice problems, they can build a framework to classify what’s important. That helps students recognize the type of problem they’re trying to solve before trying to solve the problem itself. With enough hands-on practice and examples of how experts use processes and identify which principles are relevant, learners can holistically learn entire procedures. And that learning continues once learners graduate to the workforce: professionals often meet to exchange knowledge at conferences, charrettes, and other gatherings.

      Enhancing teaching at MIT

      The Festival of Learning furthers the Office of the Chancellor’s mission to advance academic innovation that will foster the growth of MIT students. The festival also aligns with the MIT Open Learning’s Residential Education team’s goal of making MIT education more effective and efficient. Throughout the year, their team offers continuous support to MIT faculty and instructors using digital technologies to augment and transform how they teach.

      “We are doubling down on our commitment to continuous growth in how we teach,” said Nobles. More

    • 113 Shares99 Views

      in Data Management & Statistics

      Research, education, and connection in the face of war

      by

      When Russian forces invaded Ukraine in February 2022, Tetiana Herasymova had several decisions to make: What should she do, where should she live, and should she take her MITx MicroMasters capstone exams? She had registered for the Statistics and Data Science Program’s final exams just days prior to moving out of her apartment and into a bomb shelter. Although it was difficult to focus on studying and preparations with air horns sounding overhead and uncertainty lingering around her, she was determined to try. “I wouldn’t let the aggressor in the war squash my dreams,” she says.

      A love of research and the desire to improve teaching 

      An early love of solving puzzles and problems for fun piqued Herasymova’s initial interest in mathematics. When she later pursued her PhD in mathematics at Kiev National Taras Shevchenko University, Herasymova’s love of math evolved into a love of research. Throughout Herasymova’s career, she’s worked to close the gap between scientific researchers and educators. Starting as a math tutor at MBA Strategy, a company that prepares Ukrainian leaders for qualifying standardized tests for MBA programs, she was later promoted as the head of their test preparation department. Afterward, she moved on to an equivalent position at ZNOUA, a new project that prepared high school students for Ukraine’s standardized test, and she eventually became ZNOUA’s CEO.

      In 2018, she founded Prosteer, a “self-learning community” of educators who share research, pedagogy, and experience to learn from one another. “It’s really interesting to have a community of teachers from different domains,” she says, speaking of educators and researchers whose specialties range across language, mathematics, physics, music, and more.

      Implementing new pedagogical research in the classroom is often up to educators who seek out studies on an individual basis, Herasymova has found. “Lots of scientists are not practitioners,” she says, and the reverse is also true. She only became more determined to build these connections once she was promoted to head of test preparation at MBA Strategy because she wanted to share more effective pedagogy with the tutors she was mentoring.

      First, Herasymova knew she needed a way to measure the teachers’ effectiveness. She was able to determine whether students who received the company’s tutoring services improved their scores. Moreover, Ukraine keeps an open-access database of national standardized test scores, so anyone could analyze the data in hopes of improving the level of education in the country. She says, “I could do some analytics because I am a mathematician, but I knew I could do much more with this data if I knew data science and machine learning knowledge.”

      That’s why Herasymova sought out the MITx MicroMasters Program in Statistics and Data Science offered by the MIT Institute for Data, Systems, and Society (IDSS). “I wanted to learn the fundamentals so I could join the Learning Analytics domain,” she says. She was looking for a comprehensive program that covered the foundations without being overly basic. “I had some knowledge from the ground, so I could see the deepness of that course,” she says. Because of her background as an instructional designer, she thought the MicroMasters curriculum was well-constructed, calling the variety of videos, practice problems, and homework assignments that encouraged learners to approach the course material in different ways, “a perfect experience.”

      Another benefit of the MicroMasters program was its online format. “I had my usual work, so it was impossible to study in a stationary way,” she says. She found the structure to be more flexible than other programs. “It’s really great that you can construct your course schedule your own way, especially with your own adult life,” she says.

      Determination and support in the midst of war

      When the war first forced Herasymova to flee her apartment, she had already registered to take the exams for her four courses. “It was quite hard to prepare for exams when you could hear explosions outside of the bomb shelter,” she says. She and other Ukranians were invited to postpone their exams until the following session, but the next available testing period wouldn’t be held until October. “It was a hard decision, but I had to allow myself to try,” she says. “For all people in Ukraine, when you don’t know if you’re going to live or die, you try to live in the now. You have to appreciate every moment and what life brings to you. You don’t say, ‘Someday’ — you do it today or tomorrow.”

      In addition to emotional support from her boyfriend, Herasymova had a group of friends who had also enrolled in the program, and they supported each other through study sessions and an ongoing chat. Herasymova’s personal support network helped her accomplish what she set out to do with her MicroMasters program, and in turn, she was able to support her professional network. While Prosteer halted its regular work during the early stages of the war, Herasymova was determined to support the community of educators and scientists that she had built. They continued meeting weekly to exchange ideas as usual. “It’s intrinsic motivation,” she says. They managed to restore all of their activities by October.

      Despite the factors stacked against her, Herasymova’s determination paid off — she passed all of her exams in May, the final step to earning her MicroMasters certificate in statistics and data science. “I just couldn’t believe it,” she says. “It was definitely a bifurcation point. The moment when you realize that you have something to rely on, and that life is just beginning to show all its diversity despite the fact that you live in war.” With her newly minted certificate in hand, Herasymova has continued her research on the effectiveness of educational models — analyzing the data herself — with a summer research program at New York University. 

      The student becomes the master

      After moving seven times between February and October, heading west from Kyiv until most recently settling near the border of Poland, Herasymova hopes she’s moved for the last time. Ukrainian Catholic University offered her a position teaching both mathematics and programming. Before enrolling in the MicroMasters Program in Statistics and Data Science, she had some prior knowledge of programming languages and mathematical algorithms, but she didn’t know Python. She took MITx’s Introduction to Computer Science and Programming Using Python to prepare. “It gave me a huge step forward,” she says. “I learned a lot. Now, not only can I work with Python machine learning models in programming language R, I also have knowledge of the big picture of the purpose and the point to do so.”

      In addition to the skills the MicroMasters Program trained her in, she gained firsthand experience in learning new subjects and exploring topics more deeply. She will be sharing that practice with the community of students and teachers she’s built, plus, she plans on guiding them through this course during the next year. As a continuation of her own educational growth, says she’s looking forward to her next MITx course this year, Data Analysis.

      Herasymova advises that the best way to keep progressing is investing a lot of time. “Adults don’t want to hear this, but you need one or two years,” she says. “Allow yourself to be stupid. If you’re an expert in one domain and want to switch to another, or if you want to understand something new, a lot of people don’t ask questions or don’t ask for help. But from this point, if I don’t know something, I know I should ask for help because that’s the start of learning. With a fixed mindset, you won’t grow.”

      July 2022 MicroMasters Program Joint Completion Celebration. Ukrainian student Tetiana Herasymova, who completed her program amid war in her home country, speaks at 43:55. More

    • 138 Shares169 Views

      in Data Management & Statistics

      Gaining real-world industry experience through Break Through Tech AI at MIT

      by

      Taking what they learned conceptually about artificial intelligence and machine learning (ML) this year, students from across the Greater Boston area had the opportunity to apply their new skills to real-world industry projects as part of an experiential learning opportunity offered through Break Through Tech AI at MIT.

      Hosted by the MIT Schwarzman College of Computing, Break Through Tech AI is a pilot program that aims to bridge the talent gap for women and underrepresented genders in computing fields by providing skills-based training, industry-relevant portfolios, and mentoring to undergraduate students in regional metropolitan areas in order to position them more competitively for careers in data science, machine learning, and artificial intelligence.

      “Programs like Break Through Tech AI gives us opportunities to connect with other students and other institutions, and allows us to bring MIT’s values of diversity, equity, and inclusion to the learning and application in the spaces that we hold,” says Alana Anderson, assistant dean of diversity, equity, and inclusion for the MIT Schwarzman College of Computing.

      The inaugural cohort of 33 undergraduates from 18 Greater Boston-area schools, including Salem State University, Smith College, and Brandeis University, began the free, 18-month program last summer with an eight-week, online skills-based course to learn the basics of AI and machine learning. Students then split into small groups in the fall to collaborate on six machine learning challenge projects presented to them by MathWorks, MIT-IBM Watson AI Lab, and Replicate. The students dedicated five hours or more each week to meet with their teams, teaching assistants, and project advisors, including convening once a month at MIT, while juggling their regular academic course load with other daily activities and responsibilities.

      The challenges gave the undergraduates the chance to help contribute to actual projects that industry organizations are working on and to put their machine learning skills to the test. Members from each organization also served as project advisors, providing encouragement and guidance to the teams throughout.

      “Students are gaining industry experience by working closely with their project advisors,” says Aude Oliva, director of strategic industry engagement at the MIT Schwarzman College of Computing and the MIT director of the MIT-IBM Watson AI Lab. “These projects will be an add-on to their machine learning portfolio that they can share as a work example when they’re ready to apply for a job in AI.”

      Over the course of 15 weeks, teams delved into large-scale, real-world datasets to train, test, and evaluate machine learning models in a variety of contexts.

      In December, the students celebrated the fruits of their labor at a showcase event held at MIT in which the six teams gave final presentations on their AI projects. The projects not only allowed the students to build up their AI and machine learning experience, it helped to “improve their knowledge base and skills in presenting their work to both technical and nontechnical audiences,” Oliva says.

      For a project on traffic data analysis, students got trained on MATLAB, a programming and numeric computing platform developed by MathWorks, to create a model that enables decision-making in autonomous driving by predicting future vehicle trajectories. “It’s important to realize that AI is not that intelligent. It’s only as smart as you make it and that’s exactly what we tried to do,” said Brandeis University student Srishti Nautiyal as she introduced her team’s project to the audience. With companies already making autonomous vehicles from planes to trucks a reality, Nautiyal, a physics and mathematics major, shared that her team was also highly motivated to consider the ethical issues of the technology in their model for the safety of passengers, drivers, and pedestrians.

      Using census data to train a model can be tricky because they are often messy and full of holes. In a project on algorithmic fairness for the MIT-IBM Watson AI Lab, the hardest task for the team was having to clean up mountains of unorganized data in a way where they could still gain insights from them. The project — which aimed to create demonstration of fairness applied on a real dataset to evaluate and compare effectiveness of different fairness interventions and fair metric learning techniques — could eventually serve as an educational resource for data scientists interested in learning about fairness in AI and using it in their work, as well as to promote the practice of evaluating the ethical implications of machine learning models in industry.

      Other challenge projects included an ML-assisted whiteboard for nontechnical people to interact with ready-made machine learning models, and a sign language recognition model to help disabled people communicate with others. A team that worked on a visual language app set out to include over 50 languages in their model to increase access for the millions of people that are visually impaired throughout the world. According to the team, similar apps on the market currently only offer up to 23 languages. 

      Throughout the semester, students persisted and demonstrated grit in order to cross the finish line on their projects. With the final presentations marking the conclusion of the fall semester, students will return to MIT in the spring to continue their Break Through Tech AI journey to tackle another round of AI projects. This time, the students will work with Google on new machine learning challenges that will enable them to hone their AI skills even further with an eye toward launching a successful career in AI. More