The Laboratory for Social Machines develops data science methods — primarily based on natural language processing, network science, and machine learning — to map and analyze social systems, and designs tools that enable new forms of human networks for positive change.
We are mapping the intersection of news, entertainment and social media at scale to better understand the interaction of media and behavior in a range of domains including US national politics and democracy, food behavior, and video based storytelling. Our insights into media dynamics will guide interventions that positively impact behavior at scale — for example, from building empathy and connections across polarized groups, to helping people understand and improve their food choices.
Inspired by Montessori’s and Papert’s ideas of child-driven learning combined with the potential of digital social networks, we are designing and deploying technologies to support young children in learning skills of early literacy, story-telling, and self-expression. We design playful learning experiences for children, play analytics to derive insights into child activity and learning, and support for parents/caregivers to provide guidance and feedback to their children. Ultimately we seek to create sustainable community learning networks that bring together families with learning coaches for effective and efficient child-driven, machine-guided learning.
We have an interdisciplinary team with backgrounds that include machine learning & AI, interaction design, cognitive science, child development & education, journalism, marketing, and constitutional law. We are committed to deploying our research through partnerships with external organizations such as the news media, education non-profits, businesses and advocacy groups.