Fostering the next generation of innovators, leaders, and researchers shaping technology to achieve positive societal outcomes
The societal and economic impacts of digital technology are only becoming more powerful, and with it, the growing desire among graduate students, researchers, and practitioners to intentionally shape technology to serve public needs.
The Public Interest Technology (PiTech) Initiative at Cornell Tech is addressing this demand by curating engagement opportunities for graduate students and researchers to apply technical expertise in service of public needs and incorporate public objectives explicitly into the pursuit of technological innovation.
We are building a community of impact-focused scholars and practitioners through PiTech Impact Studio, our Visiting Practitioner's (VIP) Program, and the Siegel PiTech Impact Fellowships for PhDs, Postdocs, and Faculty. Our activities cater to graduate students, postgraduate trainees, and researchers at key stages of their academic and professional career trajectories.
The primary purpose of the PiTech Impact Studio is to deepen students’ understanding of the opportunities and challenges in public interest technology through their engagement with organizations seeking to apply technology to achieve social impact.
Leading public interest technology practitioners engage with Cornell Tech students and community members throughout the semester, offering office hours, mentoring student teams, and providing feedback on product and business ideas.
Supports Cornell University PhD students in technical fields to work with NYC-based nonprofit and public sector organizations during the summer.
Impact Fellows gain exposure to the technology challenges facing public interest organizations and contribute their skills and expertise to strategic projects that advance their host organizations' missions.
Supports postdocs with PhDs in technical fields in harnessing their deep expertise to start a company that addresses the public interest. Fellows join through the Jacobs Technion-Cornell Institute’s Runway Startups Program.
Our NYC-based partner organizations draw from government, civil society, and the nonprofit sector, spanning many critical subject matter domains, including:
Public health: health care provision and accessibility
Social justice: food insecurity, criminal justice reform, and economic inequality
Trustworthy media ecosystems: combatting racism, hate speech, and misinformation
Public services: public service provision, housing, transportation, and civic engagement
Environment: sustainability and conservation
PiTech Success Stories
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PIT Cases: Climate Change AI, Tackling Climate Change with Machine Learning Funding from the PiTech Runway Startup Postdoc program has supported both Priya Donti (a CCAI co-founder) and Maria João Sousa (CCAI’s executive director) as they seek to transfer the skills and knowledge developed through their doctoral programs to the social impact space.
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Innovating Dental Experiences with AR for Autism Serena prototyped an augmented reality (AR) application that converts tactile feedback from key moments of a dental visit into visual and auditory distractions to enhance patients' control over their environment, making dental visits less overwhelming. Having received positive feedback from YAI’s stakeholders, Serena is continuing to collaborate with YAI beyond her fellowship to perform user testing with patients and caregivers, refine the design, and implement it within medical service settings.
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Efficient, but Equitable Access to Information Working with the Mayor’s Office of People with Disabilities (MOPD), Mahika Phutane developed an accessible chatbot for the NYC government website, ensuring equitable access to information for residents with disabilities. Recognizing the inaccessibility of existing chatbots for the visually-impaired, she focused on creating a front-end interface compatible with assistive technologies, such as screen readers, and utilizing ARIA attributes. Mahika is continuing her work with MOPD beyond the fellowship to explore AI integration for intelligent text synthesis and making the chatbot open-source for widespread use.
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Communicating weather data when the stakes are high Working alongside the NYCEM meteorologist and developers to design an online dashboard to help address weather data. The dashboard uses data from the National Oceanic and Atmospheric Administration (NOAA), accessed through an application program interface (API).
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Improving IT Support Workflows at NYC Housing Authority I identified 19 changes based on participant data that could improve the IT ticketing experience (e.g., consistency in naming, increasing the findability of the site, and various design tweaks to improve usability). In a design session with one manager, we sketched out a variety of improvements that we wanted to see based on the proposed changes. Based on these changes, I created a low-fidelity demo on Figma.
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How Can People With Intellectual and Developmental Disabilities Be Supported With Computer Vision AI in the Future? Hauke worked closely with members of YAI’s Center for Innovation and Engagement in exploring how AI-assisted video monitoring technology could help people with I/DD, specifically those with a high risk of seizures, lead independently without labor-intensive, one-on-one staff monitoring. To identify movements of people with I/DD that may indicate seizures, Hauke prototyped a computer vision-based system which utilizes pose and motion recognition and integrated it with a smartphone app for real-time monitoring and alert notifications.
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Statistical modeling of New York City building construction times with the NYC DDC The density and diversity of urban landscapes within the United States’ most populous city present unique challenges to planning construction projects; in particular, being able to accurately estimate the amount of time required for construction is important for allocating resources and ensuring minimal disruption to the neighborhood surrounding a construction project.
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The New York Botanical Garden Canopy Classification Dataset - A Dataset for Machine Learning Tasks in Biodiversity Informatics Biodiversity monitoring is an important task in conservation biology, however, it is resource intensive, requiring time, money, expertise, and a large on–the–ground presence that is not always possible due to conflict, politics, etc. Potentially traditional biodiversity monitoring techniques can be supplemented with an inexpensive tool that utilizes remote sensing data and deep learning models to remotely monitor biodiversity.
