Key Takeaways
- The 1776 Labs event, created by OnGov, brought together government officials, university students, and private‑sector technologists to co‑design practical AI solutions for public‑sector challenges.
- Participants tackled real problems such as Adverse Childhood Experience (ACE) scoring for the HEAL PA coalition and simplifying access to government services for Team PA, producing tangible prototypes rather than theoretical discussions.
- A human‑in‑the‑loop approach was emphasized as essential for responsible AI deployment, ensuring that technology aligns with public trust, legal constraints, and procurement realities.
- The event highlighted a growing appetite among students to engage with government work early in their careers and demonstrated how rapid prototyping can accelerate innovation while minimizing risk.
- OnGov plans to expand the model beyond Pennsylvania, seeking partnerships with other universities and local governments to democratize AI‑enabled public‑sector solutions nationwide.
Overview of the 1776 Labs Inaugural Event
The first 1776 Labs gathering, organized by government‑technology firm OnGov, took place on April 17 at the University of Pennsylvania. The event was deliberately designed to move beyond superficial panels about the future of artificial intelligence and instead provide a hands‑on environment where government stakeholders, students, and builders could jointly develop concrete solutions to pressing public‑sector problems. Attendees included Pennsylvania’s Chief Information Officer Bry Pardoe, representatives from the multisector coalition HEAL PA, the nonprofit Team PA, and private‑sector partners such as Amazon Web Services and OpenAI. Academic sponsors from UPenn’s Wharton School, Fels Institute of Government, and Penn Venture Lab also lent support, underscoring the cross‑disciplinary nature of the initiative.
Motivation Behind the Event: Bridging the AI Readiness Gap
OnGov founder and CEO Silas Deane opened the event by noting that while many governments express enthusiasm for AI, actual adoption remains uneven. He argued that officials do not need another discussion of AI’s potential; they require usable models that respect public trust, legal frameworks, and procurement processes. Deane also highlighted the enthusiasm of university students who are eager to apply their skills to community‑focused government work. By creating a collaborative platform, 1776 Labs aimed to satisfy both sides: giving governments access to fresh talent and iterative prototyping, while offering students a meaningful way to contribute to public‑sector innovation.
Structure and Goals of the Hands‑On Exercise
The core of the event consisted of small, mixed teams tasked with developing prototypes to address specific challenges submitted by participating organizations. Importantly, the outcomes were not required to be AI‑powered; any feasible solution that could be built and tested within the event’s timeframe was welcomed. This flexibility allowed participants to focus on problem‑definition and user‑centered design first, then decide whether AI would add value. The emphasis on rapid iteration and “try‑and‑fail‑forward” mentality aimed to reduce the perceived risk of experimenting with emerging technologies in a government context.
Case Study: HEAL PA and ACE Scoring
One team partnered with HEAL PA Director Jesse Kohler to address the fragmentation of trauma‑informed care across Pennsylvania. Their goal was to improve communication and information sharing among the various groups involved in the coalition. During the session, the team produced what Deane described as a “legitimate prototype” for Adverse Childhood Experience scoring—a tool that could standardize data collection, trigger appropriate referrals, and facilitate secure sharing of relevant information. Kohler noted that the prototype already showed promise for eventual launch, illustrating how a focused, hands‑on sprint can move a concept from idea to a deployable artifact in a matter of hours.
Case Study: Team PA and Access to Government Services
Another team, working with Team PA President and CEO Abby Smith, tackled the challenge of simplifying the application process for state funding. Smith described the initiative as a “Team PA bingo board” because it intersected government, private‑sector, and academic interests. The team explored how AI could lower barriers to entry for organizations with limited administrative capacity, making it easier for them to discover eligibility criteria, complete applications, and track status. Smith emphasized that the event’s practical approach allowed participants to experiment, learn from missteps, and refine ideas without the usual bureaucratic overhead that often stalls innovation.
Philosophy of AI Implementation: Human‑in‑the‑Loop
Bry Pardoe articulated a guiding principle for AI adoption in government: successful implementation requires “hitting the right nail with the right hammer.” She stressed that technology must be introduced with a human‑in‑the‑loop to ensure accountability, ethical considerations, and alignment with public values. By keeping humans central to the design and testing process, governments can harness AI’s power while mitigating risks related to bias, privacy, and misuse. Pardoe praised the event’s prototyping speed, noting that the ability to build and test ideas quickly is one of the most powerful tools state agencies have for exploring AI applications responsibly.
Student Engagement and Career Pathways
Throughout the day, organizers observed a palpable enthusiasm among the student participants. Deane remarked that students are “hungry” to solve real government challenges and see tangible impact from their work. The event served as an early exposure to public‑sector careers, reinforcing the value of civic tech and encouraging students to consider roles that blend technical expertise with public service. Pardoe echoed this sentiment, noting a burgeoning interest in government work among young talent and asserting that initiatives like 1776 Labs help bridge the gap between academia and public institutions.
Future Expansion and Vision for Nationwide Impact
Looking ahead, Deane indicated that the success of the inaugural 1776 Labs has sparked interest from universities outside Pennsylvania to host similar events. He envisions a replicable model where local governments, academic institutions, and private partners co‑create solutions tailored to community‑specific needs. Potential future gatherings could involve Pittsburgh’s mayor and regional schools, extending the collaborative framework to additional locales. Deane’s ultimate aspiration is to “rethink how American government can be for the AI era,” advocating for practical, deployable, and useful technology that directly serves citizens rather than pursuing costly, one‑size‑fits‑all solutions that often fail to meet real‑world needs.
Conclusion: Lessons for Public‑Sector Innovation
The 1776 Labs event demonstrated that meaningful progress in government AI adoption is achievable when stakeholders prioritize problem‑driven, hands‑on collaboration over theoretical discourse. By bringing together diverse perspectives—government officials seeking practical tools, students craving impactful projects, and technology partners offering resources—the event produced prototypes that addressed genuine public‑service challenges, such as trauma‑care coordination and funding‑access simplification. The emphasis on human‑in‑the‑loop design ensured that ethical and legal considerations remained central. As OnGov plans to scale this model, the lessons from 1776 Labs offer a blueprint for democratizing innovation, fostering early talent pipelines, and building AI‑enabled solutions that are both trustworthy and effective for the communities they serve.