Research Initiatives

Current Research Projects

Two diagrams illustrate current research projects in the Innotech research lab. Both projects aim to advance data-driven governance and cyber security policy. The diagram on the left shows the circular interaction among election cyber security, public trust, and voter participation. It shows that the research model applies the following concepts to those three elements: Election Cybersecurity Index for years 2012 to 2014, and Multilevel Longitudinal Datasets. It also applies Survey Experiments to the model. As a result, the project produces evidence-based insights for democratic resilience and graduate training. The diagram on the right shows that AI-generated misinformation, disinformation, and malinformation (MDM) result in the need for three things: crisis management and resilience capacity, public communication and trust building, and regulatory and technical safeguards. Applying an AI MDM response index and comparative framework can help develop actionable strategies for officials and strengthen the democratic process.

Securing Democracy in the AI Era: Election Cybersecurity, Public Trust, and Voter Participation

The InnoTech Policy Lab investigates how election cybersecurity, public trust, and voter participation interact in an era shaped by rapidly advancing artificial intelligence. This project develops a national Election Cybersecurity Index (2012–2024), constructs multilevel longitudinal datasets to analyze how cybersecurity maturity influences voter registration and turnout, and conducts survey experiments to measure how information about cybersecurity protections affects trust and perceptions of election integrity. Through interdisciplinary methods—integrating national datasets, qualitative coding, and AI-supported analytics—the Lab produces evidence-based insights that strengthen democratic resilience while advancing graduate training in data-driven governance, cybersecurity policy, and AI-informed public decision-making.

AI-Driven Misinformation & Election Security

This project examines how U.S. state governments respond to AI-generated misinformation, disinformation, and malinformation (MDM) targeting elections. The Lab systematically analyzes state-level policies, public communication strategies, crisis-response mechanisms, and regulatory/technical safeguards designed to counter misleading election-related content, including synthetic media and fraudulent election websites. Using AI-assisted data collection, careful manual validation, and mixed-methods analysis, the Lab is developing the AI MDM Response Index—a comparative framework evaluating state efforts across:

  • Crisis Management & Resilience Capacity
  • Public Communication & Trust-Building
  • Regulatory & Technical Safeguards

This project offers election officials evidence-based insights, comparative benchmarks, and actionable strategies to protect public trust and strengthen democratic processes in the age of AI.

Research Projects Under Development

Diagram illustration 5 future research direction, all shaping a secure and equitable future through innovative research. The image has five boxes with text and images, each illustrating one of the research areas. The boxes are connected by circuit pathways. Box A depicts a brain, gears, a person touching a flow chart on a tablet, and the caption “AI-Augmented Cybersecurity Decision-Making Tools.” Box B depicts a quantum physics atom surrounding a microchip, a clock, a scroll, and a lock and key. The caption reads “Quantum Computing Policy Paradigms.” Box C depicts a person in a wheel chair making a selection at a voting station, a padlock with a voting ballot on it, and the scales of justice. The caption reads “Voting Cybersecurity and Accessibility.” Box D depicts a woman wearing a headset standing next to a map with emergency alerts on it. On the other side of the map is a robot wearing an antenna. The caption reads “Human–AI Interaction for Crisis Management.” Box E depicts a map of the world in the background, and two landscapes separated by a bridge. One is a model city skyline, and the other is a rural area with antennas, trees, and a stream. Images of a brain hover over each landscape. The caption reads “Digital Divide in Global AI Adoption.”

A. AI-Augmented Cybersecurity Decision-Making Tools

Development of advanced analytical tools that integrate AI modeling with human expertise to support comprehensive cybersecurity preparedness assessments and strategic investment decisions for governments.

B. Quantum Computing Policy Paradigms

Examination of emerging cybersecurity policy frameworks that address quantum computing’s disruptive potential, with a focus on post-quantum cryptography and long-term institutional preparedness.

C. Voting Cybersecurity and Accessibility

Exploration of technological, political, and legal challenges in balancing secure election technologies with improved accessibility for voters with disabilities, including best-practice recommendations for inclusive election administration.

D. Human–AI Interaction for Crisis Management

Analysis of evidence-based strategies to improve human–AI collaboration in emergency and disaster management, focusing on communication, decision-support tools, and coordination effectiveness.

E. Digital Divide in Global AI Adoption

Comparative research examining disparities in AI technology adoption between developed and developing countries, with attention to infrastructure, governance, socioeconomic barriers, and implications for global equity.