Responsible AI at Nebraska Engineering
Building a culture where artificial intelligence amplifies human creativity, strengthens learning, advances research, and serves society responsibly.
The PRAIRIE Initiative promotes a practical, human-centered approach to artificial intelligence—one that balances innovation with ethics, transparency, and accountability. Explore our foundational guidance documents and learn how responsible AI can enhance teaching, learning, research, and professional practice.
Responsible AI is More Than Technology
Artificial intelligence is transforming engineering education, research, and industry. To realize its full potential, AI must be implemented intentionally—with clear expectations, ethical considerations, and a commitment to preserving human judgment.
At PRAIRIE, responsible AI means creating systems and practices that:
- Empower people rather than replace them
- Promote transparency and accountability
- Support equitable access to AI technologies
- Protect privacy and institutional data
- Develop graduates who can think critically alongside AI
PRAIRIE White Papers
These white papers establish Nebraska Engineering's framework for responsible AI integration. Together they provide both the conceptual foundation and the practical guidance for using AI across teaching, learning, research, and professional practice.
Responsible AI in Teaching and Learning
As generative AI becomes part of higher education, instructors and students need practical guidance for using these tools responsibly. This white paper presents a framework that encourages meaningful learning while preserving academic integrity, human judgment, and durable skill development.
Rather than asking whether AI should be used, the paper focuses on how AI can be integrated thoughtfully to improve learning outcomes while maintaining educational excellence.
Key Topics:
- Purposeful AI Use
- Transparency
- Academic Integrity
- Critical AI Literacy
- Equity & Access
- Privacy & Data Protection
Who Should Read This?
- Faculty
- Instructors
- Teaching Assistants
- Students
- Academic Leaders
Shared Language for Responsible AI Integration
Successful AI adoption requires more than policies—it requires a common vocabulary. This publication establishes a shared language for discussing AI across education, research, administration, and industry collaboration.
By defining consistent terminology and concepts, the framework helps faculty, students, administrators, and partners communicate more effectively about responsible AI implementation while reducing ambiguity across disciplines.
What You'll Learn:
- Common Definitions
- Cross-Disciplinary Communication
- Responsible Decision-Making
- Institutional Alignment
- Research Collaboration
- Future Readiness
Who Should Read This?
- Faculty
- Researchers
- Staff
- Graduate Students
- Industry Partners
- Institutional Leaders