The Google Faculty Groups, or GFG, event series kicked off June 10 with a vital conversation: Faculty Professional Learning in the AI Age. Joining the panel were Dr. Eric Carbaugh, a professor at James Madison University, and Dr. Leah Lattimore, a program manager on the Google for Education Impact Team, to explore how institutions can navigate this shifting landscape.
The overarching takeaway was clear: Effective AI integration requires institutions to shift focus away from technical tool mastery and anchor themselves firmly in instructional intent, learning science, and human-centered pedagogy.
Here are the key themes and insights from the discussion:
Moving Beyond the Tool: Prioritizing Instructional Intent
Institutions frequently over-index on technology itself, which can stall deeper pedagogical conversations. Lattimore emphasized that professional learning must start with a clear understanding of an institution’s unique landscape and policy context. Rather than chasing every new tool, development should focus on sustainable impact, learning frameworks, and the specific classroom problems faculty are trying to solve.
"We never want to be so tool focused or tool forward that we lose the impact and the intent that's behind the learning science," Lattimore said.
Dr. Leah Lattimore
The Spectrum of Faculty Entry Points
Faculty expertise is not monolithic; it exists on a sliding scale from absolute novices to expert users leveraging AI in advanced research. Carbaugh noted that professional development cannot be one-size-fits-all. Institutions must design customized engagement strategies that meet professors at their current comfort levels and respect their disciplinary constraints.
Furthermore, institutions must acknowledge the time required for faculty to thoughtfully redesign courses and offer structures that support that work.
"If you’re at the novice level, if you haven’t even played around with AI and thinking about how it impacts your students... then what’s an entry point there?" Carbaugh asked. "What opportunities are we providing for faculty to be able to spend that time... redesigning a course? Because that takes a lot of time and effort".
Re-Evaluating Academic Integrity and Stigma
Higher education has historically struggled to establish a truly shared understanding of academic integrity. Carbaugh pushed back against the default suspicion or stigma that assumes any AI utilization by students or faculty is inherently dishonest. When faculty feel isolated or defensive about using standard language-refining tools in their own annual reviews, it signals a deeper institutional disconnect.
We need explicit, transparent campus conversations to define acceptable use boundaries rather than playing a guessing game.
"There's always this sort of assumption of... if you're using AI, you're using AI inappropriately," Carbaugh said. "And I think that we really need to push back against that stigma a little bit as well".
Dr. Eric Carbaugh
Transforming Assessment to Center the Human
Because traditional evaluation methods like standard essays can no longer reliably measure standalone student understanding, AI is forcing an overdue re-evaluation of assessment practices. Carbaugh argued that the best path forward is to design assessments that are fundamentally more human—focusing heavily on relevance, authenticity, and meaningful student engagement. Whether looking at coursework or the administrative lift of a dissertation, maintaining a "human in the loop" ensures academic rigor while freeing up cognitive space for higher-order inquiry.
"Wait a minute, you mean that essay that I always send with students to do and bring in is no longer necessarily a valid representation of their learning?" Carbaugh said. "If we don't fall back on best practices for learning, best practices for assessment... then I think we're doing a disservice to faculty and to students".
Equity, Access, and Systemic Uncertainty
While AI tools have the profound potential to level the playing field for scholars lacking traditional resources, they also risk further disenfranchising communities that lack access or structured training. On the student side, many face immense anxiety entering an uncertain job market while receiving fragmented, messaging about AI from their instructors.
"Where AI can... create this kind of leveling playing field, there is also the concern that there will be further disenfranchisement if we aren't thinking systemically around who has access how," Lattimore warned. Carbaugh added that students are "entering into a job market that's very uncertain right now... and what jobs that's taking away and how they can use AI to be successful".
Practical Takeaways for Faculty
- Lead with Inquiry: Do not feel pressured to have all the answers right away. Lattimore recommended starting small by embracing an "I don't know" mindset and identifying a single trusted professional voice or resource to build knowledge incrementally.
- Focus on the Assessment: Look closely at your current syllabus. Evaluate how you can pivot your assessments to center on authentic, human performance and real-world application rather than easily automated outputs.
What's Next?
- Join the Community: Continue this conversation and share your thoughts on the future of professional learning with peers worldwide on our GFG Discussion Thread.
- Next Event (June 24): The series will return with Dr. James Basham and Dr. Elizabeth Bauer to examine the mechanics of cognitive offloading and intentional learning experiences. Register via the HE Community Events Page or go straight to the Session Link.
- July Assignment Redesign Cohort: Ready to fix an assignment that isn't working? Apply for our free, four-week asynchronous global cohort focused on lowering the threat of AI offloading while elevating authentic discipline application. Space is limited, so submit your application via the Cohort Registration Form.
Shared Event Resources
- The AI Assessment Scale
- CAST Universal Design for Learning (UDL) Guidelines
- Peter Senge's Fifth Discipline Model (Learning Organizations)
- The Opposite of Cheating (Gallant & Reinger)
- Dr. Elizabeth Bauer — Research on Moving Beyond AI Hype
- Dr. James Basham — CIDDL Artificial Intelligence Frameworks
- The Power of Saying "I Don't Know"
Related Google AI Educator Series Content
For structured, pedagogical-first modules designed specifically for higher education contexts, explore the main Google AI Educator Series Portal or dive into these highlighted sessions from last night's conversation:
- Main GES Landing Page
- GES Session 25: Gemini and Grant Writing
- GES Session 26: Synthesize Research Findings
This content was created by a human and refined by Gemini.
