As we have explored the implications of AI in education, we hypothesized that “Ease is the Enemy,” arguing that deep learning requires a certain level of “productive difficulty” to build resilience. As we look toward the recent insights from the ASU+GSV Summit, a nuance emerges: while struggle is essential for learning, inequity is an unproductive barrier.
The mission of the ASU+GSV Summit is clear: ALL people deserve equal access to the future. In an AI-driven world, achieving that goal means moving beyond using technology to simply make old tasks faster. It requires us to choose a “pro-human” path that uses AI as a “bicycle for the mind” to expand agency rather than just automate work.
Choosing the human path
According to recent research from MIT Sloan, we are at a crossroads. We can use AI to automate and replace human labor, or we can use it to redesign work and education around human strengths.
The stakes are massive. The McKinsey Global Institute estimates that $2.9 trillion of economic value could be unlocked in the U.S. by 2030, but only if organizations redesign workflows around humans and AI agents working together. This “Skills Coalition” has tripled in size over the last year, proving there is a global hunger for responsible, accessible AI literacy.
Personalization as an equity tool
One of the most promising avenues for equity is Competency-Based Education (CBE) and personalized learning. As we noted in March, the vision of an “adaptive learning companion,” like the one in Neal Stephenson’s The Diamond Age, is no longer science fiction.
- Meeting Learners Where They Are: In Cambodia and the Philippines, the “High Touch, High Tech” (HTHT) initiative is using AI to help struggling students catch up while allowing advanced learners to accelerate.
- Agentic AI in the Classroom: At Arizona State University (ASU), a new partnership with will.i.am and NVIDIA is creating EDU.FYI, a platform designed to help students use AI agents to amplify their own creativity and ambitions.
- Reducing Cognitive Load: AI can now re-explain complex concepts using visual aids or audio narration, breaking content into manageable segments that match a student’s specific strengths.
Inclusion by design
We often say that “we can’t design a glove without knowing the hand”. For education to be truly transformative, it must impact the actual experience of the student and teacher. AI is becoming the “bridge” to a more inclusive academic world through very practical applications:
| Tool category | Impact on equity |
| Accessibility | Tools like ReadSpeaker and Otter.ai provide audio and real-time transcription for visually or hearing-impaired students. |
| Language | DeepL and other translation tools break down barriers for multilingual learners, ensuring “brilliant voices” aren’t silenced by a language gap. |
| Personalization | Ambient AI creates a “ubiquitous data profile” that allows for continuous, real-time feedback rather than relying on after-the-fact testing. |
From sorting to support
For too long, higher education has functioned on a model of “sorting and scarcity”. As ASU President Michael Crow suggests, we must move out of these “19th-century” ways of assigning value.
If AI becomes “ambient,” as common as the air we breathe, the question shifts from if we use it to how we use it. Will we use it to build the “Primer” (a tool for developmental growth) or the “Panopticon” (a tool for surveillance and control)?
The moral choice hiding inside our technology strategies is simple: Does this tool serve learner agency, or institutional extraction? By focusing on equity by design, we ensure that AI doesn’t just make education easier for some—it makes it possible for everyone.
How is your institution currently balancing the need for “productive struggle” with the power of AI to remove unproductive barriers?
