About the Initiative

ASCEND-AI (Advancing Student and Collaborative Educator Networks for Digital AI Integration) is a $4 million initiative funded by the U.S. Department of Education’s Fund for the Improvement of Postsecondary Education (FIPSE), with an award period spanning 2026 to 2030. Led by Howard University as the lead institution and Bowie State University as co-lead, ASCEND-AI addresses the critical need for comprehensive AI literacy across Historically Black Colleges and Universities.

The initiative builds strategically on existing NSF-funded infrastructure, including Howard’s HBCU-UP Targeted Infusion Project and Bowie State’s established Faculty Learning Community model. ASCEND-AI positions HBCUs at the forefront of an equity-centered approach to AI workforce development and national competitiveness.

Meet the Leadership

The Problems We're Solving

What We Are Not

Our Three Pillars

Ethical AI

ASCEND-AI Leadership


The ASCEND-AI leadership team brings together scholars, researchers, and practitioners committed to shaping the future of AI education and innovation. Their expertise drives the initiative's vision, implementation, and evaluation, ensuring meaningful impact across education, research, and workforce development.

LaTanya Brown-Robertson, Ph.D.

Principal Investigator, Howard University

l.brown-robertson@howard.edu

Amy Yeboah Quarkume, Ph.D.

Co- Principal Investigator, Howard University

amy.yeboah@howard.edu

Azene D. Zenebe, Ph.D.

Co- Principal Investigator, Bowie State University

azenebe@bowiestate.edu

Rand Obeidat, Ph.D.

Co- Principal Investigator, Bowie State University

robeidat@bowiestate.edu

Erica P. Middleton, MA, PMP

Project Director,

Howard University

erica.middleton@howard.edu

Bianca J. Jackson, PMP

External Evaluator,

BrickRose Exchange

bianca@brickroseexchange.org


The Problems We're Solving


Effective AI adoption requires more than technical proficiency. It requires critical evaluation, metacognitive awareness, sustained engagement, and cross-disciplinary collaboration. ASCEND-AI is advancing solutions that help individuals and institutions develop these essential capacities for the future.


AI Literacy Gap

Faculty and students both encounter AI tools without a disciplinary or ethical framework for responsible integration.

Metacognitive Risk

Research suggests unguided AI use may contribute to ‘metacognitive laziness,’ reducing the self-regulation needed for durable learning

(Fan et al., 2024).

Retention Disconnect

Students who rely on AI for task completion demonstrate short-term performance gains but reduced knowledge retention and transfer

(Bastani et al., 2024).

Cross-Disciplinary Gap

Existing AI tools and curricula are rarely designed for the disciplinary diversity of HBCU student populations and faculty expertise.


For faculty, ASCEND-AI provides literacy modules to create practical tools and frameworks for integrating AI into teaching, research, and professional practice while supporting informed decision-making about AI use in their disciplines.


For students, ASCEND-AI utilizes AI literacy modules to build foundational AI knowledge, develop skills for evaluating AI-generated information, and prepares them to navigate an increasingly AI-enabled academic and professional landscape.


What We are Not


ASCEND-AI is not a course about AI tools. It is a structured learning experience designed to move faculty and students from AI dependency to agency, and from consumption to stewardship.


This is not a technology training. It is a capability-building experience.

  • This is not about learning to use a specific tool. Tools change. Judgment, agency, and stewardship do not.

  • This is not additional work layered on top of your courses. It is designed to integrate into what you already teach and study.


Three Pillars:
Agency, Integrity, Innovation

Pillar 1: Agency First

Human thought before tools. Your thinking comes first. Always.


What This Means:

  • You draft, analyze, and reason before asking AI for assistance

  • AI accelerates your work; it does not replace your thinking

  • You maintain intellectual ownership of your ideas

  • You can explain, defend, and extend your work without AI

In Practice:

  • Write your first draft without AI, then use AI for editing suggestions you evaluate critically

  • Develop your analytical framework before asking AI to help structure it

  • Form your argument before testing it against AI-generated counterpoints 

Pillar 2: Integrity Always

Truth and verification are human responsibilities. AI does not get to decide what is true.


What This Means:

  • You verify AI outputs before trusting them

  • You document uncertainty transparently

  • You cite sources you’ve actually checked, not sources AI claims exist

  • You maintain professional standards even when AI makes shortcuts tempting

In Practice:

  • Check every citation AI provides, many are fabricated

  • Verify statistics and claims using primary sources

  • Acknowledge when you cannot verify something rather than presenting it as fact

  • Maintain disciplinary rigor in AI-assisted work

Pillar 3: Innovation in Context

Impact over novelty. The question is not “can we?” but “should we, and for whom?”


What This Means:

  • Innovation serves real communities and addresses genuine problems

  • Efficiency is not neutral speed can harm when it bypasses necessary judgment

  • Technology must support human judgment and decision-making, not substitute for it

  • Solutions are evaluated for impact, sustainability, and accountability to the people they serve

In Practice:

  • Ask “who benefits?” and “who might be harmed?” before deploying AI

  • Evaluate whether AI actually solves the problem or just automates a flawed process

  • Consider whether “faster” undermines quality, fairness, or accountability

  • Design with affected communities, not just for them


Three Pillars: Agency, Integrity, Innovation

Pillar 1: Agency First

Human thought before tools. Your thinking comes first. Always.


What This Means:

  • You draft, analyze, and reason before asking AI for assistance

  • AI accelerates your work; it does not replace your thinking

  • You maintain intellectual ownership of your ideas

  • You can explain, defend, and extend your work without AI

In Practice:

  • Write your first draft without AI, then use AI for editing suggestions you evaluate critically

  • Develop your analytical framework before asking AI to help structure it

  • Form your argument before testing it against AI-generated counterpoints

Pillar 2: Integrity Always

Truth and verification are human responsibilities. AI does not get to decide what is true.


What This Means:

  • You verify AI outputs before trusting them

  • You document uncertainty transparently

  • You cite sources you’ve actually checked, not sources AI claims exist

  • You maintain professional standards even when AI makes shortcuts tempting

In Practice:

  • Check every citation AI provides, many are fabricated

  • Verify statistics and claims using primary sources

  • Acknowledge when you cannot verify something rather than presenting it as fact

  • Maintain disciplinary rigor in AI-assisted work

Pillar 3: Innovation in Context

Impact over novelty. The question is not “can we?” but “should we, and for whom?”


What This Means:

  • Innovation serves real communities and addresses genuine problems

  • Efficiency is not neutral speed can harm when it bypasses necessary judgment

  • Technology must support human judgment and decision-making, not substitute for it

  • Solutions are evaluated for impact, sustainability, and accountability to the people they serve

In Practice:

  • Ask “who benefits?” and “who might be harmed?” before deploying AI

  • Evaluate whether AI actually solves the problem or just automates a flawed process

  • Consider whether “faster” undermines quality, fairness, or accountability

  • Design with affected communities, not just for them


People in a boardroom

Ethical AI

Responsible AI integration stands at the center of the ASCEND-AI curriculum. Our approach is grounded in the principle that AI serves as amplification rather than replacement of human expertise. Faculty and students engage with AI through a framework of critical evaluation: questioning outputs, verifying sources, identifying bias, and considering whose perspectives may be absent from AI-generated content.

This approach ensures that ASCEND-AI graduates are not passive recipients of AI tools but active stewards who evaluate AI solutions through the lenses of impact, ethics, and disciplinary rigor.

Email

info@ascend2gether.ai

LinkedIn

ascend2getherai

Instagram

@ascend2getherai

© 2026 ASCEND-AI. A U.S. Department of Education FIPSE Initiative. Howard University, Lead Institution.


This project is supported by the U.S. Department of Education’s Fund for the Improvement of Postsecondary Education (FIPSE). The content of this website does not necessarily represent the policy of the Department of Education, and endorsement by the federal government should not be assumed.

Email

info@ascend2gether.ai

LinkedIn

ascend2getherai

Instagram

@ascend2getherai

© 2026 ASCEND-AI. A U.S. Department of Education FIPSE Initiative. Howard University, Lead Institution.


This project is supported by the U.S. Department of Education’s Fund for the Improvement of Postsecondary Education (FIPSE). The content of this website does not necessarily represent the policy of the Department of Education, and endorsement by the federal government should not be assumed.

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