Summary:

 House Memorial 2 (HM 2) requests the Legislative Education Study Committee (LESC) to convene an Education Data Governance and Artificial Intelligence Working Group during the 2025 legislative interim. The working group is tasked with studying and recommending a statewide structure for education data governance and policies to address artificial intelligence in educational institutions. The memorial highlights the importance of high-quality, collaborative, and secure data systems for improving educational outcomes and addressing the unique needs of New Mexico stakeholders. 

Legislation Overview:

 House Memorial 2 (HM 2) highlights the critical importance of accurate and accessible education data for supporting students, educators, and policymakers in New Mexico. The memorial addresses challenges related to data quality caused by administrative silos, insufficient collaboration among agencies, and the increasing influence of artificial intelligence in education. To address these issues, the Legislative Education Study Committee (LESC) is requested to convene a working group composed of representatives from key state agencies managing education and workforce data, such as the Public Education Department, Higher Education Department (HED), and Early Childhood Education and Care Department. The group would also include legislative representatives from the LESC and Legislative Finance Committee, school district superintendents, charter school administrators, higher education faculty, and representatives of Indian nations, tribes, and pueblos to ensure culturally sensitive governance. Additionally, experts in data governance, artificial intelligence, and data privacy, along with stakeholders representing diverse backgrounds, including race, culture, geography, and age, would contribute to the group’s work.

The working group is tasked with studying several topics, including the current status of state education data systems and opportunities for interoperability, data privacy and sovereignty with a focus on culturally sensitive information, and the role of artificial intelligence in education. Particular attention will be given to ensuring equitable access to AI, protecting data, and preserving meaningful human connection in classrooms. The group will also examine data governance structures that improve collaboration and quality assurance, as well as identify resource requirements such as funding, staffing, and technology to formalize a statewide governance framework.

By October 31, 2025, the working group is expected to deliver recommendations to the LESC on a formal statewide data governance structure, policies for managing education data and artificial intelligence, and legislative actions to enhance data systems. These recommendations aim to foster collaboration, improve data quality, and address emerging challenges in education data management.

Implications

Improved Data Quality:
The proposed governance framework aims to address issues with inconsistent, incomplete, or unreliable data, which currently hinder effective program evaluations and decision-making.

Artificial Intelligence Integration:
By focusing on AI policies, the memorial ensures the state leverages AI responsibly and equitably while addressing privacy concerns and protecting cultural contexts, particularly for Indian nations, tribes, and pueblos.

Collaboration and Coordination:
The memorial emphasizes collaboration across state agencies, educational leaders, and stakeholders to reduce silos, promote transparency, and foster timely and actionable data insights.

Fiscal Considerations:
While HM 2 does not appropriate funds, implementing its recommendations may require additional resources for staffing, technology, and inter-agency coordination. Addressing these needs will likely involve future legislative funding requests.

Current Context

New Mexico’s education data systems face persistent challenges, including poor-quality reporting, siloed administration, and limited interoperability. The RISE NM longitudinal data system under development by the HED represents progress but lacks comprehensive governance. HM 2 builds on this effort by advocating for a cohesive framework that incorporates AI considerations and addresses statewide data needs.