Knowledge Resource · Open access
Research Summary: Research: Evidence-informed policymaking and fast-changing technology
- Original authors
- Attribution requires verification
- Original source
- UK Department for Education
- Summary & Analysis prepared by
- Aziz Shuaib Ausi
- Resource type
- Research Summary / Knowledge Resource
- Resource published on AZIZ OS
- 25 September 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
About this Summary & Analysis
AZIZ OS provides independently prepared summaries and analytical interpretations of externally published research and knowledge sources. The underlying works remain attributable to their original authors and rights holders. This resource is intended to improve accessibility and understanding and does not replace the original publication.
The UK Department for Education has released a report outlining principles for evidence-informed policymaking in contexts involving rapidly evolving technology, citing artificial intelligence in education as a key example. This initiative aims to address the challenges of developing policy effectively when technological advancements are swift.
Why it matters
This development is strategically important as it highlights the increasing challenge of governmental bodies to formulate effective policy in rapidly evolving technological landscapes. Establishing clear principles for evidence-informed policymaking can enhance the agility and responsiveness of regulatory frameworks, ensuring that societal benefits are maximised while risks are mitigated.
Key insights
- The report proposes principles specifically for evidence-informed policymaking.
- These principles are designed for application in fast-changing technology contexts.
- Artificial intelligence in education is presented as an illustrative domain for these principles.
Source
UK Department for Education — https://www.gov.uk/government/publications/evidence-informed-policymaking-and-fast-changing-technology
Related resources
Previous
Research: Understanding independent scrutiny in safeguarding partnerships
Next
Guidance: SEND training for schools: guide to materials
Functional Emotion Without Character: Large Language Models, Aristotelian Disposition, and the Limits of Behavioral Alignment
Knowledge Resource
AI-inferred expressed well-being and collective-action discourse in climate-change campaigns on X
Knowledge Resource
The Tethys Dataset: Seven Years of Hourly Smart Water Metering and a Pipeline for Making It Usable
Knowledge Resource
When Disability Disclosure Travels: Memory, Privacy, and Contextual Integrity in Conversational AI
Knowledge Resource
Convex AI Compositionality and the Governance of AI System Populations
Knowledge Resource
When Who You Are Can Change the Code You Get: A Study of Persona-Induced Bias in LLM Code Generation
Knowledge Resource
Citation
Cite the original work (APA 7)
The original source is authoritative for this citation. Cite the source publication directly — this attribution is pending verification. Open the original source.
Verification
This is an authenticated AZIZ OS resource record.
- Verification ID
- ASA-EXE-2026-00830
- Version
- v1.0 · r0
- Issued
- 25 September 2026
- Resource prepared by
- Aziz Shuaib Ausi
- Resource status
- Research Summary / Knowledge Resource
- Underlying work
- Research: Evidence-informed policymaking and fast-changing technology
- Original authors
- Attribution requires verification
- Original source
- UK Department for Education
- Provenance status
- Attribution requires verification
- Rights
- Underlying publication rights remain with the respective copyright holder(s). Refer to the original source for authoritative publication and licensing information.
This verification confirms the AZIZ OS resource record and its documented provenance. It does not establish authorship of the underlying external work.