Artificial Intelligence - Information Matters

In the past year, the focus of AI in education has shifted from generating content to evaluating its quality. While large language models can now produce vast amounts of material in seconds, ensuring that this content is accurate, reliable, and pedagogically sound remains a challenge. Emerging research shows that using AI as an evaluator is still unreliable, making human judgment more essential than ever. In this new paradigm, the real bottleneck is no longer creation but validation.

Original

March 16, 2026 Lynne Bowker

Breaking Down Language Barriers to Reduce Information Privilege in Scholarly Communication

For decades, English has been a lingua franca in the research community, where it has become the principal language for publishing and conferences. But when one main language is used to share information, knowledge of this language is also needed to access information. In this way, English has become linked to information privilege: people who have mastered English can access scholarly information more easily than people who are less comfortable in this language. This has ripple effects, influencing the extent to which scientists can participate fully in scholarly communication. While the problems are clear, the solutions are trickier.

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March 11, 2026 Tova Harris

Who Gets to Train the Machine? AI, Race, and Storytelling in Library Makerspaces

As generative AI tools move into library makerspaces, they do more than draft metadata or translate text—they reflect the power structures embedded in the spaces where they are deployed. Without intentional design, we risk automating the very inequities libraries seek to dismantle.

Education Opinion

February 19, 2026 Patrick Jerry

Speaking the Language of AI

This is the conclusion I’ve come to after witnessing the growing popularity of AI tools. AI is everywhere, despite its propensity to produce misleading or incorrect information, and the moral objections of workers who fear losing their livelihoods. Why do patrons choose AI tools while more reliable (and less controversial) options sit on the shelf?

Education Featured

February 5, 2026 Omorodion Okuonghae

From Smart Libraries to Intelligent Edges: Exploring the Potential of TinyML in the Future of Library Services

Among the most recent AI developments with the potential to significantly transform library services is tiny machine learning (TinyML). TinyML is a low-latency technology that enables intelligent, on-device decision-making without requiring data transmission to the cloud for processing.

Education Featured Opinion

February 3, 2026 Elisa Tattersall Wallin

How Will You Respond to the Unacceptable Costs of GenAI?

We must remember that those who profit the most from our growing reliance of GenAI are the tech companies themselves. Meanwhile, the people who are the most excited about AI are the ones who understand it the least. While machine learning can be useful, I argue that GenAI comes at an unacceptable cost. Taking in to consideration GenAI’s role in the spread of disinformation, the complex damages caused to people and the planet along with the proven negative effect to cognitive skills among users, this text advocates for critical perspectives, and ideally, critical refusal of GenAI.

Education Featured

January 15, 2026 Dan Wu

Exploring the Future of Human–AI Collaboration: Insights from “Human–AI Interaction and Collaboration”

How should people and AI work together in ways that are useful, ethical, and trustworthy? Edited by Dan Wu and Shaobo Liang (Wuhan University), “Human–AI Interaction and Collaboration” maps the fast-moving terrain where users, systems, and information meet—treating human strengths and machine strengths as complements, not substitutes. The introduction frames collaboration as a user-centered endeavor that must balance capability with ethics, transparency, and trust.

Featured Translation

December 19, 2025 Evelyn Cox

AI in a Tribal Context: Diverse Perspectives Matter in a Changing Landscape

With Artificial Intelligence’s (AI) seemingly increasing integration into various aspects of society, nations worldwide—including Tribal Nations—are assessing its impact on the changing landscape. AI is a revolutionary technology that poses potential opportunities and risks for federally recognized Indian Tribes (Tribal Nations or Tribes) and their citizens. This article provides an overview of the literature related to AI in a tribal context.

Education Featured

December 18, 2025 Breanne Kirsch

Preparing Librarians for the Generative AI Age

In this paper, we explore successful AI training initiatives, resources and networks for librarians, AI integration strategies, and implications of AI for library services. Join me in discovering best practices for preparing librarians as leaders in the generative AI era and integrating AI into library services.

Original

December 3, 2025 Ponego Letswalo

The AI-Powered Third-Party Risk Manager: Continuously Monitoring Vendor Security Posture

Modern enterprises are increasingly vulnerable to cyberattacks through their third-party vendors, with over half of all data breaches now originating in the supply chain. Traditional third-party risk management (TPRM), reliant on manual, point-in-time assessments like annual questionnaires, is ill-equipped to address the dynamic nature of cyber threats. This paper proposes an AI-powered TPRM framework as a transformative solution. By enabling continuous, real-time monitoring of vendor security posture – AI streamlines risk assessments using intelligent questionnaires and provides dynamic, multi-factor risk scoring to prioritize critical vendors. The integration of AI into TPRM represents a paradigm shift from a static, reactive process to a dynamic, intelligent, and continuous safeguard, essential for security in an interconnected digital ecosystem.