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Brandi Porter

Libraries as AI Literacy Leaders

In this special issue we explore the role that libraries, librarians, and information professionals can play in advancing AI literacy in our workplaces and communities.  AI literacy is a broad term meant to encompass educating users about AI use, production, and evaluation; however, as we can see there is no commonly agreed upon definition as of yet.  The included literature reflects common similarities in the need to incorporate AI literacy into our ongoing work as librarians and educators, while also recognizing that libraries serving such a wide base of communities will need to lead literacy efforts that are uniquely tailored to the populations they serve.

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Troy Davis

The Inward Turn: From AI Outputs to AI Discourse

Librarians have spent decades teaching students to evaluate sources, trace authority, and recognize how information is constructed. We’ve built sophisticated frameworks for this work. The advent of generative AI has obviously intensified these efforts. We’ve provided frameworks for evaluating AI-generated content: Is this output accurate? What biases might it contain? But as we’ve rushed to develop “AI literacy” programming, I wonder if we’ve overlooked a rich space where these same frameworks can be applied: the language we use to describe these systems in our own conversations, instructional materials, task forces, and workshops.

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Ian Y. Song

Can AI Prompting and Academic Libraries Push the Door of Open Access Wider?

The article argues that skilled AI prompting and academic libraries can work together to widen access to scholarly knowledge. As open access grows, AI can explain and synthesize openly available research for broader audiences. But paywalls still limit what AI can analyze, creating visibility gaps between open and closed scholarship. Libraries help address this by improving institutional repositories, supporting OA publishing through transformative agreements, teaching AI literacy, and developing ethical guidelines. Combined, these efforts make research more accessible, understandable, and useful worldwide.

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Ponego Letswalo

Proactive Privacy: Using AI to Automate PII Discovery and Data Subject Access Requests (DSARs)

The regulatory landscape of GDPR, CCPA, and other privacy laws has made fulfilling Data Subject Access Requests (DSARs) a critical yet operationally complex challenge. Manual processes for locating an individual’s data across fragmented systems are slow, error-prone, and struggle to meet mandated deadlines. This article explores how AI-driven privacy tools are transforming compliance from a reactive burden into a proactive strategy.

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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.

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Sheng-Hsiang Lance Peng

Making Sense of REF, Impact and Creative Outputs Through the Infosphere

In the UK higher education landscape, the Research Excellence Framework (better known as the REF) plays a major role in shaping how research quality is understood. And if it’s in a creative-industries university…say somewhere like Falmouth, REF talk can feel especially odd. Suddenly the performance, film, installation, digital game or community project has to be explained using phrases like reach, significance, pathways to impact and it’s like being asked to translate creative souls into spreadsheet cells.

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Azeez Adeoye

Paperless Society: The Prediction That Came Too Early, Yet Came True

In the early 1970s, bold predictions emerged about the coming of a “paperless society.” The concept was first formally introduced by F. W. (Frederick Wilfrid) Lancaster, an information scientist and professor at the University of Illinois, who envisioned that advances in information technology would make paper largely obsolete by the year 2000. In 2025, Lancaster’s once-ambitious vision appears closer to fulfilment. The long-envisioned dream of a paperless society is gradually becoming a tangible reality, as many sectors including education, commerce, governance and healthcare now rely significantly less on paper for their daily operations.

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Anita Coleman

AI-Powered Peer Review: How Review Reveal Can Detect Bias, Improve Fairness, and Transform Scholarly Publishing

When a harsh peer review exposed systemic bias, the author drew on established and emerging research to envision AI‑powered Review Reveal: a tool that flags exclusionary reviewer language, maps critiques to manuscript sections, audits equity‑related phrasing, and suggests inclusive rewrites — protecting intellectual freedom and making global digital knowledge culture more accessible to under‑represented and all participating scholars.

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