AI - Information Matters

We’ve been sold a lie about human-AI collaboration. The truth is far more unsettling: humans and AI don’t operate on different levels—they operate in fundamentally incompatible realities. One experiences genuine uncertainty and constructs meaning through time; the other executes pattern-matching in milliseconds without ever “knowing” anything at all. It’s time to stop pretending they’re teammates and start designing for what they actually are: oil and water.

Editorial

September 18, 2025 Chirag Shah

The Chatbot Crisis: Why We’re Failing Our Children Before They Even Ask for Help

AI chatbots become less safe the longer you talk to them, yet mental health conversations are precisely the extended dialogues where safety fails most catastrophically. As the FTC investigates tech companies, we must confront why children seek help from algorithms instead of the adults who should be there for them.

Editorial

August 13, 2025 Chirag Shah

Is AI the New Plastic?

AI is the new plastic because our relationship to it is proving just as short-termist. There isn’t enough evidence to suggest that we are planning, as a planet, for AI’s long-term risks. We’re governed mostly, in fact, by what AI is doing now.

Education Original

June 15, 2025 Azeez Adeoye

Fear, Concern, and Collapse of Artificial Intelligence Tools: Perspectives of an Academia

Technology is not a bad invention, but the inability to be human after its adoption and use is what is challenging human existence. Young adults see technology as demi-gods and adore AI without employing critical thinking. Despite their digital nativeness, there is a lack of skills to critically interrogate AI tools and decipher their output or results. Many young adults do not know that AI is prone to error, stemming from the large language models (LLM) upon which it operates. Therefore, there is a greater need for critical digital literacy skills — now more than ever.

Editorial

June 10, 2025 Chirag Shah

How Do You Like Them Agents?

As autonomous agent technologies rapidly permeate our digital landscape, a critical question emerges: what roles should computational agents fulfill to best augment human capabilities? The capabilities of today’s agents—from voice-activated personal assistants to code-generation systems—continue to expand dramatically, prompting urgent questions about their optimal design, function, and integration into human activities. Despite significant technical advances, we lack a coherent framework for conceptualizing the different relationships humans might have with agents, hampering both the evaluation of existing technologies and the principled design of future systems.

InfoFire

April 17, 2025 Shalini Urs

IR Meets AI: Looking Back, Looking Forward — A Conversation with Stephen Robertson, Pioneer of Information Retrieval

In this episode of InfoFire, I speak with Dr. Stephen Robertson, a pioneering figure in the field of Information Retrieval (IR), who offers a reflective account of its conceptual and methodological evolution.

Translation

April 16, 2025 Jaihyun Park

Rethinking Reuse in Data Lifecycle in the Age of Large Language Models

In the world we are living in, a digital world, some data slips past our awareness, but very little data ever truly disappears. As we, information scientists, are concerned with reproducibility and responsibility of research, data lifecycle models have been developed to manage the complexity. To foster open, transparent, and collaborative science, data is often archived in a repository at the end of the project according to such data lifecycle models. This is often followed by the last step of the lifecycle models, data reuse. Traditionally, this model is cyclical, with reused data leading to new questions and fueling subsequent rounds of research.

InfoFire

March 10, 2025 Shalini Urs

LLMs, AI, and the Future of Research Evaluation: A Conversation with Mike Thelwall on Informetrics and Research Impact

In this episode of InfoFire, I sit down with Professor Mike Thelwall, a well accomplished scholar of Informetrics, to explore the intersections of Large Language Models (LLMs) and research evaluation. We delve into how LLMs are reshaping the landscape of research assessment, examining the promises they hold and the challenges they present in ensuring fair, meaningful, and context-aware evaluations.

Editorial

February 27, 2025 Chirag Shah

Here Come Agents

An agent is an autonomous entity or program that takes preferences, instructions, or other forms of inputs from a user to accomplish specific tasks on their behalf. And there is a huge hype around agents these days, thanks to advancements in various GenAI technologies. As big and small companies and individual developers continue investing heavily in development and deployment of agents, we are often missing some of the basic considerations, including what problems are we solving and how users, their tasks, and their contexts are incorporated in these developments.

Translation

January 27, 2025 Hsia-Ching Chang

Bringing AI and Blockchain Synergy into Cyber Threat Intelligence Cycle

Cyber Threat Intelligence (CTI) plays a pivotal role in governance, risk and compliance (GRC) as it enables risk assessment through the identification of threats, vulnerabilities, compliance requirements, and their consequent impacts. Efficient and secure information sharing matters in effective cyber threat intelligence.