Facebook Twitter Linkedin
Sign in
Sign In

Artificial Intelligence

EditorialFeatured
Chirag Shah

Ship It, Then Apologize: We Can Do Better Than This for AI Advancements

Three days. That’s how long Fable 5 lasted before the U.S. government ordered Anthropic to switch it off worldwide, citing a vaguely described “jailbreak” and an export control directive broad enough to sweep in Anthropic’s own employees abroad. But the recall is only half the story: Anthropic had also moved fast, pushing its most capable model to the public within months of keeping its predecessor restricted to vetted partners. From Gemini’s image generator to Tay to GPT-4o’s sycophancy rollback, this is a pattern we keep repeating, and the people who pay for it are never the ones who decided to ship.

Read More
EducationTranslation
Angelica Lo Duca

From Content Generation to Content Validation: Why Human Judgment Still Matters in the AI Era

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.

Read More
FeaturedOriginal
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.

Read More
EducationOpinion
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.

Read More
Education
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.

Read More
Translation
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.

Read More