AI and Authors’ Rights: Can Innovation and Fairness Coexist?
Artificial intelligence is transforming the way we create, publish, translate, and consume content. Yet one of the most important questions remains unresolved: Who should benefit when AI systems are trained on the work of others? As part of my current editorial work with LITA (the Slovak Literary and Information Centre), I have been following ongoing […]
The Sydney AI Controversy Isn’t About Cheating. It’s About Disclosure.
Darren Chastney | 3 June 2026 A recent controversy in Australia has sparked intense debate after a university academic reportedly used AI to help draft a newspaper opinion piece that warned students against relying on AI in their academic work. Predictably, accusations of hypocrisy followed. But I think many people are focusing on the wrong […]
If Even Literary Prize Judges Can’t Tell, What Happens Next?
Darren Chastney | 28 May 2026 A major literary controversy last week has raised an uncomfortable question for publishers, prize judges, and readers alike: Can we still reliably tell the difference between human writing and AI-generated fiction? The debate emerged after concerns were raised over one of the regional winners of the 2026 Commonwealth Short […]
“Book Club” Scam Targets Content Producers
Darren Chastney May 25, 2026 A few days ago, I received an email from someone claiming to run a literary organisation called “vermontbookclub”. At first glance, it looked entirely legitimate. The sender referenced my recent posts about AI guardrails, translation ethics, and the challenges of preserving meaning between languages. They mentioned my work in Bratislava, […]
NOK Computer – When AI Goes Rogue
When AI Accidentally Switches Languages: A Small Error with Big Implications During a recent writing task, an unusual thing happened. In the middle of an English sentence, the Arabic word “موجود” suddenly appeared: “A similarity score is the percentage of text in a document that matches content already موجود in databases…” The intended word was […]
The Uncanny Valley of Academic Similarity Scores
What Is a “Similarity Score” — and Why Should Researchers Care? Many researchers are familiar with plagiarism detection software such as Turnitin or iThenticate, but fewer fully understand what a similarity score actually means. A similarity score is the percentage of text in a document that matches content already found in databases, journals, websites, student […]
When AI Runs the Risk of Reputational Damage
The rapid adoption of generative AI in higher education has introduced a new and evolving risk: the intersection of AI-assisted writing and increasingly sophisticated detection systems. While AI tools are widely used to support drafting and editing, universities are simultaneously expanding the use of AI-detection technologies to identify undeclared machine-generated content. Recent reporting indicates thousands […]
What Gets Lost Between Languages (Even When the English Is Near Perfect)
In multilingual research environments, “good English” is often seen as the end goal. If a paper reads fluently, clearly, and without obvious errors, it is usually considered ready. But fluency can be deceptive. Because what is lost in translation is not always visible in the final text. A sentence may be: while still failing to […]
What Reviewers Really Notice (Even If They Don’t Say It)
When a paper is reviewed, feedback usually focuses on the big things: methodology, argumentation, contribution. But smaller language issues often play a quieter role in how that work is perceived. Not necessarily consciously—and not always explicitly stated. A sentence that is slightly ambiguous.A claim that feels just a little too strong.An explanation that requires a […]
AI summaries – succinct but misleading?
A recent BBC News article highlighted a shift in how information is discovered online. Instead of lists of links, users are increasingly presented with AI-generated answers—summaries that extract and synthesise content from multiple sources. For researchers and academic institutions, this raises an important question: What happens when your work is no longer read in full—but […]