#Aiinresearch

A landmark study published in the Proceedings of the National Academy of Sciences warns that organised scientific fraud — from “paper mills” and brokers to hijacked journals and paid authorships — is expanding faster than legitimate scholarly output, posing a serious threat to the credibility of science worldwide and raising urgent questions for Thailand’s universities and research funders. The analysis finds networks of actors producing and laundering fraudulent papers at scale, with compromised subfields showing dramatically higher retraction rates and evidence that fake publications may be doubling at a pace that outstrips honest research growth ((PNAS study); (Northwestern news release); (New York Times summary)).

When academic careers depend on publication counts and research funding hinges on scholarly output, what happens when an entire underground economy emerges to sell fake science? A groundbreaking investigation published in the Proceedings of the National Academy of Sciences reveals a disturbing reality: organized scientific fraud networks are expanding faster than legitimate research, creating an existential crisis for academic integrity that directly threatens Thailand’s scientific credibility and public welfare.

The comprehensive analysis documents how sophisticated “paper mills” and criminal brokers have industrialized academic deception, manufacturing fraudulent research at unprecedented scale. These operations don’t just produce isolated fake studies—they systematically contaminate entire research fields through coordinated networks that researchers from Northwestern University describe as “essentially criminal organizations acting together to fake the process of science.” For Thailand’s rapidly expanding university sector, this represents both an immediate warning and a critical opportunity to protect the nation’s scientific reputation.

A growing underground economy in fake science threatens Thailand’s universities, public health, and international collaborations. A new assessment highlights how organized fraud networks are expanding faster than legitimate research, challenging the integrity of evidence-based policy and patient care in Thailand.

Researchers describe paper mills as sophisticated operations that deliver manufactured manuscripts, ghostwritten content, falsified images, and guaranteed publication placements. Fraud networks coordinate across journals and institutions, employing tactics such as editor manipulation and citation laundering. Data suggest retraction rates in affected areas are markedly higher, and fraudulent publications may be doubling every eighteen months, outpacing genuine scientific output. This dynamic reshapes how knowledge is built and trusted in Thai academia.

A new international study shows artificial intelligence is reshaping scientific publishing, with large language models increasingly assisting writing across disciplines. The study, highlighted by Nature Human Behaviour and summarized for the public, reveals that AI-generated text is influencing abstracts and introductions in many fields, including computer science. The shift has sparked excitement for faster writing and concerns about accuracy, originality, and access to AI tools for researchers in non-native English-speaking countries.

A breakthrough in reading the ancient, carbonized scrolls from Herculaneum marks a new era of speed and precision. Researchers are leveraging high-energy data capture and advanced imaging to unlock text buried for nearly two millennia. This progress signals a leap from painstaking, line-by-line reconstruction to broader discoveries of Roman thought, politics, science, and daily life at the end of antiquity. The work builds on non-destructive imaging techniques that peer inside rolled papyri without unrolling them, preserving fragile material for generations to come.

The race to read the lost words of Ancient Rome has entered a new era of speed and precision as researchers leverage powerful scientific tools to decipher carbonized papyrus scrolls buried for nearly two millennia. Recent advancements, highlighted by an article in The Economist (economist.com), reveal that the laborious process of recovering text from the “Herculaneum scrolls”—once a slow crawl—has shifted into a faster, more promising phase, thanks to cutting-edge particle accelerator technology.

In an event reverberating across the scientific community, the Massachusetts Institute of Technology (MIT) has publicly rescinded its institutional support for a recent artificial intelligence (AI) research paper. The move, reported by Retraction Watch, raises fundamental questions about the future of AI-authored academic articles and the ethical challenges facing research institutions worldwide.

The decision by MIT, a global powerhouse in science and technology innovation, has significant implications for the credibility and accountability of scientific literature. AI-generated content, increasingly prevalent in both drafting and data analysis duties, is under the microscope for issues relating to originality, transparency, and academic integrity. For Thai academic institutions, researchers, and the broader public, this case exemplifies the urgent need to establish clear policies and ethical guardrails as the adoption of AI tools accelerates throughout the research landscape.

A move with wide reverberations in science circles: MIT has publicly withdrawn its institutional support for a recent AI-driven research paper. The decision, reported by Retraction Watch, highlights ongoing questions about AI’s role in drafting and analyzing scientific work and the ethical responsibilities of research institutions worldwide. For Thai readers, the episode signals a crucial moment to establish clear policies on AI use in research and publication.

MIT’s reversal raises questions about how much credit AI should receive in scholarly work and whether automated systems can or should participate as contributors or co-authors. The cited paper reportedly used advanced language models to generate substantial portions of text and analysis, prompting concerns that automation could bypass essential peer review steps or recycle unverifiable content. A technology ethics expert noted that while AI can summarize or rephrase existing research, it cannot reliably assess the validity of scientific claims or ensure precise citations.