The text examines the growing perception of a decline in the quality of contemporary scientific output, situating this phenomenon within the context of institutional pressures—such as the “publish or perish” culture—and the potentially inappropriate use of artificial intelligence. Available only in portuguese.
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Even standing on the shoulders of giants, science is taking a step backward
Diogenes’ lantern and the researcher’s self-examination: scientific integrity under pressure
Using the metaphor of Diogenes’ lantern, Ricardo Limongi and Marcio Pimenta discuss contemporary scientific practice. More than merely offering a critique, the image of the lantern invites a deeper reflection: how to turn the light inward, engaging in self-examination, ethical responsibility, and integrity while confronting a context that is often unfavorable to researchers in Brazil. … Read More →
Sycophancy in AI: the risk of complacency
Sycophancy is a behavior exhibited by artificial intelligence since it prioritizes agreeing with the user rather than the truthfulness of the facts. This tendency arises from training processes designed to maximize human satisfaction, which can validate serious errors in critical sectors such as healthcare. The behavior, described as a form of “digital flattery”, means that AI can validate errors, reinforce biases, or avoid necessary criticism in order to be pleasant or useful according to the user’s immediate perception. To mitigate these risks, strategies such as ethical fine-tuning, the design of systems that encourage dissent, and the use of prompts that are neutral with respect to users have been proposed.
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The professor’s dilemma in the age of AI: do we teach the prompt or the scientific process?
The question is not trivial. The adoption speed of generative AI tools in scientific research has generated a legitimate demand for technical training. Researchers want and need to know how to use these technologies. The problem arises when training is reduced to teaching shortcuts, without understanding the underlying processes that give researchers the ability to critically evaluate what the tool produces. … Read More →
The Ring of Gyges and AI in science: When invisibility challenges integrity
If AI can be used without being detected, how can scientific integrity be maintained? Based on the allegory of the Ring of Gyges, this post reflects on the limits of detection, the proliferation of guidelines, and the need to reposition the debate: from surveillance to researchers’ ethical training. … Read More →
The rise of ‘predatory’ publishing
Over the past two decades, scientific publishing has undergone a technological and economic transformation that has opened the door to more unorthodox models and, unfortunately, predatory practices. Predatory publishing refers to journals and publishers that charge authors (very high fees) to publish, claim peer review and indexing practices that do not exist or are fraudulent, and prioritize quick revenue over scientific quality. … Read More →
Who is the midwife and who is the parturient? The maieutic perspective for rethinking authorship and epistemic responsibility in the use of AI in scientific output
The Socratic maieutic perspective offers a philosophical framework for rethinking the use of AI in scientific output. Instead of an oracle that provides answers, AI can be a dialogical partner that helps researchers to make latent knowledge explicit and thus reposition the discussion about authorship: the researcher remains the responsible epistemic agent, while AI acts as an intellectual midwife. … Read More →
Scientific Data Sovereignty in the tension between global openness and local autonomy
Scientific data sovereignty is essential for a truly equitable open science. Between the ideal of global openness and the risk of data extractivism, we must build local infrastructures, participatory governance and collaboration models grounded in reciprocity and justice. … Read More →
Scientific Integrity in the Age of AI and the challenges of transparency: Fraud, manipulation, and the new transparency challenges
Artificial intelligence radically transforms the challenges of scientific integrity. From paper mills to automated fraud generation, we face a crisis that requires new forms of transparency, detection and governance to preserve trust in science—combining technology, institutional reforms and international cooperation. … Read More →
The dangers of using AI in peer review [Originally published in Hora Campias in December/2025]
Within my academic life, I am always on ‘both sides of the counter,’ as an author and as a reviewer. It is work of high responsibility because we have a commitment to the excellence of scientific information and to improving the article. Currently, authors may use genAI in preparing their manuscripts with certain caveats, but there are strict restrictions regarding its use in peer review. … Read More →
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