The Ghost in the Machine: How Vocational Awe is Safeguarding a New Era of Predatory Publishing

The Virtue Signal as a Predator's Dinner Bell

Peer review isn’t dying; it’s being hollowed out and sold back to us as 'innovation.' For years, we have treated the academic librarian as the ultimate firewall against predatory publishing. But as Greyson Pasiak rightly identifies in his recent analysis of "AI Fatigue," we are witnessing a dangerous convergence: the weaponization of a librarian’s sense of duty, what Fobazi Ettarh termed "vocational awe," to mask the rapid degradation of scholarly integrity.

The industry logic suggests that adopting Generative AI is some kind of moral necessity for staying current. This is nonsense. In the real world, this obligation is a goldmine for predatory journals. These outfits aren't just sending clunky emails anymore. They use the tools we are bullied into using to build a sophisticated, fake veneer of legitimacy at a speed humans cannot track. By calling AI adoption a sacred duty, the system is gaslighting professionals into acting as a free quality control wing for a mess of synthetic garbage.

The Inversion of Authority

In this high-stakes environment, the "follow the money" trail leads directly to the APC (Article Processing Charge) mills. These entities thrive on the fatigue Pasiak describes. When librarians and researchers are too exhausted to perform the deep forensic work required to vet a journal's editorial board or its 'AI-assisted' peer review claims, the predators win. They bank on our burnout.

Pasiak, writing for the Rochester Institute of Technology, notes that expecting librarians to teach "safe" AI use often goes beyond their actual jobs. This creates a gap. Speed becomes the only metric, and scrutiny dies. This is where predators set up shop, promising the very speed that legitimate journals claim AI will provide. It is a trap.

The 'Hallucinated' Citation Economy

We are entering an era of "circular fabrication." Predatory journals are now publishing AI-generated papers that cite other AI-generated papers (often citing papers that don't even exist, yet look statistically significant). Librarians are being tasked with 'finding' these hallucinated works, wasting precious cognitive labor on ghosts.

This is a failure of the entire system, not just a technical bug. When we use high minded language to demand that library staff handle this digital flood without help, we are basically helping the predators. We are asking humans to be a filter for a firehose that was built specifically to break those filters. It is an impossible request.

Structural Defiance: From Awe to Accountability

If we want to save scholarly publishing, we must stop romanticizing the struggle. To combat the rise of AI-driven predatory practices, we need a radical shift in the architecture of trust.

Mandatory Non-AI Provenance: We must demand that journals provide transparent, verifiable logs of human intellectual labor. If a journal cannot prove its peer reviewers are sentient beings with verifiable expertise, it should be auto-flagged as predatory. Passive 'AI-literacy' isn't enough; we need aggressive AI-exclusion for critical oversight roles.

The 'Slow Science' Rebate: Institutions must stop rewarding the volume of output. Predatory publishing exists because our metrics demand 'more.' We need to fund 'Slow Science' roles, librarians and researchers whose sole job is to reject and deconstruct low-quality, AI-fatigued submissions without the pressure of institutional 'vocational' KPIs.

We must stop treating AI like a weather pattern we just have to live with. It is a product. The exhaustion it creates is not an accident; it is how the system wears us down to turn truth into a commodity. We should be skeptical, not in awe.