"AI is an attack from above on wages" ft. cognitive scientist Hagen Blix (www.bloodinthemachine.com)

Cognitive scientist Hagen Blix, in an interview about his book Why We Fear AI, argues that generative AI should be seen less as a neutral productivity booster and more as a coordinated mechanism for de-skilling work and depressing wages. He frames language models as the "industrial production of language": cheap, mass-produced outputs that undercut skilled labor (translators, paralegals, image readers) by flooding markets with lower‑quality but vastly cheaper substitutes. The result isn’t wholesale replacement so much as proletarianization—tasks become cheaper to perform, workers are forced into gig-like, low-pay remediation roles, and middle-quality goods and services erode, widening access to expensive, high-quality work and hollowing out the rest. For the AI/ML community this reframes priorities: technical advances interact with economic incentives and error-tolerance thresholds to determine social impact. Key implications include measuring downstream wage effects (not just accuracy and efficiency), recognizing that AI will disproportionately replace work where mistakes are tolerable, and that model-driven control systems can amplify managerial power. Engineers and researchers should design for augmentation, audit deployment contexts (public defense, healthcare, translation), build guardrails against race-to-the-bottom pricing, and engage with governance, labor organizations and policy to mitigate class-based harms. Blix’s core prescription is political: collective worker responses and regulatory frameworks will be essential to prevent AI from becoming a top-down attack on living standards.