The MedicalXpress report on brain scans and AI for chronic pain rightly flags catch-22 validation failures, yet underplays how small-sample observational fMRI studies (typically n<50, no RCTs) in Nature Neuroscience (2023) and Nature Medicine (2024) embed selection bias by testing only low-stress volunteers. These works, funded partly by tech firms with opioid-prescribing algorithm stakes, fail to account for demographic skews where women and minorities—already overrepresented in chronic pain epidemiology per CDC observational data—face amplified false negatives. This echoes broader tech overpromising patterns seen in long COVID and fibromyalgia diagnostics, where early EEG/AI claims collapsed under real-world stress confounds without blinded controls. Synthesizing the 2006 Koch case with Wired's 2023 exposé on biased AI opioid tools reveals systemic distrust amplification: algorithms trained on curated datasets mislabel anxiety-driven activation as malingering. The IASP's 2024 stance against pain biomarkers underscores that subjective context, unmeasurable in scans, renders these tools diagnostically inert for invisible illnesses.