CONCEPT
The Peircean Diagnostic Protocol
The three-step practitioner’s test—derived from Peirce’s account of genuine abduction—for distinguishing authentic discovery in human-AI collaboration from its fluent, structurally convincing doubles: Is there a genuine surprising fact? Does the hypothesis respond to that specific surprise? Does it carry genuine explanatory risk?
Genuine
abductive inference requires three elements operating in sequence: a genuine surprising fact (an observation that violates a specific expectation), a responsive hypothesis (a proposed explanation that, if true, would render the surprising fact unsurprising), and a judgment of plausibility (an evaluation, grounded in the inquirer’s experience, that the hypothesis is worth testing). The Peircean diagnostic protocol applies these three requirements to outputs produced in human-AI collaboration, providing a practical method for identifying which contributions constitute genuine inquiry and which are
abductive doubles—outputs that exhibit the surface characteristics of abduction without its logical substance. The protocol has three steps. First: Is the initiating fact genuinely surprising, or is the “surprise” produced by the machine’s output rather than by an anomaly in the subject matter? Surprise at the machine (it produced something I didn’t expect) is meta-level and initiates a different inquiry (into the machine’s capabilities) rather than into the subject. Second: Does