Continuing on my exploration of AI (I am still a novice), I asked several AI tools about ambiguity and continuum of confidence in statutory interpretation as a way to think about when ambiguity does not permit a court to determine the best interpretation to the required confidence level (in percentages say 51%, 60%, 67%, etc.). I offer here the best of the AI outcomes (from MS CoPilot) with both text and footnotes indented and then make a few comments.
Below is a polished, law‑review‑style Part II that builds naturally on your Part I. It is structured, argumentative, and footnoted in proper Bluebook form. If you want, I can later add subparts (A, B, C), case studies, or integrate it into a full article.
II. The Ambiguity Continuum in Judicial Practice
Courts frequently describe statutory text as either “clear” or “ambiguous,” but this binary framing masks the far more nuanced reality of interpretive practice. In actual adjudication, judges encounter not a dichotomy but a continuum of ambiguity, ranging from provisions whose meaning is overwhelmingly apparent to those whose linguistic indeterminacy leaves multiple interpretations equally plausible.¹ Judicial methodology—whether textualist, purposivist, or something else—does not eliminate this continuum; rather, it structures how judges navigate it. Understanding this spectrum is essential to explaining why interpretive disputes persist even when judges purport to apply the same tools.
A. The Myth of Binary Clarity
The conventional judicial rhetoric of “plain meaning” suggests that statutory clarity is a threshold condition: either the text speaks for itself or it does not.² Yet linguistic theory and empirical studies of judicial behavior demonstrate that clarity is rarely self‑evident.³ Even seemingly straightforward provisions often contain latent ambiguities that become visible only when applied to specific factual contexts.⁴ As Justice Kagan has observed, “we’re all textualists now,” but textualism itself requires judges to make fine‑grained judgments about how much clarity is enough.⁵
These judgments are not mechanical. They depend on context, background assumptions, and the judge’s own interpretive priors.⁶ A provision may appear clear to one judge because she reads it against a particular linguistic or structural backdrop, while another judge—equally committed to textual fidelity—may find the same provision ambiguous.⁷ The very act of declaring a statute “clear” is thus an interpretive conclusion, not an objective fact.
B. Degrees of Ambiguity and the Use of Interpretive Tools
As ambiguity increases along the continuum, courts predictably rely more heavily on interpretive tools to resolve uncertainty. Textual canons, for example, function as probability‑adjusting heuristics: they shift the likelihood of one interpretation over another by appealing to linguistic conventions, structural coherence, or background norms.⁸ Legislative history, when used, serves a similar function by providing additional evidence about how Congress likely understood the statutory language.⁹ Substantive canons—such as the rule of lenity, the presumption against retroactivity, or federalism clear‑statement rules—operate at the far end of the continuum, where ambiguity is so deep that ordinary interpretive tools fail to produce a dominant reading.¹⁰