28 lines
1.7 KiB
TeX
28 lines
1.7 KiB
TeX
\section{Conclusion and Future Work}
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\label{sec:conclusion}
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We have presented a verified quantitative survey of AI/agent-related IETF
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Internet-Drafts, based on a curated corpus of $524$ documents spanning January
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2024 to May 2026. The corpus exhibits a sharp recent surge---from $3.7$ to
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$38.8$ drafts per month, peaking at $106$ in March 2026---and is dominated by
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individual submissions ($87\%$ not adopted by any working group) with
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substantial semantic redundancy ($32.4\%$ of drafts having a near-duplicate),
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the signature of a young, pre-standardization design space. Crucially, we
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treated the LLM-assisted labels themselves as objects of measurement: a
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two-model re-rating shows that categorical assignment is substantially
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reproducible (Cohen's $\kappa \approx 0.65$), while ordinal quality scores are
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not ($\kappa_w = 0.13$--$0.21$ for the least stable dimensions), so we report
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the category landscape and exclude the quality scores.
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Several directions extend this work. \emph{Full-text classification} would
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replace the abstract-only pipeline and test whether categories shift when the
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classifier reads the complete document. \emph{Longitudinal re-runs} on later
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snapshots would turn the single-snapshot picture into a moving record of how the
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surge evolves and whether redundancy consolidates over time. \emph{Cross-SDO
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extension} to ISO, ITU, ETSI, NIST, and W3C---contingent on reconciling their
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heterogeneous metadata---would situate the IETF activity within the broader
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standards landscape. Finally, \emph{tracking working-group adoption} of
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individual drafts would reveal which of the many competing proposals clear the
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bar from individual submission to adopted work, giving an empirical handle on
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how the pre-standardization field resolves.
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