Auditing Recorded Predictive Lead Service-Line Classifications Against Physical Verification: A Statewide Study of New York
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Computer Science > Machine Learning
arXiv:2608.19922 (cs)
[Submitted on 20 Aug 2026]
Title:Auditing Recorded Predictive Lead Service-Line Classifications Against Physical Verification: A Statewide Study of New York
Authors:Muhammad Sarmad Sohail
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Abstract:Under the US Lead and Copper Rule Revisions, a utility may determine a service line's material with a predictive model instead of inspecting it. New York State publishes, per address, which method was used. Almost no address carries both a model classification and a physical verification, so the check is between populations within a utility rather than paired addresses. We screen all 153 New York localities that classified at least 100 addresses this way. Seventy-five (49%), covering 125,990 addresses or 57% of those screened, record one value. Zero variance alone is not misconduct: 68 of the 75 match their own verification or have too little to test. Seven are contradicted by their own crews, six beyond any sampling explanation. Five are boroughs of New York City, which file as one system; one is East Rochester, 550 km away. New York City is the largest case: a predictive model is the recorded basis for 43,215 addresses, and on all of them the recorded material is "Known Other". The city records "Unknown" on 121,779 addresses, 1,880 already excavated, and lead on 120,692. In the model bucket both counts are zero, and the 95% upper bound on the rate is 0.0085%. Across the rest of New York the same method records lead or the hedge "Unknown but could be lead" on 12.21% of 176,888 addresses, a comparison whose weaknesses we report. The model-cleared population is newer, median year built 1984 against 1930, and construction era accounts for about a third of the gap and not the rest: holding era fixed, records-based classification finds lead at 4.3-31.9%, physical verification at 1.5-14.5%, the model in no era. Six era-aware estimators place the expected lead lines among them at 1,150-1,450. Two findings need no comparison: 7,782 of these addresses are in pre-1940 buildings, and the archived 2025 snapshot shows the public-side determination was copied from a customer-side model output.
| Comments: | 14 pages, 3 figures, 3 tables. Analysis code and data provenance: this https URL |
| Subjects: | Machine Learning (cs.LG); Computers and Society (cs.CY) |
| ACM classes: | I.2.6; G.3; K.4.1 |
| Cite as: | arXiv:2608.19922 [cs.LG] |
| (or arXiv:2608.19922v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2608.19922
arXiv-issued DOI via DataCite (pending registration)
|
Submission history
From: Muhammad Sarmad Sohail [view email][v1] Thu, 20 Aug 2026 11:39:06 UTC (71 KB)
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