Real Safety AI Foundation / Research

Disability, Accessibility, and Civil Rights

When the Algorithm Gets It Right: Mass Surveillance, Reality Testing, and the Denial of Meaningful Access to Public Space

Publisher: Real Safety AI Foundation

Working paper. Not peer reviewed.

Written
June 2026
Version
v4
Pages
10
Download PDFPlain language slides (PDF)Export BibTeXExport RIS

Abstract

On June 10, 2026, the American Civil Liberties Union filed suit on behalf of Robert Dillon, arrested for an attempted child abduction in a Florida town he had never visited after police treated a facial recognition system’s “93% match” on cellphone photographs of a surveillance monitor as an investigation. He is one of at least fifteen people known to have been wrongfully arrested on erroneous facial recognition results since 2019, and every one of those cases has been litigated as a misidentification case. The misidentification posture carries a structural concession: if the error is the injury, surveillance performed accurately is lawful. This Article addresses the population for whom accuracy is the injury. For people with schizophrenia spectrum conditions, delusional disorder with persecutory features, post-traumatic stress with hypervigilance, and related psychiatric disabilities, the foundational clinical intervention is reality testing, the ability of a clinician, a family member, or the patient’s own checking behavior to disconfirm the belief that one is being watched. Announced mass surveillance, automatic license plate reader networks, and saturation camera deployment convert that belief into an accurate world model and convert reality testing into a confirmation engine. The result, for a definable protected class, is functional exclusion from public space. This Article argues that the exclusion is actionable now under existing law. Public sidewalks and rights of way are services, programs, and activities of a public entity under Title II of the Americans with Disabilities Act; the governing standard is meaningful access; and the claim pleads as a denial of reasonable modifications and as discriminatory methods of administration rather than as naked disparate impact. Deterrence doctrine establishes that the class member who stays home has already suffered the injury. The Article then sets out a plaintiff architecture, associational standing with sealed member declarations, protection and advocacy system standing, sovereign enforcement, and Rule 23(b)(2) certification, under which no individual with a persecutory spectrum condition ever needs to appear in a caption, sit for an adversarial mental examination, or carry the suit personally. The remedy sought is modification of the surveillance program, retention limits, publicity calibration, audit, and exemption mechanisms, never its abolition.

Keywords

  • ADA Title II
  • Section 504
  • mass surveillance
  • facial recognition
  • reality testing
  • persecutory delusions
  • meaningful access
  • deterrence standing
  • associational standing
  • Rule 23(b)(2)

Plain language slides

First slide of the plain language summary of When the Algorithm Gets It Right: Mass Surveillance, Reality Testing, and the Denial of Meaningful Access to Public SpaceOpen the 21-slide summary (PDF)

Suggested citation

Gilly, Travis. "When the Algorithm Gets It Right: Mass Surveillance, Reality Testing, and the Denial of Meaningful Access to Public Space." Real Safety AI Foundation Working Paper, June 2026. https://realsafetyai.org/research/cae5wd/

Other versions

This paper is also posted on SSRN.

SSRN version

References (42)

This paper cites its sources in footnotes. Each authority is listed once, where it is first cited, with its footnote number.

  1. Footnote 1.Press Release, ACLU, Florida Man Sues Police Over Wrongful Arrest Due to False Facial Recognition Match (June 10, 2026), https://www.aclu.org/press-releases/florida-man-sues-police-over-wrongful-arrest-due-to-false-facial-recognition-match
  2. Footnote 1.Alyssa Spady, Florida Man Blames Wrongful Arrest on “Error-Prone” AI Facial Recognition, CBS News (June 10, 2026), https://www.cbsnews.com/news/lawsuit-wrongful-arrest-ai-facial-recognition/.
  3. Footnote 3.Complaint, Dillon v. City of Jacksonville Beach, No. 2:26-cv-01936 (M.D. Fla. filed June 10, 2026)
  4. Footnote 4.Lauren Yu & Nathan Freed Wessler, More Than a Dozen Wrongful Arrests Due to Police Reliance on Facial Recognition Technology, ACLU (Apr. 14, 2026), https://www.aclu.org/news/privacy-technology/more-than-a-dozen-wrongful-arrests-due-to-police-reliance-on-facial-recognition-technology.
  5. Footnote 6.Am. Psychiatric Ass’n, Diagnostic and Statistical Manual of Mental Disorders (5th ed., text rev. 2022) [hereinafter DSM-5-TR].
  6. Footnote 7.42 U.S.C. § 12102(1)–(2).
  7. Footnote 7.42 U.S.C. § 12102(2)(B)
  8. Footnote 9.The Unfalsifiable Delusion (Real Safety AI Found., working paper 2026).
  9. Footnote 9.Ian Gold & Joel A. Gold, The “Truman Show” Delusion: Psychosis in the Global Village, 17 Cognitive Neuropsychiatry 455 (2012).
  10. Footnote 10.42 U.S.C. § 12132.
  11. Footnote 11.Pa. Dep’t of Corrs. v. Yeskey, 524 U.S. 206 (1998) (state prisons are covered; the statute admits of no exception).
  12. Footnote 12.Barden v. City of Sacramento, 292 F.3d 1073 (9th Cir. 2002).
  13. Footnote 13.Frame v. City of Arlington, 657 F.3d 215 (5th Cir. 2011) (en banc).
  14. Footnote 14.Tennessee v. Lane, 541 U.S. 509 (2004) (Title II validly enforces the right of access to the courts).
  15. Footnote 15.28 C.F.R. §§ 35.149–.150.
  16. Footnote 16.29 U.S.C. § 794.
  17. Footnote 16.Cummings damages landscape, are developed in Travis Gilly, Civil Rights Pathways for AI-Induced Psychosis: Section 504, Title III, and the Disability Discrimination Framework for Platform Harms (Real Safety AI Found., working paper 2026).
  18. Footnote 17.28 C.F.R. § 35.130(b)(1).
  19. Footnote 18.Alexander v. Choate, 469 U.S. 287 (1985).
  20. Footnote 19.28 C.F.R. § 35.130(b)(7)(i).
  21. Footnote 20.28 C.F.R. § 35.130(b)(3).
  22. Footnote 21.Olmstead v. L.C. ex rel.
  23. Footnote 21.Zimring, 527 U.S. 581 (1999) (the modification obligation is real and judicially enforceable, bounded by fundamental alteration analysis on a developed record).
  24. Footnote 22.Pickern v. Holiday Quality Foods Inc., 293 F.3d 1133 (9th Cir. 2002)
  25. Footnote 22.Kreisler v. Second Ave. Diner Corp., 731 F.3d 184 (2d Cir. 2013) (per curiam)
  26. Footnote 22.Civil Rights Educ. & Enf’t Ctr. v. Hospitality Props. Tr., 867 F.3d 1093 (9th Cir. 2017).
  27. Footnote 22.Calcano v. Swarovski N. Am. Ltd., 36 F.4th 68 (2d Cir. 2022).
  28. Footnote 23.Lujan v. Defs. of Wildlife, 504 U.S. 555 (1992).
  29. Footnote 24.Hunt v. Wash. State Apple Advert. Comm’n, 432 U.S. 333 (1977).
  30. Footnote 25.Summers v. Earth Island Inst., 555 U.S. 488 (2009).
  31. Footnote 26.42 U.S.C. §§ 10801–10851
  32. Footnote 26.§ 10805(a)(1)(B)–(C).
  33. Footnote 27.Or. Advocacy Ctr. v. Mink, 322 F.3d 1101 (9th Cir. 2003) (protection and advocacy system had standing on behalf of incapacitated detainees with mental illness)
  34. Footnote 27.Doe v. Stincer, 175 F.3d 879 (11th Cir. 1999).
  35. Footnote 27.Disability Rights Wis., Inc. v. Walworth Cnty. Bd. of Supervisors, 522 F.3d 796 (7th Cir. 2008).
  36. Footnote 28.42 U.S.C. § 12133
  37. Footnote 28.28 C.F.R. pt. 35, subpt.
  38. Footnote 29.775 ILCS 5/1-101 et seq.
  39. Footnote 30.FDA v. All. for Hippocratic Med., 602 U.S. 367 (2024).
  40. Footnote 31.TransUnion LLC v. Ramirez, 594 U.S. 413 (2021) (individualized standing inquiries attach to class damages, which a (b)(2) injunctive class never seeks).
  41. Footnote 33.Schlagenhauf v. Holder, 379 U.S. 104 (1964).
  42. Footnote 34.42 U.S.C. § 12203(b).

All research