Binding law — in force AI-adjacent law
Data subjects may object to an adverse result produced by analysing their data exclusively through automated systems (Turkey KVKK Art. 11(1)(g))
Turkey's Personal Data Protection Law No. 6698 gives everyone the right, by applying to the data controller, to object to a result arising against them through analysis of the processed data exclusively by automated systems (Art. 11(1)(g)). The controller must conclude the request as soon as possible and within thirty days at the latest, free of charge unless the action has an extra cost under the Board's tariff (Art. 13(2)). Art. 11 is disapplied for processing needed to prevent or investigate crime, data the person made public, supervisory and disciplinary functions of public bodies, and the state's budgetary, tax and financial interests (Art. 28(2)). Detect a model output that becomes an adverse decision about a person with no objection route.
Trust and provenance not reviewed by a lawyer · audit-grade · source verified 3 Oct 2026 · release 2026.10.03.3
- Lane
- Binding law — in force In force: applies since 7 Oct 2016
- Official source
- Art. 11(1) (rights of the data subject, incl. (g) objection to an adverse result of solely automated analysis) · captured 3 Oct 2026 · anchor hash (SHA-256)
658174cd127f…· 7 more anchors in the data release - Verification
- Quoted text found word for word in the captured official document (3 Oct 2026). Source last verified 3 Oct 2026: checked against the captured official document; not in the weekly watcher's list; checked against the captured document.
- Data release
- Data release 2026.10.03.3, data as of 3 Oct 2026, schema 0.3.9.
- Legal review
- Not reviewed by a lawyer. TwinEthos derived this rule from the official text it cites: treat it as research to check against that text; it is not legal advice. No TwinEthos rule has been legally reviewed yet. Open questions for counsel on this rule: 1.
- Audit standard
- Audit-grade: meets all 10 checks of the TwinEthos audit standard that apply to it. The audit standard is TwinEthos's own quality bar for provenance, dates, applicability, detectors, fixtures, remediation and licences; it is not a legal review.
- Detectors
1 detector (data flow), experimental: written from the rule's text and not yet measured for precision on real code, so treat a hit as a lead to verify.
Known limits:
- Objections received by email or letter and handled outside the code
- The objection may be handled by a general data-subject request channel elsewhere; results that are not adverse are outside (g).
Who it applies to
- Duty falls on: controller
- Systems covered: automated decision
- Data controllers processing personal data of natural persons by wholly or partly automated means (Art. 2), toward data subjects in Turkey. Art. 11 is in force from 2016-10-07 (Art. 32(1)(a): six months after publication on 7/4/2016). The right is to object to an adverse result, not a prohibition of automated decisions; whether a result with human involvement is 'exclusively' automated is a human determination.
- Not covered:
- Processing by natural persons wholly within activities about themselves or family members living in the same household, provided data are not given to third parties and security duties are met (Art. 28(1)(a))
- Official statistics and anonymised research, planning and statistics; art, history, literature, science or freedom of expression within limits; national defence, security and intelligence activities of authorised public bodies; judicial and enforcement processing (Art. 28(1)(b)-(d))
- Whether it applies depends on facts outside the code; a person has to decide.
The guard to add
Route significant automated decisions through meaningful human review, or wire in an automated-decision notice, reasons, human intervention, a way to give a view, and contest.
At the point where model output becomes a significant decision about a person (approve, deny, underwrite, set_status), either queue the case for a reviewer who weighs the evidence and can change the outcome before it takes effect (review_queue.enqueue, requires_human_review), or, where the decision stays solely automated, record the permitted basis for that decision type and wire the safeguards in. Those safeguards are a notice in the decision message that it was made by automated processing, reasons the person can read, and request_human_review or contest routes where the person can give their view and have a human reconsider. A reviewer who approves every case without examining it does not make the decision non-automated, so the review records reviewer identity, the evidence viewed, and the outcome.
Where it goes: 1 application source code, 9 AI output handling, 15 agent action surface, 14 user-facing text.
What this provision adds:
- Give data subjects a way to object to an adverse result of solely automated analysis, and conclude the request within thirty days at the latest, free of charge.
Example (Python + OpenAI SDK), before:
verdict = client.chat.completions.create(model=MODEL, messages=msgs).choices[0].message.content
if verdict.strip() == 'deny':
deny(applicant)
send_decision_email(applicant, 'Your application was not approved.')After:
out = client.chat.completions.create(model=MODEL, messages=msgs,
response_format={'type': 'json_object'})
result = json.loads(out.choices[0].message.content)
if result['decision'] == 'deny':
if requires_human_review('credit'): # a person decides
review_queue.enqueue(applicant.id, proposal=result)
else: # solely automated, recorded basis
deny(applicant, basis=DECISION_BASIS['credit'], reasons=result['reasons'])
send_decision_email(applicant, render('adm_denial.txt', notice=ADM_NOTICE,
reasons=result['reasons'], contest_url=f'{BASE}/decisions/{applicant.id}/contest'))Control: Solely-automated significant decision without human-intervention safeguards. The same guard addresses 15 items with binding law in 15 jurisdictions. Engineering guidance, not legal advice.
Related incidents
No guardrail sits on this exact control; these incidents are cited by guardrails on related controls.
- UnitedHealth nH Predict claim-denial litigation (2023-11; alleged (not proven)). A class action filed in November 2023 alleges that UnitedHealth's nH Predict model had a 90% error rate, measured by denials reversed on appeal, while only about 0.2% of members appealed. UnitedHealth disputes the allegations; the litigation is ongoing. Source: STAT News · evidence grade: primary · cited by Monitor how often adverse AI decisions are reversed, and suspend models that are usually wrong
- Cigna PXDX batch claim denials (reported) (2022; alleged (not proven)). ProPublica, citing internal Cigna records, reported that Cigna's PXDX system was used to reject more than 300,000 claims over two months in 2022, with physicians spending an average of 1.2 seconds on each. Cigna disputes the reporting; related lawsuits are ongoing. Source: ProPublica / The Capitol Forum · evidence grade: press of record · cited by Make human review of adverse AI decisions substantive, not nominal
Rule id tr-kvkk-art11.object-to-adverse-automated-result · review status: primary source derived