Turing
Turing is an AI-powered talent platform that vets software engineers through automated multi-stage technical assessments and uses machine-learned ranking to score, match, and place them with client companies.
§ 01 — Score breakdown
§ Score breakdown
Category scoring
Weighted contribution shown to the right of each bar.
- 01
Article 11 Technical Documentation
Weight 20%42
+8.4
- 02
Bias Audit Transparency
Weight 18%28
+5.0
- 03
FRIA Support
Weight 15%25
+3.8
- 04
Data Governance Disclosure
Weight 15%44
+6.6
- 05
Human Oversight Design
Weight 12%45
+5.4
- 06
Post-Market Monitoring
Weight 12%27
+3.2
- 07
Customer Documentation
Weight 8%48
+3.8
§ 02 — Strongest · weakest
Strongest category
Customer Documentation
Raw score 48 · contributes 3.8 to total.
Weakest category
FRIA Support
Raw score 25 · contributes 3.8 to total.
§ 03 — Cited evidence
Download diligence record→§ Evidence
Cited per category
Every score is backed by at least one cited piece of evidence.
§ 04 — Editorial notes
Company overview
Turing (Turing Enterprises, Inc.), founded in 2018 by Jonathan Siddharth and co-founders and headquartered in Palo Alto, California, is a venture-backed talent platform (Series E, ~$2.2B valuation) that maintains a global pool of several million developers and serves enterprise clients such as Dell, Disney, and Volvo. Its hiring product runs a four-stage, largely automated vetting funnel (experience survey, MCQ quiz, coding challenge, AI matching) and applies machine-learned models — gradient boosting, decision trees, and logistic regression — to predict a candidate's probability of success and rank them for client roles. The company has more recently expanded into AI-training and expert-evaluation ('AGI') services, but its developer vetting-and-matching engine remains the AI-hiring-relevant product.
Regulatory exposure
Turing's automated vetting and ranking substantially determines which candidates advance to employers, so it functions as an Automated Employment Decision Tool under NYC Local Law 144 and as a high-risk employment AI system under the EU AI Act; because Turing both builds the tool and supplies the vetted candidates, it straddles the developer and employment-agency roles, plausibly triggering LL 144 bias-audit and candidate-notice duties for NYC hiring and Art. 27 FRIA / transparency obligations for EU deployers. Despite this exposure, Turing publishes no independent bias audit, no FRIA or deployer guidance, no model/system card, and no AEDT-specific candidate notice; its GDPR-supplemented privacy policy and a generic automated-decision-making safeguard are the only governance-adjacent disclosures found.
Path to a higher score
Turing could raise its score by commissioning and publicly posting an independent LL 144 bias audit (named auditor, date, downloadable summary with impact ratios), releasing a model or system card plus an explainability statement for its vetting and ranking models, standing up a security/trust page evidencing SOC 2 and ISO 27001 (and ideally ISO 42001) for the platform itself rather than its consulting arm, publishing EU AI Act deployer and Art. 27 FRIA guidance alongside NYC candidate-notice templates, and adding a public status page, security-disclosure channel, and model-update changelog for post-market monitoring.
Conflicts of interest
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