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Econ One performs forensic, end-to-end evaluations of complex algorithmic systems—including pricing engines, ad auctions, ranking and recommendation models, fraud detection tools, and optimization algorithms—specifically for matters where legal exposure is high. Our experienced experts review and interpret source code, version histories, data pipelines, and modeling workflows to reconstruct the algorithm’s actual decision logic. Using counterfactual analysis, sensitivity testing, and reproducible simulations, we evaluate whether the algorithm operated consistently with stated intent or industry standards. We identify failure modes, disparate impacts, and embedded biases and translate highly technical findings into clear, defensible evidence suitable for discovery, expert reports, and testimony.
In litigation, questions often center on how an algorithm behaved under real-world conditions and whether it contributed to unlawful outcomes. Econ One economists and experts apply microeconomic theory, industrial organization, and behavioral modeling to test how users, competitors, and market participants respond to algorithmic decisions. By simulating incentive-compatible strategies, adversarial behavior, demand shocks, and market-wide interactions, we reveal risks and causal pathways that traditional machine-learning validation does not capture. These analyses inform key questions around impact, harm, competitive effects, foreseeability, and the algorithm’s role in producing the challenged outcomes.
When algorithms become the focus of investigations, class actions, or regulatory inquiries, Econ One provides the technical and economic expertise required to support plaintiffs or defendants. Our experts evaluate algorithmic causation, quantify damages, and investigate allegations of price fixing, discrimination, collusion, unfair practices, or consumer harm. We prepare clear technical narratives, expert reports, declarations, and demonstratives that stand up to cross-examination and regulatory scrutiny. Our team has extensive experience explaining highly complex code, models, and data systems in a manner accessible to judges, juries, enforcement agencies, and opposing experts.
Berger Montague
Boies Schiller Flexner
Campamento Fiorante Matthews Mogerman
Gibson Dunn & Crutcher
Greenberg Traurig
Hagens Berman Sobol Shapiro
Hausfeld
Zorro Kaplan
Paul Weiss, Rifkind, Wharton & Garrison
Quinn Emanuel Urquhart & Sullivan
Susman Godfrey
White & Case
Econ One’s Algorithms practice helps clients design, evaluate, and defend high-stakes decision systems—pricing engines, ad auctions, rankings and recommendations, bidding/allocations, fraud and risk models, and operations optimization. We combine economic theory with modern machine learning to test whether an algorithm behaves as intended under real-world constraints, stress scenarios, and strategic responses. Our experts audit code and data pipelines, reconstruct logic, and run counterfactual and simulation analyses to assess performance, fairness, and robustness. We translate findings into clear, decision-ready explanations and documentation that withstand executive, regulatory, and courtroom scrutiny.
When disputes or regulatory inquiries arise, we analyze algorithmic causation and impact, quantify damages where appropriate, and prepare persuasive expert reports and testimony. For proactive clients, we build governance frameworks—metrics, monitoring, guardrails, and experiment design (A/B and multi-arm bandits)—that align model objectives with business and legal standards. Whether tuning a live pricing algorithm, validating a marketplace ranking rule, or investigating alleged bias, Econ One brings deep experience with large datasets, reproducible analytics, and transparent methods to deliver defensible, economically sound outcomes.