Bad Alchemy: Turning Estimates Into Fraud
Client Alert | less than 1 min read | 02.08.06
Building on comments at the Nash & Cibinic Roundtable, David Bodenheimer challenges the oxymoronic trend of government agencies and qui tam whistleblowers to assert defective pricing or false claims based upon second-guessing poor estimates. In his article "'False' or 'Inaccurate' Estimates" published in the December 2005 Briefing Paper (http://www.crowell.com/pdf/Expertise/GovtContracts/BriefingPapers_Bodenheimer.pdf), he explains that estimating -- due to its inherently risky and predictive nature -- requires judgmental forecasts long recognized as appropriate by government pricing guidelines and not suitable for defective pricing and fraud suits complaining about bad estimates of future events.
Insights
Client Alert | 9 min read | 10.21.26
The life sciences sector is uniquely vulnerable to the inherent risks of AI-generated evidence in drug development and discovery. This client alert focuses on five core challenges: hallucinations, skewed predictions from unrepresentative training data, the opacity of AI reasoning, input sensitivity that undermines reproducibility, and adversarial manipulation of training data. To address these risks, companies should use experimental validation and human oversight as the common legal and regulatory safety net. This entails among other measures auditing AI outputs, characterizing training data, and structural oversight. Companies also should prepare for evolving frameworks and guidance from the U.S. Food and Drug Administration (FDA) and the European Union (EU) that address use of AI in drug discovery and development .
Client Alert | 2 min read | 10.21.26
Client Alert | 3 min read | 10.21.26
Private Investigations Act Series: Temporal, material and territorial scope
Client Alert | 7 min read | 10.21.26
