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Executive Order Prohibiting Bias Training? Ignore That. DoD Issues Class Deviation to Comply with Nationwide Ban on EO 13950 Provisions.

Client Alert | 1 min read | 01.08.21

On January 6, 2021, the DoD issued a class deviation, effective immediately, to implement the nationwide court order enjoining Sections 4 and 5 of Executive Order (EO) 13950, Combating Race and Sex Stereotyping, as well as guidance provided by the Office of Federal Contract Compliance Programs (OFCCP). EO 13950 prohibits federal agencies, contractors, and grant recipients from using workplace diversity and inclusion trainings to “promote race or sex stereotyping or scapegoating,” with Section 4 applying specifically to government contractors.

Under the class deviation, contracting officers are directed to “take all steps necessary to ensure the enjoined Section 4 of EO 13950 and its associated clause 252.222-7999, Combating Race and Sex Stereotyping (DEVIATION 2021-O0001) (NOV 2020), are not implemented or enforced and are inoperable until further notice.” Among other steps, contracting officers are instructed to (i) ensure that any new contracts do not contain the enjoined clause; (ii) modify existing contracts that include the enjoined clause to remove it and replace with the revised clause; (iii) not enforce any clauses contained in government contracts added pursuant to EO 13950; and (iv) not take any adverse action towards contractors or subcontractors on the basis of purported noncompliance with EO 13950, agency action implementing EO 13950, or any contract term inserted pursuant to EO 13950. To the extent contractors or subcontractors are presented with the enjoined clause, the injunction and class deviation provides a basis for refusing to incorporate the clause into any contract.

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Client Alert | 9 min read | 10.21.26

Artificial Intelligence in Life Sciences: Reliability of AI-Generated Evidence in Drug Discovery and Development

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 .  ...