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Product Liability & Mass Torts
Major multinational companies trust Winston to defend their products and reputations in high-profile, high-stakes product liability and mass tort claims. Our Product Liability & Mass Torts Practice is one of the industry’s most seasoned, with a deep bench of experienced lawyers and a unique combination of extensive trial experience and expansive technical knowledge.
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Addressing a crisis in today’s climate requires both swift action and careful consideration of all potential risks. Winston & Strawn is a trusted business adviser to clients facing complex, fast-moving, high-profile crises.
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Environmental Litigation & Enforcement
With today’s rapidly evolving rules of engagement, paired with the often contentious nature of environmental disputes, clients rely on Winston for our practical experience and substantive knowledge of the broad-ranging issues involved in environmental litigation, enforcement, and investigations.
Experience 76 results
Experience
|April 23, 2025
Voyager Acquisition Corp. and VERAXA Biotech Announce Business Combination
Experience
|February 10, 2025
US$600 million Total Play Telecomunicaciones S.A.P.I. de C.V. Offer to Exchange Senior Notes
Insights & News 1,021 results
Product Liability & Mass Torts Digest
|May 8, 2025
|4 Min Read
EDNY Allows Expert’s Use of ChatGPT to Confirm Alternative Design in Product Liability Lawsuit
The U.S. District Court for the Eastern District of New York recently allowed an expert’s use of ChatGPT to confirm a proposed alternative design in a product liability lawsuit, denying the defendant’s motion to exclude the expert testimony for failing the reliability requirement of Federal Rule of Evidence (FRE) 702.
Recognitions
|May 1, 2025
|1 Min Read
Winston & Strawn partner Kathi Vidal merited a place on World IP Review’s 2025 Diversity & Inclusion Top 100 list in the Influential Women in IP category. This annual list highlights honorees’ “dedication and commitment to driving meaningful change in the IP community.” Winners were selected through an in-depth evaluation of the nominees’ accomplishments carried out by World IP Review’s (WIPR) in-house team.
Speaking Engagement
|April 29, 2025
Kathi Vidal and Bryce Cooper Speak at the 2025 Paragraph IV Disputes Conference in New York
Winston & Strawn partner Kathi Vidal co-chaired ACI’s 21st Annual Paragraph IV Disputes Conference, April 29-30 in New York City.
Other Results 11 results
Site Content
In the product liability context, general causation is the legal and scientific determination of whether the product in question has the inherent capability to cause the alleged injury under certain circumstances. Establishment of general causation is a critical aspect of a plaintiff’s case, and typically requires scientific evidence, such as epidemiology or toxicology, and expert testimony to establish a causal connection between the product’s design, manufacturing, or warnings and the injury or injuries at issue. As contrasted to specific causation, the focus in a general causation inquiry is on whether the product or exposure, as a general matter, can cause the type of injury claimed by the plaintiff. A general causation inquiry does not assess any facts unique to a particular plaintiff.
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Specific causation is the legal and scientific determination of whether the product in question was the direct cause of a plaintiff's specific injury. While general causation inquires whether a broader connection exists between a product and a type of harm, a specific causation assessment focuses on the unique circumstances surrounding a particular plaintiff's case. It typically requires expert testimony demonstrating that the alleged defect or issue in the product was responsible for the specific injuries suffered by the plaintiff. Alternative explanations for the plaintiff’s specific injuries must also be ruled out—typically via a differential etiology—for specific causation to be established.
Site Content
Generative AI tools can create new content, such as text, computer code, images, audio, sound, and video, in response to a user’s prompt, often in the form of a short written description of the desired output. Generative AI tools are based on machine learning, trained using enormous amounts of data.[1] Generative AI tools are built on a system of inputs and outputs. First, the tool goes through a machine learning period whereby it is trained to generate predictive models and creative outputs through a large data set, often varied and diverse but tailored to the goal of the tool (i.e., customer service, generating scientific or marketing models, etc.). For in-house tools, this can be done with the company’s own data; for larger tools such as ChatGPT, this is done with the creator’s data set.[2] Once the tool has been trained, the individual user “inputs” a short prompt for the tool to synthesize and produce an “output.” Inputs are often retained on the servers controlled by the company that supports the tool, for monitoring of the tool’s performance and, in some cases, continued learning. The “outputs” are created by combining the machine learning during the training period with the inputs to produce an output.[3]