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In a past blog post, we predicted that data is arguably the products liability issue of the future. And we also explored some ways in which data can be used as a sword and a shield in products liability cases.

Also, we have written before about the data gathering and management practical problems that currently limit the use of data in products liability cases due to high costs and other logistical complications. But those are not the only issues. Despite the potential benefits of using data in product liability cases, there are also several limitations. In this blog post, we will explore some of these limitations.

Data quality: One of the biggest limitations to using data in product liability cases is the quality of the data itself. Data can be unreliable or incomplete, which can make it difficult to draw accurate conclusions about what went wrong with a product. Especially in the case of data that is generated throughout the lifecycle of a product, and in part depends on consistent actions taken by a consumer, the quality of the data can be inconsistently whole. In addition, data can be manipulated or intentionally withheld, which can further undermine its reliability. Even when these issues are not clearly present, expert witnesses employed for the purpose of casting doubt on an opposing litigant’s case can interpret the data in ways that may possibly read in issues that are not as big as they may seem.

Data interpretation: Even when data is reliable, it can be difficult to interpret. Data analyst expert witnesses hired for the purpose of litigation may not have a full understanding of the product or the context in which it was used, which can decrease the quality of their conclusions, or lead to increased fodder for cross examination. In addition, data may be open to interpretation, and different analysts may draw different conclusions from the same data, which may set the stage for a battle of the experts.

Privacy concerns: In order to collect data, products sometimes collect personal information about their users. This can raise privacy concerns, particularly if the data is being collected without the user’s knowledge. While companies can control this this to some extent, dealing with data privacy concerns is extremely costly for companies. And for a plaintiff’s lawyer who is struggling to put on a compelling presentation of evidence in a products case, it could be tempting to reptile and pivot the products case into an indictment of a company based on alleged data privacy issues. Such conduct could be curtailed through motions in limine practice, but this is yet one problematic way in which a plaintiff’s lawyer may use data to their advantage, even in subtle and initially unseen ways. As a result, there may be legal and ethical issues around the use of data in product liability cases.

Cost: Collecting and analyzing data can be expensive, particularly if the product in question is complex and requires a large amount of data to be collected. This cost can be a significant barrier to using data in product liability cases, particularly for smaller companies or individuals who may not have the resources to invest in data collection and analysis.

Expertise: The use of data in products cases requires a high level of expertise in data collection, analysis, and interpretation. This expertise may not be readily available, particularly in smaller or less complex cases. As a result, the use of data may be limited to only the most complex and high-profile cases. Although as we have written in the past, this need for expertise will be curtailed by the continued development of machine learning and artificial intelligence.

Lack of Familiarity with Data: A Judge’s experience and level of comfort with data can influence their rulings on motions such as motions in limine, or Duabert motions seeking to disqualify experts who purport to be qualified to usher in all sorts of data based testimony and conclusions. Similarly, when presenting and explaining data to juries, some math and data challenged people may be lost or may discount the objective information found in data.

In conclusion, while the use of data in product liability cases can provide valuable insights into how products are used and how they are allegedly defective, there are also several limitations to data use. Data is an increasingly essential aspect of products liability lawsuits, particularly as AI and automation continue to shape the product landscape. In the event of a products lawsuit that will deal in product data, it is important to make a litigation plan upfront that addresses and mitigates the issues identified above.