Technology: Product Misrepresentation, Product Liability, Data Privacy, and Data Breach

Much of today’s data is generated by the everyday activities of consumers as they communicate, shop, travel, work, or engage in routine interactions with other consumers, businesses, and government entities through digital systems, platforms, and social media.

Given this massive accumulation of information, the opportunities for disputes over the use or misuse of consumer information will concurrently increase. Indeed, litigation relating to allegations that businesses obtained and/or used private data without consumers’ prior consent or that businesses did not sufficiently protect private data has become common.

Our staff and experts have expertise relevant to these matters, including:

• An in-depth understanding of the academic literature and proprietary data and research on data privacy expectations and the potential negative outcomes resulting from data breach incidents.
• Experience addressing a wide range of damages methodologies commonly used by plaintiffs in data privacy and data breach litigation, including conjoint analysis, contingent valuation, and regression analysis.

Advancements in artificial intelligence (AI) have yielded new products capable of performing tasks involving human-like decision-making. These include many popular products such as medical monitoring devices, digital voice assistants, or intelligent HVAC systems. Emerging with these technologies are a number of issues related to the risks presented by AI-driven decision-making.

• Are consumers aware of the risks associated with the predictive algorithms imbedded in their products?
• Are consumers able to anticipate problems and understand the limits to what these products can actually do?

Litigation surrounding liability for AI-driven products requires an expertise in analyzing consumer expectations and behaviors. We have experience applying advanced data analytics, statistical techniques, and survey design to address questions of causation, impact, and damages in these matters.

Data analytics has enabled businesses to target consumers based on their personal or device data and connect them to goods or services. Such use of targeted online and in-app advertising has raised a number of questions.

• How do advertising platforms harness user-provided data to target individuals?
• Is the accuracy of such targeting practices well understood, both by advertisers and by consumers?
• How effective is targeted advertising compared to traditional marketing alternatives?

Experts who understand digital advertising strategies and who are well versed in identifying the factors that affect advertisers’ decisions are critical to answering these questions in the context of product liability litigation.

The internet has revolutionized the way people shop. Online reviews, social media, and other electronic word-of-mouth have become increasingly influential in consumers’ evaluations of products. These digital footprints are a promising source of real-world data. Proficiency in text mining techniques makes it possible to harness the vast amount of online product reviews and examine the relative importance of different product features in consumers’ decision-making process.

While the use of online reviews in litigation is still in its early stages, our expertise in data analytics offers new avenues to leverage consumer-generated data to address issues that arise in product misrepresentation and product liability matters. Our experience includes:

• Applying advanced machine learning computing methods such as Natural Language Processing (NLP) and sentiment analysis, and using these techniques to assess changes in consumers’ online evaluations of products over time.
• Using survey methods to address issues relating to online search and purchase decision-making.