Article
Jul 20, 2018

Who Got the Ball Rolling? Jurors and Causal Chains

This article examines how jurors assign blame in causal chains, often favoring proximal causes over more distant ones.

When Donald Trump was elected president in 2016, many Americans asked—how did this happen?  Some attributed it to James Comey’s decision to re-open the investigation into Hillary Clinton’s e-mails just days earlier, while others looked farther back in time to Trump’s success on the Apprentice.  This investigation into what led Trump to become President exemplifies the human inclination to create causal chains when trying to understand events.  And we do this all the time, whether we’re trying to understand public events like the space shuttle disaster or the 9/11 attack, or private events like a break-up or divorce.

Jurors are sometimes asked to evaluate parties at different points in a causal chain when determining liability and/or damages.  For example, most US states have “dram shop” laws that make businesses potentially liable for injuries/damages caused by intoxicated customers to whom they served or sold alcohol.  Research with mock jurors, though, suggests that most jurors are reluctant to hold these businesses liable because they are distal, or farther removed from the event being explained (the accident).[1]  People are more inclined to attribute responsibility to proximal causes – the ones closest to the event – here, the drunk driver.  This has proved true even when jurors are told that the customer was obviously intoxicated when served.  This criterion means the retailer should have known that “more alcohol would cause danger to himself or others,”[2] which is what triggers liability for the dram shop owner.  Mock jurors’ deflection of blame away from these distal causes flies in the face of the very intent of “Dram shop” laws.  This tendency is consistent with the blame attribution model, in which the presence of additional, intervening causes would diffuse responsibility away from distal causes.[3]   

According to the social functionalist model, we look for causes that give us control over future consequences of similar events.[4]  Typically, this leads us to focus blame on irresponsible or malicious human actions rather than on causes that feel outside of social control.  In fact, research suggests that people prefer causes that are socially controllable through sanctions and preventive actions.[5]   In the drunk driving case, the alcohol retailer is not only temporally removed from the accident but is also less psychologically useful as an explanation: He is less amenable to the societal need to control and prevent harmful events.

Jurors analyze causal chains in many types of cases:  product liability, toxic torts, and mass torts, for example.  Knowing the human inclination to blame proximal causes, attorneys should consider:  How much time passed between the actions of the distal cause and the outcome (harm)?  Would punishment or sanctions for the distal cause prevent similar future harm?  Was the harm foreseeable?  This last point is important because outcomes that are foreseeable are more likely to be perceived as controllable, which may make distal causes perceived as more blameworthy.[6]

I recently heard focus group members debating the liability of parties farther back in a causal chain, in a case that involved devastating harm to a community.  Defense advocates who argued against holding distal causes liable analogized: “You don’t hold car manufacturers responsible for accidents caused by dangerous driving” and “you don’t hold liquor manufacturers responsible for alcoholism.”

The takeaway?  In cases involving a causal chain (or the possibility of jurors creating one themselves), remember: All causes are not created equal.


[1] Gordon, N., & Evelo, A. (2018). Lay individuals differ from legal standards of blame in cases of third party liability. Manuscript in preparation.

[2] dui.findlaw.com/dui-laws-resources-dram-shop-laws.

[3] Shaver, K. G. (1985). The attribution of blame: Causality, responsibility, and blameworthiness. New York: Springer-Verlag.

[4] Tetlock, P. E. (2002). Social functionalist frameworks for judgment and choice: Intuitive politicians, theologians

and prosecutors. Psychological Review, 109, 451–471.

[5] McClure, J., Hilton, D. J., & Sutton, R. M. (2007). Judgments of voluntary and physical causes in causal chains: Probabilistic and social functionalist criteria for attributions. European journal of social psychology37, 879-901.

[6] Lagnado, D. A., & Channon, S. (2008). Judgments of cause and blame: The effects of intentionality and foreseeability. Cognition108, 754-770.

 
Stay Informed
Stay up to date on our latest news and insights.
Subscribe
Read More
blue and black texture wavey
Article
Jun 30, 2026
Investigations at the ITC: Navigating Speed and Complexity in a High-Stakes Forum

Success at the ITC depends not just on the legal merits, but on how effectively parties can organize technical complexity, align expert-driven narratives, and present a clear, disciplined case under significant time pressure. Let’s explore how venue nuances and current industry trends are impacting proceedings seen before the Commission.

Read Now
overhead view of cars speeding on road like blurs of light
Article
Jun 18, 2026
Who Gets the Blame? What Autonomous Vehicle Research Reveals About AI Litigation

Litigation surrounding autonomous vehicle technology raises a question that courts will increasingly confront as AI becomes more embedded in everyday life: when humans and machines share control, who gets the blame when something goes wrong?

Read Now
blue and black background with grain and texture
Article
Jun 9, 2026
What ITC Practitioners Should Know: Key Judicial Insights from ACI’s ITC Conference

To better understand evolving trends at the venue and hear directly from those involved in ITC litigation, DOAR proudly sponsored and attended the American Conference Institute’s annual ITC Litigation and Enforcement Conference.

Read Now
white and black triangle texture on washed out background
Article
Apr 20, 2026
AI Litigation Trends: Rapid Growth and Emerging Patterns

As generative AI technologies move from early adoption to widespread commercial use, litigation activity is accelerating in parallel. Our analysis of 168 district court cases highlights a sharp rise in filings, a high concentration among a small group of defendants, and early signals of how this legal landscape may evolve.

Read Now
black dark background with orange lights almost looking like wires
Article
Feb 3, 2026
Wireless Litigation Trends at a Glance: Where the Risk is Shifting Across the Ecosystem

Using litigation data across carriers, infrastructure providers, device manufacturers, and technology suppliers, we highlight where different types of disputes tend to arise and why those patterns vary by segment.

Read Now
light leaks with orange and blue light flares in lense
In the News
Jan 28, 2026
Using Graphics in Insurance Litigation: Turning Volume into Clarity

For litigators, especially in insurance disputes with their endless exhibits and dense policy language, the challenge is not whether to use graphics but how to use them effectively, credibly, and strategically to make the case intelligible to the trier of fact.

Read Now
celllphone image with blue light leak in top blocking out screen, insinuating social media issues with jurors
Article
Jan 9, 2026
Social Media Research on Prospective Jurors: Navigating Evolving Ethical Boundaries

As technology transforms what is possible in juror research, the gap between available tools and permissible practices continues to widen, particularly with respect to social media.

Read Now
lines of light making forward movement
Article
Dec 12, 2025
Wireless Litigation Trends at a Glance: Case Trends and Top Parties

Using aggregated filing data from the wireless dataset, we provide a data-driven view of where litigation is concentrated, which parties are most active, and how the structure of the wireless market shapes the legal landscape.

Read Now