The Subversion of Causation into Normative Feelings
The late Professor Margaret Berger argued for the abandonment of general causation, or cause-in-fact, as an element of tort claims under the law.[1] Her antipathy to the requirement of showing causation ultimately involved her deprecating efforts to inject due scientific care in gatekeeping of causation opinions. After a long, distinguished career as a law professor, Berger died in November 2010. Her animus against causation and Rule 702, however, was so strong that her chapter in the third edition of the Reference Manual on Scientific Evidence, which came out almost one year after her death, she embraced the First Circuit’s notorious anti-Daubert decision in Milward, which also post-dated her passing.[2]
Despite this posthumous writing and publication by Professor Berger, there have been no further instances of Zombie scholarship or ghost authorship. Nonetheless, the assault on causation has been picked up by Professor Alexandra D. Lahav, of the University of Connecticut School of Law, in a recent essay posted online.[3] Lahav’s essay is an extension of her work, “The Knowledge Remedy,” published last year.[4]
This second essay, entitled “Chancy Causation in Tort Law,” is the plaintiffs’ brief against counterfactual causation, which Lahav acknowledges is the dominant test for factual causation.[5] Lahav begins with a reasonable, reasonably understandable distinction between deterministic (necessary and sufficient) and probabilistic (or chancy in her parlance) causation.
The putative victim of a toxic exposure (such as glyphosate and Non-Hodgkin’s lymphoma) cannot show that his exposure was a necessary and sufficient determinant of his developing NHL. Not everyone similarly exposed develops NHL; and not everyone with NHL has been exposed to glyphosate. In Lahav’s terminology, specific causation in such a case is “chancy.” Lahav asserts, but never proves, that the putative victim “could never prove that he would not have developed cancer if he had not been exposed to that herbicide.”[6]
Lahav’s example presents an example of a causal claim, which involves both general and specific causation, which is easily distinguishable from someone who claims his death was caused by being run over by a high-speed train. Despite this difference, Lahav never marshals any evidence to show why the putative glyphosate victim cannot show a probability that his case is causally related by adverting to the magnitude of the relative risk created by the prior exposure.
Repeatedly, Lahav asserts that when causation is chancy – probabilistic – it can never be shown by counterfactual causal reasoning, which she claims “assumes deterministic causation.” And she further asserts that because probabilistic causation cannot fit the counterfactual model, it can never “meet the law’s demand for a binary determination of cause.”[7]
Contrary to these ipse dixits, probabilistic causation can, at both the general and specific, or individual, levels be described in terms of counterfactuals. The modification requires us, of course, to address the baseline situation as a rate or frequency of events, and the post-exposure world as one with a modified rate or frequency. The exposure is the cause of the change in event rates. Modern physics addresses whether we must be content with probability statements, rather than precise deterministic “billiard ball” physics, which is so useful in a game of snooker, but less so in describing quarks. In the first half of the 20th century, the biological sciences learned with some difficulty that it must embrace probabilistic models, in genetic science, as well as in epidemiology. Many biological causation models are completely stated in terms of probabilities that are modified by specified conditions.
When Lahav gets to providing an example of where chancy causation fails in reasoning about individual causation, she gives a meaningless hypothetical of a woman, Mary, who is a smoker who develops lung cancer. To remove any semblance to real world cases, Lahav postulates that Mary had a 20% increased risk of lung cancer from smoking (a relative risk of 1.2). Thus, Lahav suggests that:
“[i]f Mary is a smoker and develops lung cancer, even after she has developed lung cancer it would still be the case that the cause of her cancer could only be described as a likelihood of 20 percent greater than what it would have been otherwise. Her doctor would not be able to say to her ‘Mary, if you had not smoked, you would not have developed this cancer’ because she might have developed it in any event.”
A more pertinent, less counterfactual hypothetical, is that Mary had a 2,000% increase in risk from her tobacco smoking. This corresponds to the relative risks in the range of 20, seen in many, if not most, epidemiologic studies of smoking and lung cancer. And there is an individual probability of causation that would be well over 0.9, for such a risk.
To be sure, there are critics of using the probability of causation because it assumes that the risk is distributed stochastically, which may not be correct. Of course, claimants are free to try to show that more of the risk fell on them for some reason, but of course, this requires evidence!
Lahav attempts to answer this point, but her argument runs off its rails. She notes that:
“[i]f there is an 80% chance that a given smoker’s cancer is caused by smoking, and Mary smoked, some might like to say that she has met her burden of proof.
This approach confuses the strength of the evidence with its content. Assume that it is more likely than not, based on recognized scientific methodology, that for 80% of smokers who contract lung cancer their cancer is attributable to smoking. That fact does not answer the question of whether we ought to infer that Mary’s cancer was caused by smoking. I use the word ought advisedly here. Suppose Mary and the cigarette company stipulate that 80% of people like Mary will contract lung cancer, the burden of proof has been met. The strength of the evidence is established. The next question regards the legal permissibility of an inference that bridges the gap between the run of cases and Mary. The burden of proof cannot dictate the answer. It is a normative question of whether to impose liability on the cigarette company for Mary’s harm.”[8]
Lahav is correct that an 80% probability of causation might be based upon very flimsy evidence, and so that probability alone cannot establish that the plaintiff has a “submissible” case. If the 80% probability of causation is stipulated, and not subject to challenge, then Lahav’s claim is remarkable and contrary to most of the scholarship that has followed the infamous Blue Bus hypothetical. Indeed, she is making the very argument that tobacco companies made in opposition to the use of epidemiologic evidence in tobacco cases, in the 1950s and 1960s.
Lahav advances a perverse skepticism that any inferences about individuals can be drawn from information about rates or frequencies in groups of similar individuals. Yes, there may always be some debate about what is “similar,” but successive studies may well draw the net tighter around what is the appropriate class. Lahav’s skepticism and her outright denialism, is common among some in the legal academy, but it ignores that group to individual inferences are drawn in epidemiology in multiple contexts. Regressions for disease prediction are based upon individual data within groups, and the regression equations are then applied to future individuals to help predict those individuals’ probability of future disease (such as heart attack or breast cancer), or their probability of cancer-free survival after a specific therapy. Group to individual inferences are, of course, also the basis for prescribing decisions in clinical medicine. These are not normative inferences; they are based upon evidence-based causal thinking.
Lahav suggests that the metaphor of a “link” between exposure and outcome implies “something is determined and knowable, which is not possible in chancy causation cases.”[9] Not only is the link metaphor used all the time by sloppy journalists and some scientists, but when they use it, they mostly use it in the context of what Lahav would characterize as “chancy causation.” Even when speaking more carefully, and eschewing the link metaphor, scientists speak of probabilistic causation as something that is real, based upon evidence and valid inferences, not normative judgments or emotive reactions.
The probabilistic nature of the probability of causation does not affect its epistemic status.
The law does not assume that binary deterministic causality, as Lahav describes, is required to apply “but for” or counterfactual analysis. Juries are instructed to determine whether the party with the burden of proof has prevailed on each element of the claim, by a preponderance of the evidence. This civil jury instruction is almost always explained in terms of a posterior probability greater than 0.5, whether the claimed tort is a car crash or a case of Non-Hodgkin’s lymphoma.
Elsewhere, Lahav struggles with the concept of probability. Her essay suggests that
“[p]robability follows certain rules, or tendencies, but these regular laws do not abolish chance. There is a chance that the exposure caused his cancer, and a chance that it did not.”[10]
The use of chance here, in contradistinction to probability, is so idiosyncratic, and unexplained, that it is impossible to know what is meant.
Manufactured Doubt
Lahav’s essay twice touches upon a strawperson argument that stretches to claim that “manufacturing doubt” does not undermine her arguments about the nature of chancy causation. To Lahav, the likes of David Michaels have “demonstrated” that manufactured uncertainty is a genuine problem, but not one that affects her main claims. Nevertheless, Lahav remarkably sees no problem with manufactured certainty in the advocacy science of many authors.[11]
Lahav swallows the Michaels’ line, lure and all, and goes so far as to describe Rule 702 challenges to causal claims as having the “negative effect” of producing “incentives to sow doubt about epidemiologic studies using methodological battles, a strategy pioneered by the tobacco companies … .”[12] There is no corresponding concern about the negative effect of producing incentives to overstate the findings, or the validity of inferences, in order to get to a verdict for claimants.
Post-Modern Causation
What we have then is the ultimate post-modern program, which asserts that cause is “irreducibly chancy,” and thus indeterminate, and rightfully in the realm of “normative decisions.”[13] Lahav maintains there is an extreme plasticity to the very concept of causation:
“Causation in tort law can be whatever judges want it to be… .”[14]
I for one sincerely doubt it. And if judges make up some Lahav-inspired concept or normative causation, the scientific community would rightfully scoff.
Taking Lahav’s earlier paper, “The Knowledge Remedy,” along with this paper, the reader will see that Lahav is arguing for a rather extreme, radical precautionary principle approach to causation. There is a germ of truth that gatekeeping is affected by the moral quality of the defendant or its product. In the early days of the silicone gel breast implant litigation, some judges were influenced by suggestions that breast implants were frivolous products, made and sold to cater to male fantasies. Later, upon more mature reflection, judges recognized that roughly one third of breast implant surgeries were post-mastectomy, and that silicone was an essential biomaterial. The recognition brought a sea change in critical thinking about the evidence proffered by claimants, and ultimately brought a recognition that the claimants were relying upon bogus and fraudulent evidence.[15]
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[1] Margaret A. Berger, “Eliminating General Causation: Notes towards a New Theory of Justice and Toxic Torts,” 97 Colum. L. Rev. 2117 (1997).
[2] Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11 (1st Cir. 2011), cert. denied sub nom., U.S. Steel Corp. v. Milward, 132 S. Ct. 1002 (2012)
[3] Alexandra D. Lahav, “Chancy Causation in Tort,” (May 15, 2020) [cited as Chancy], available at https://ssrn.com/abstract=3633923 or http://dx.doi.org/10.2139/ssrn.3633923.
[4] Alexandra D. Lahav, “The Knowledge Remedy,” 98 Texas L. Rev. 1361 (2020). See “The Knowledge Remedy Proposal” (Nov. 14, 2020).
[5] Chancy at 2 (citing American Law Institute, Restatement (Third) of Torts: Physical & Emotional Harm § 26 & com. a (2010) (describing legal history of causal tests)).
[6] Id. at 2-3.
[7] Id.
[8] Id. at 10.
[9] Id. at 12.
[10] Id. at 2.
[11] Id. at 8 (citing David Michaels, The Triumph of Doubt: Dark Money and the Science of Deception (2020), among others).
[12] Id. at 18.
[13] Id. at 6.
[14] Id. at 3.
[15] Hon. Jack B. Weinstein, “Preliminary Reflections on Administration of Complex Litigation” 2009 Cardozo L. Rev. de novo 1, 14 (2009) (describing plaintiffs’ expert witnesses in silicone litigation as “charlatans” and the litigation as largely based upon fraud).
