Palsgraf articulated the doctrine of proximate cause, necessary to prove the tort of negligence. Palsgraf needs to be reexamined in light of today\u27s understanding of cause and effect. The case concerned a woman (Mrs. Palsgraf) standing on a train platform who was injured by a roof tile that fell as the result of the vibrations caused by the explosion of another passenger\u27s package. Mrs. Palsgraf sued the railway for negligence and prevailed at the trial court level. The New York Court of Appeals reversed the trial court, however, holding that the railway company\u27s actions were not the proximate cause of Mrs. Palsgraf\u27s injuries. Modern science recognizes that the railway station constituted a complex dynamic system. Palsgraf was decided in 1928 at a time when understanding of cause and effect in complex dynamics was minimal and steeped in a linear mind-set. Because the understanding of cause and effect in these systems has been significantly advanced by the field of nonlinear dynamics in recent years, the case should be reexamined in this new light. Linear systems have outputs that are proportional to their inputs and are therefore predictable. But linearity inadequately models most of the real world. Nonlinear systems, though not recognized by most as such, are more prevalent than linear systems and have outputs disproportionate to their input. A subset within the group of nonlinear systems are chaotic systems, the main focus of this essay. The title “chaotic” is misleading as these systems still follow discrete physical laws. But it is their sensitivity to initial conditions that makes them unpredictable. What appears as a random result may actually be a strong reaction to immeasurable inputs at the beginning of a sequence of events. The weather is a good example of this principle, termed deterministic chaos. There is no way to isolate and define each initial condition that goes into a weather pattern, but as will be shown, each initial condition may radically affect the resulting systems. Chaotic systems exist alongside predictable linear systems. In Palsgraf, the train station had both regular, predictable systems, such as the track being able to carry the weight of the train, and some unpredictable, chaotic systems, such as the interaction of the exploding package, the roof tiles, and Mrs. Palsgraf. If an accident happened that involved a regular system, then it is more likely that the railway should have been held liable. This is because the engineers who designed the station should have known the linear parameters within which the station could be used safely. Had they neglected to act on this knowledge, the company would have been negligent. However, because the system involved was a high dimension chaotic system-many interacting degrees of freedom-the system was subject to the principle of sensitivity to initial conditions, and Mrs. Palsgraf\u27s injuries were in no way foreseeable or direct even though chaos theory elucidates the causal link between explosion and injury. Because they were in no way foreseeable or direct, the defendant had no duty toward the plaintiff with regard to the roof tile. So, according to the doctrine of proximate cause as articulated in this case, it still holds that the company was not negligent and the court\u27s finding is supported. There is a second way to look at proximate cause and Palsgraf in light of modern scientific theories. Modern theories postulate that the apparently chaotic phenomenon which are occurring at the station are actually following rules. A deterministic pattern of behavior exists even though it is not readily discernible. All of the operative degrees of freedom define a phase space, and phase space analysis may elucidate the system\u27s deterministic behavioral patterns. Phase space analysis is a tool used to visualize the behavior of a dynamic system over time. Many dynamic systems generally behave in a stable manner, but intrusions from outside a system can alter the stability in varying degrees. Depending on the disturbance, the system may return to its original pattern, or may be permanently disrupted, adopting a completely new pattern of behavior. Phase space analysis provides a second way to look at Palsgraf . In a system made of a train station and a train, there are a number of phase space portraits which demonstrate predictable patterns, such as the location of the station\u27s platform. Other portraits, such as those that include the movement of passengers, are never stable. The railway company has a responsibility to maintain the stable system within safe parameters so that it is not permanently disturbed by outside systems. Because the roof tiles at the train station were loose, they were subject to being disturbed. The loose tiles created what scientists call a zone of danger, and the accident was therefore foreseeable. The railway station did not take the proper precautions, and liability results. Using phase space analysis, Palsgraf would have been resolved as Judge Andrews suggested in his dissent, and the train company would have been liable. These same theories and scientific principles can be applied to most proximate cause tort cases. The appendix following this essay contains examples of actual cases decided using these principles
