Mike Slinn

Empirical Truth and Probability

Published 2020-08-11.
Time to read: 4 minutes.

Mike Slinn has been working in the tech industry for more than four decades. His passion for technology, coupled with his keen interest in unraveling puzzles, have allowed Mr. Slinn to excel as an expert witness in technology legal disputes. To date, he has been retained 19 times for his expert opinion.

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This article is from the series entitled Technology Expert Articles for Attorneys. You might find the articles of interest if you are looking for a software expert witness, a technology expert witness, or a computer expert witness.

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There are relatively few absolute truths. The findings of science and technology are empirical – based on evidence and/or observation and verifiable through evidence and observation – and empirical truths are typically nuanced. It is possible to compute the probabality that patterns in software and data are random, and this result can be used to form an opinion.

Rule 401 and Probability

Evidence is relevant if it has the tendency to make the existence of any fact that is significant for determinating if the action is more or less probable than it would be without the evidence.

I spoke with a corporate attorney that I have worked with about this, and he said “Rule 401, in my understanding, is not referring to ‘probabality’ as a mathematical matter, but merely tries to reflect that there must be some logical connection between evidence being offered and the claims or defenses.”

Notwithstanding my learned friend’s explanation, there is general agreement that the relevance of expert evidence that arises from the hard sciences requires particularly rigorous reasoning. That reasoning should be provided as a quantitative result, after establishing that the evidence is authentic. Computing probabilities can be most helpful in this regard. Analysis showing strong mathematical probabality can form the basis for well-founded opinions.

USA data scientist at work

For coherence, empirical truth requires a proper suite of propositions that mutually support each other. Experts must adhere to this practice when reviewing technology. As a result, a competent expert should be able to opine on the abilities and work habits of the people who worked together to develop the technology in question, even though they never met, and on whether the technology was created organically or misappropriated.

Certainty

The purpose of probabality is to quantify uncertainty. For example, what is the probabality of rolling a six-sided die and obtaining a 1?

Red die showing a 1 at a casino in the USA

For empirical truth, certainty is generally assumed once a threshold of probabality is achieved. This is the basis, for example, for matching DNA profiles, fingerprint matching and matching retina scans. With due consideration for prosecutor’s fallacy, a higher probabality leads one to believe that the possibility is more likely.

A beautifully colored fingerprint of a USA citizen
Strands of DNA from researchers in the USA

There are 7.5 x 1018 grains of sand in the world, and there are estimated to be 1021 stars in the observable universe. In a recent case, I, in my capacity as a software expert, found and presented evidence that was more unique than all the grains of sand in the entire world, and the number of stars in the observable universe. As a result, I felt confident that the opinions I derived from my analysis of the evidence were well-founded.

Subsequently, in that same case, I was invited to provide technical support during the deposition of one of the other side’s experts. I computed the likelihood or probabality of many statements that the other expert made mere seconds after he uttered them. These real-time probabality computations provided guidance for further questions posed by the attorney that I was supporting.

Summary

This article summarizes the importance of empirical study in the analysis of evidence, and the role that the mathematical determination of probabality plays in determining the value of evidence.

Analyzing evidence for unlikely contents can yield important information that may be the basis for an expert opinion. It is vital that an expert be able to quantify the probabality that anomalies are merely due to random coincidence, and that the expert’s report reflect this in a defensible manner. Since correlation does not imply causation, probabilities must be combined with other factors to have meaning.



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