Two symbols, infinite meanings

What do you think the following means?

1010

One-thousand and ten, right? What if I told you that it meant four-thousand one-hundred and twelve? Or three-hundred and fifty? Or simply ten? The truth is that all of these answers are right, depending on what number system you’re using. Let me illustrate with a more abstract example. Imagine you have two symbols that you’re using to count objects. When you have no objects, you represent that with a triangle. When you have one object, you represent it with a heart. What if you have two objects? Well, we can simply box up both of our symbols and use another heart in a different position, say, slightly to the left, to indicate that we have one box of two symbols! To represent three symbols, we can write two hearts next to each other, one heart representing the original meaning–one object–and the next heart representing the second meaning–a box containing two objects. Now when we add both meanings, we get three because our symbols represent three total objects. To represent four, we can use another heart in a different position that represents a box containing two boxes, each with two objects. This is what is known as the binary system, though it is typically employed using the more familiar symbols 0 and 1. The number which we originally displayed, 1010, can be read as follows, from right to left (in our standard decimal system).
(0 * 2^0) + (1 * 2^1) + (0 * 2^2) + (1 * 2^3) = (0 * 1) + (1 * 2) + (0 * 4) + (1 * 8) = 0 + 2 + 0 + 8 = 10

The reason we multiply each number by some power of two is that we have two symbols in this number system. We would call this a base-two number system. In our more familiar decimal system, we have ten symbols–0, 1, 2, 3, 4, 5, 6, 7, 8, and 9. We would call this a base-ten number system. If we wish to represent the number ten, we write “10” to show that we have one box of the preceding ten symbols, and no extra numbers–thus ten total objects. Going back to our original example, the number 1010 in decimal just means
(0 * 10^0) + (1 * 10^1) + (0 * 10^2) + (1 * 10^3) = (0 * 1) + (1 * 10) + (0 * 100) + (1 * 1000) = 0 + 10 + 0 + 1000 = 1010

Likewise, if we want to use some strange number of symbols, like thirteen, we are more than free to do so. We could represent them as follows, the first number as the symbol in our base-thirteen system, the second as our symbol in decimal.
0 = 0, 1 = 1, 2 = 2, … (and so on up to nine), A = 10, B = 11, C = 12. Note that even though we have thirteen symbols, we don’t have a specific symbol that equals thirteen because our symbol for zero gets us up to thirteen total symbols. To represent thirteen, we would write 10 (one box of thirteen objects and zero loose objects). Thus, 1010 would mean
(0 * 13^0) + (1 * 13^1) + (0 * 13^2) + (1 * 13^3) = (0 * 1) + (1 * 13) + (0 * 169) + (1 * 2197) = 0 + 13 + 0 + 2197 = 2210
I hope that makes sense. The main point of this exercise is to show that symbols can be completely arbitrary. Zero does not need to be represented by “0,” nor does two-hundred and eighty-three need to be represented as “283.” We could represent them as a pyramid and a hippo if we wanted to, although the decimal system does a fairly good job at keeping matters concise.

The sexagesimal (base sixty!) Babylonian number system

Image Credit: Babylonian numerals under GNU Free Documentation License.

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.