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What is Computational Media? – Retrospective from a Graduating Senior

November 22, 2024

What is Computational Media? This is a question I have been asking myself for practically every year I’ve been at Georgia Tech. The truth I have come to realize, however, is that Computational Media is truly whatever you make of it. Let me explain.

I came to Georgia Tech with the goal of becoming an animator, someone who works at an animation studio like Disney or Pixar. I chose Georgia Tech rather than an art school because I wanted to know the technical background of animation software so that one day I may even be able to make my own. Since I wanted to combine both a technical aspect and an artistic aspect, I believed Computational Media would be the perfect fit for me, and luckily, I still do!

To go into more detail about what this degree is, Computational Media is a combination of Georgia Tech’s Computer Science degree and Literature, Media, and Communications (LMC)  degree. This allowed me to learn the technical know-how of a Computer Science degree while also still learning the film principles and background for the more artistic side of animation.

In my opinion, there are two ways to approach this degree. One, you know exactly what you want and because of that you are easily able to tailor your schedule and the types of classes you want to take to those goals. For example, since I know I want to do animation, I took classes like LMC 2730, Construction of the Moving Image, to further my skills in that area. The second way, I would say, is that you don’t know what you want. Believe it or not, I would say that Computational Media is a fantastic degree to have if you know you want to be involved in some sort of media or artistic field but are not sure which angle to approach it at. In my case, even though I knew I wanted to pursue animation, I took many classes in live action film production, video editing, general media studies, video game creation, etc. All of these studies were adjacent to the goal of animation and honestly helped me consider other fields in which I could use this skill. Because of this, I would say I’m a jack of all trades when it comes to different forms of media production.

Now the hardest part of Computational Media is the smallness of the degree. As someone who is currently searching for jobs / applying for internships / applying for grad school, I find myself constantly having to sell myself with my degree and my skills simply because no one knows what Computational Media is or means. I really had to research different fields that my degree applied to and made sure my resume backs my computing skills. Building up both personal projects and class projects so that they look fantastic on a resume is crucial if you want a Computer Science job as a Computational Media major. The same goes for if you want a job in the film industry. You will have a lot of very different types of projects to put on a resume but a lot of times they don’t overlap, meaning you will absolutely need to tailor your resume to the job / internship you are applying for because that’s where recruiters can get confused about what your degree means.

Despite that previous paragraph, I must say that I love my degree. It truly allowed me to experiment in different careers and fields that I have even the slightest bit of interest in and even opened me up to new possibilities that I might not have considered before. We may not have many active alumni, in fact the most famous Computational Media major that I know of is a YouTuber, Danny Gonzalez, but the alumni who do remain connected have a strong passion for helping other Computational Media students find their way in this strange but exciting major. You can truly make this degree anything you want. Whether you want to pursue video game design or animation or UI/UX or even film production, you will find what you need here at Georgia Tech. Heck, if you feel as though you were lacking in any expertise in what you’re pursuing, there are numerous clubs on campus that are here to back you up, such as VGDev and Animation Club.

If you are someone who is applying to Tech and is considering a degree in Computational Media, I hope this gives you some more context. I will be graduating very soon, and I hope to be a very active alumni once I get my feet on the ground. I wish you the best of luck in your Computational Media endeavors, and I hope that you encounter the same joys of exploration and the same kindness of the people around you in this major as I have.

 

References

Computational Media @ Georgia Tech. (2019). CM Promo Video 2019. Georgia Tech. https://youtu.be/412sCbbiPf8?feature=shared

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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.