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My Challenges with AI

December 10, 2025

My Challenges with AI

AI has taken over the world of technology; from software developers to artists, AI has an effect on almost all of us these days. In this essay I will be talking about the effects AI had on me as a college student and weigh out the good, the bad and the ugly.

The Good

Starting off with the good. AI has immensely aided in my understanding of various subjects from Computer Architecture (CS 2200) to understanding the Psychology of Cybersecurity (CS 4263). Whenever I am stuck, I see AI as an instant solution towards understanding the topic that I am having trouble with. Instead of having to wait for answers of Piazza or Ed discussion, or wait in lines at office hours, I am able to head over to an AI chatbot and get my answers instantly. Now you may be wondering, what if the answers are wrong? Well to limit this I give the AI the correct context. For example, if I am studying for a quiz for a math course, I would give the AI the correct lecture slides, textbook, study guide, etc. and then ask it questions based on the material. This strategy is especially useful with LLMs such as Notebook LM because it will only give you answers based on the text that you give it and no outside sources (unless you prompt it to use outside sources). AI also gives me the ability to really dig deep into a topic by asking it questions until I get a thorough understanding. This is especially beneficial in classes where office hours are usually crowded and you are not able to have too much time with the TA. The AI can serve as your substitute TA.

The Bad

Now, although these use cases help in bettering my education, there are many use cases where AI has done the opposite. The rise of AI in the past 3 years has caused many professors to begin to integrate it within courses. The professors understand the inevitability of AI usage by students in these courses, so they arrange for it to be available to students, but with various restrictions. One of the most common restrictions is copy and paste. Copying and pasting content from an LLM to an IDE or to wherever your workspace is, is almost always a violation in many courses. Having this type of tool freely available to students is very dangerous when it comes to our education. It is very easy and tempting for students to simply finish the assignment using AI. It is like having all the answers to the test, but you force yourself to not take a lot before going into the test. Although the restrictions help, they only do so much in restricting AI usage. In my personal experience, AI usage has done more good than harm for my education, but there are definitely instances (especially in essay writing) where I used AI to accelerate my writing process.

The Ugly

That was the bad part of AI, now let’s get into the ugly. The ugly part of AI usage is essentially a more extreme use of what I stated in the bad. AI use in the wrong students’ hands can be extremely detrimental to their education. From my personal experience as a student I can completely see how someone can get through all 4 years in college without learning a thing and simply just using AI. Especially with the larger tokenized models that continue to release every few months, I speculate that in less than a year (unless colleges find extreme AI detection resources) there are going to be many students that can achieve their whole degree with just AI.

To sum up my position through my anecdotal experience, I would say that the benefits of and detriments of AI all depend on the person using it. If someone wants to better their education by using AI as a partner to learn then they would benefit tremendously, but if one simply uses AI as a tool to complete all of their assignments then they would reap the detriments of AI usage.

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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.