My road trip has come to an end, as I have finally submitted my research paper and finished my presentation! Submitting my paper and presenting my research was an extremely gratifying experience because I got to see all my work for the past eight months come together.

My overall goal was to answer the question: do healthcare datasets have sufficient racial diversity to be effective in medical artificial intelligence in developing countries? Through a meta-analysis research design, I found that three out of the four healthcare datasets I analyzed did not represent minorities adequately. Other healthcare datasets that are similar to the FluPrint dataset, Diabetes dataset, and MIMIC III dataset will not be racially diverse enough to be used in developing countries.

From this new understanding and the content I researched I hope to explore deeper into the ethical implications of AI. My research found that certain datasets are not racially diverse enough to be used in developing countries. In the future, I could actually use these datasets in AI algorithms and compare the results for various races to determine if there is a disparity. I could also explore the impact of racial biases in AI on various other areas, such as the criminal justice system or upper education. My research process has prepared me to explore AI in the criminal justice system and upper education because I know more background information about racial biases in AI, and how they come to be. Additionally, I understand more about the harmful effects that racially biased algorithms have on minorities; with this knowledge, I can explore the specific consequences of racially biased algorithms in the criminal justice system and upper education. Furthermore, I could look at other ethical implications of AI as well. For example, the debate surrounding the question of who is responsible when AI makes a mistake sounds interesting to me, and I would want to explore that in the future. In conclusion, there are a variety of areas that still need to be researched in AI, a relatively new technology, and I hope to continue researching more about it in the future!

Writing a scientific research paper was a relatively new experience for me. I had never written a detailed methods and discussion section before AP Research, so I learned lots of new information along the way. I learned that my methods have to be very detailed and in-depth so another researcher could mimic them. I also learned about the importance of situating my research with other studies and explaining the implications of my results in the field. The presentation and oral defense was another part of the research process where I learned a lot (Figure 2). I discovered how essential preparation is when presenting your research. The panel also asked me a few difficult questions after the presentation and I had to be ready to defend my methods and results. A few of their questions were challenging for me to answer but I really appreciated the feedback they gave me. In the future, I hope to continue conducting research. Writing the academic paper and giving my presentation has prepared me for future research that I do. I have learned how to formulate a new and unique research question and write descriptive and detailed methods. Additionally, I have experienced presenting my research and talking to others in my topic.

Not only has this journey given me insight into the research process but I also learned a lot about myself as a researcher, student, and human being. As a researcher, I learned to be prepared for uncertainty and changes in research. I am a super organized and prepared person, and I like to plan ahead. Even though I'm pretty flexible, I do like to know changes ahead of time so I can plan accordingly. Therefore, when I ran into some changes in my methods I had to alter my plans and research goal which was unexpected. This was a new experience for me as I had to be flexible and suddenly change my plans. As a researcher, I learned that changes in research are almost inevitable and that sometimes it is necessary to take educated risks.

As a student, I have always thought of myself as hardworking and dedicated, and this class has helped proved this to me. Going into this class, I knew it was not going to be easy and that I would have to spend quite a bit of my time working on my research. Especially first semester, looking at various sources and creating the annotated bibliographies took up a lot of time. However, I stuck with it and am extremely happy that I did. I am very proud of the work that I have done, and I proved to myself that I can accomplish anything I put my mind to.

As a human being, I learned about how important research is for society. I learned the importance of investigating solutions as they may not be perfect, especially with new technologies. There could be things that we are missing that we can only find out through research. I have learned that there are varying perspectives and while a solution can be beneficial from one viewpoint looking at the same solution from another viewpoint can show certain implications that I may not have realized.

References

Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016, May 23). Machine Bias. ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing

O’Neil, C. (2016, September 6). Weapons of Math Destruction. Google Books. https://www.google.com/books/edition/Weapons_of_Math_Destruction/CxD-DAAAQBAJ?hl=en&gbpv=0

Rolle, E. (2017, October 21). File:Colorado School of Mines.jpg [Photograph]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Colorado_School_of_Mines.jpg

Weapons Of Math Destruction. (n.d.). [Photograph]. Amazon. https://images-na.ssl-images-amazon.com/images/I/81e-vyUaB6L.jpg