I am Arthur Kim, and I live in Pennington New Jersey. Throughout grade school, I have always been interested in mathamatics and science, especially chemistry. I have participated in multiple related clubs and even some competitions. Because of this, I now intend to major in chemsitry and also minor in mathematics. Science has also shaped some of my core values, in that I value truth and reason above most things. As a result, I love participating in intellectual discussions, and am enjoying the discussions that we have in class. Besides math and science, I play the cello and have played in youth orchestras and music festivals over the years. Although it is not my main priority, I do participate in the orchestra program here at William and Mary. Overall, I am happy to be here to further study my biggest academic interests.
Based on my impressions from this class so far, I view data science as the use of big datasets and databases in order to make inferences and reasoned judgements about situations in the world. By using new sources of data, humanity has been able to make assessments about populations that were nigh-impossible with older methods of data collection. Because of its ability to provide more spatially and temporally accurate information compared to older methods, data science has a very high potential to improve people’s quality of life.
Though not perfect, data science has proven to be an indespensible means of understanding poverty and vulnerability within populations. For example, for my current research project, I have read that mobile phone data is being used to make more accurate assessments of people’s vulnerability to climate change, allowing for government agencies to act accordingly and improve those peoples’ safety and resilence, which shows that data science is a major step in improving our capacity to adapt to global problems and improve lives. Additionally, by assessing poverty distributions in a more spatially-accurate manner as well as examining correlations in datasets, we have a better understanding of the underlying factors that can play a role in driving poverty. Unfortunately, because the forces at play differ greatly by region, data science does not offer any miracle solutions to poverty, but if combined with other types of knowledge, we can accrue a greater understanding and adapt in order to improve human lives and society.
In addition to understanding human lives and development, data science has allowed us to model highly complex systems. Unfortunately, most global systems do not follow consistent, predictable patterns, making it very difficult to plan for and adapt to change. However, with our ability to accrue more spatially and temporally accurate information with data science, it becomes easier to visualize many of the underlying processes at play in complex systems, enabling us to make better predictions. By being able to make more accurate predictions, we will have a much greater adaptive capacity, improving the resilience of any entity of interest, whether it be a population, business, the economy, et cetera. Overall, I see data science as an invaluable complement to human knowledge as it gives us the ability to make much more accurate assessments and analysis.