Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
The process of producing enormous amounts of ephemeral clothing at accelerated rates, known as fast fashion, creates significant environmental and societal issues. The phenomenon of fast fashion rose due to globalization, economic factors, lack of legislation, and the advancement of technology. Governments, companies, and consumers must work together to create more sustainable retail supply chains. I have gathered information from interviews with individuals in the sustainable fashion industry, books, case studies, online reports, and newspaper articles. Based on my research, I recommend that companies should target wealthier consumers, develop a common language concerning sustainability, invest in sustainable fibers, and listen to factory employees for solutions to improve their working conditions. I also advise that the U.S governments should revise fashion copyright laws and international governments should emphasize regulations concerning the fashion industry. Lastly, consumers should adopt a price-per-wear mindset and utilize resale options. Overall, while perfect sustainability is improbable, consumers, governments, and companies should not use this as an excuse to avoid responsibility.