早稲田大学　国際教養学部　AO入試　志望理由書　提出例(早川 有 教授参考)

早稲田大学　国際教養学部　AO入試　志望理由書　提出例(早川 有 教授参考)

Dear Admission Office, 

I am writing this letter with an intention to explain my purpose in applying for School of International Liberal Studies at Waseda University, hoping to pursue a major in Statistics, Operations Research and Cultural Studies later in my academic year. I would be more than grateful if you could kindly give it a read and grant me an unconditional admission or an opportunity to the next in-person interview. I would also be delighted to expand more on my area of studies and what I can achieve upon joining the school.

In a modern, highly industrialized world, as any organization functions on a foundation of any technology or system and responsible engineering teams these days, a role such as reliability engineer emerged. Artificial Intelligence is starting to be adopted in software analysis, electricity power systems, preventing cyber attacks etc. However, recent accidents with AI powered vehicles or technologies also call for liability laws and more precise risk management engineering. According to newly released report by Allianz Global Specialty, The Rise of Artificial Intelligence: Future Outlook and Emerging Risks, examines future risks and implications and discusses the difference between weak and strong AI applications. Some obvious risks, highlighted by the report, include the increased connectivity among autonomous machines which could lead to more frequent, widespread cyber losses. While AI could reduce cyberattacks, it could also be used to enable them. The authors noted that in an AI connected machine world, a single machine could be used to repeat the same attack “leading to an unforeseen accumulation of losses.” Liability was one of five areas of concern related to advanced or “strong” AI applications outlined by the report. The other four include software accessibility, safety, accountability and ethics.

To explore analysis models used to address technology reliability, from the simplest to the most complex system, building and using a reliability model permits teams to make better decisions thus operations to go smoother. Understanding and monitoring system reliability involves knowing both: the reliability of elements within the system, as well as how the elements relate to each other reliability-wise. There are different types of models experts refer to: Markov Models, Petri Models, Physics of Failures Models, Bayesian Models and so on. Knowledge in Block Chain Diagram, Fault Tree Analysis, Success Tree Analysis and similar greatly help with the analysis.

In recent years, an imprecise Bayesian nonparametric approach to system reliability with multiple types of components is developed. This allows modelling partial or imperfect prior knowledge on component failure distributions in a flexible way through bounds on the functioning probability. Meaning, the industry is making steps toward addressing common concerns by developing a nonparametric method which utilises imprecise probability to model more vague or imperfect prior beliefs using upper and lower probabilities.

We live in a world of rapid change, development, market adoption and following consequences, and more than never risk management and prediction technology has been so important. I wish to gain broad knowledge in international studies and deep dive in statistical approach to common problems. I am impressed with a wide range of study programs in relevant field. And in order to attain high-level education and equip myself with what is needed to survive the next decades of globalization and competition, it is extremely important for me to study various international studies among like-minded students at Waseda where liberal studies is offered. Thank you very much for reading and I am very much looking forward to hearing good news.