Using Machine Learning to Filter Fraudulent Jobs; A Care Ethics Analysis of Equifax Data Breach Response 127 views

My technical work and my STS research are connected through the idea of the importance of personal data. Data is a collection of information,but some information is more valuable than others. Personal data includes information such as credit card information, medical records, and other important information that should be kept private. Both my technical work and STS research analyze systems that target people’s information. My technical work focuses on using machine learning and artificial intelligence to improve detecting fraudulent job postings on popular job seeking platforms. My STS research analyzes the response of a company after a data breach. While spam filtering and data breaches handels different scenarios regarding data, both my STS and technical work are seeking ways to better protect and handle personal data. My technical work focuses on the spam filtering system of job seeking platforms. Similarly to spam email filtering systems, I looked at ways machine learning and artificial intelligence can improve how Linkedin could reduce fraudulent job postings. Analyzing the similarities between fake job posting, I can find the type of individuals and jobs that scammers are targeting to help sort real and fake job opportunities. I also explored ways to continuously improve and maintain the filtering system by employing works to produce updated datasets and sharing it with other platforms. While it is important for individuals to be educating in spotting scams, this idea will also limit and reduce visible scams to individuals on these popular platforms. My STS paper also explores data through analyzing a popular data breach on Equifax. I evaluated the response from Equifax after the data breach occurred. The individuals most impacted by the data breach were Equifax’s consumers, so it is important to analyze the relationship between the two. To better understand the relationship between Equifax and its consumers, I utilized the care ethics specifically care ethics in practice to view the responsibility Equifax has to its consumers. I use this framework to conclude the morality of Equifax’s response. While it is important to analyze ways to prevent data breaches, it is also important to view ways to respond with the consumers’ best interest in mind. From working on these projects, I was able to understand the significance of data. Data is all over the world, but working on the STS paper along with my technical work made me realize how important it is to protect and be more aware of personal data. My technical work showed me that personal data is very valuable where thousands of people are trying to steal it through scams in job postings. It made me more aware of potential scams in other cases such as email and other applications. Similarly, the STS paper revealed how companies are not careful with private information where data is stolen and companies do not know how to handle the aftermath. From these works, I was able to explore the issues with how we currently handle data and how to improve to become a better engineer.

BS (Bachelor of Science)

data; machine learning; data breach; care ethics; Equifax

English

All rights reserved (no additional license for public reuse)

2024-05-08