MIT EECS | Lincoln Laboratory Undergraduate Research and Innovation Scholar
Investigating the Past to Predict the Future of Personal Privacy
- Artificial Intelligence and Machine Learning
Privacy policies are commonly used in modern technologies to alert and inform people of how services handle their personal data. This includes the usage and sharing of the accessed personal data either implicitly or explicitly. This project will analyze how privacy policies have changed over time. In particular, we would like to identify and compare policy changes that individual companies have implemented and the implications of these changes for users and their personal data. We will compare changes in policies within and across various services (social news retail financial etc.). We will discuss the implications of our findings in the context of privacy preservation and provide guidelines to policy regulators or civil organizations to help preserve and safeguard personal privacy.
“I am interested in online privacy policies and the implications for personal data. While abroad at Cambridge University, I became interested in statistics and machine learning. I will create a dataset of privacy policies over time and employ NLP and machine learning techniques to compare, cluster, and investigate the changes and implications for users. Communication of results is a key to the research process, so I hope to write a paper.”