There was not much work for me to do this week, since the machine learning data is not yet available. I spent most of my time on getting familiar with AWS and reflecting on the ethics readings.
For AWS, I read up on the S3 product. S3 stands for Simple Storage Service, and we may use it to securely maintain and access our data on the cloud. It has multiple tiers like Standard, Infrequent Access and Glacier for varying levels of access amounts and latency requirements. After reading up on all of them, I will use the Standard S3 bucket. It has a durability of 99.999999999% and availability of 99.99%. The high durability ensures that the data will not be lost and the high availability will ensure good enough latency for the purpose of training a machine learning model. Other than S3, I also plan to use EC2 for this project, but I had researched EC2 before this week and my research into it this week did not reveal any new information that changed my plans.
I also spent a good amount of time this week on the ethics readings. I found Langdon Winner’s paper particularly interesting. I didn’t know the extent to which simple design choices made by engineers affected society and culture. It has made me more mindful of my project and gotten me to think about unintended consequences that may arise. While working with data containing images of real people, I must be very careful that the data is secure and used only for the purposes of this project. Otherwise, it could be misused and violate people’s privacy.