Published By: MIT Technology Review, 1/23/2017
Researchers developed an app that suggests news stories using locally stored personal data. They are investigating ways to provide services to users without storing their personal information in remote servers, as a solution to privacy issues with news apps.
Flesch-Kincaid Grade Level of Article: 11.9
Extended Discussion Questions
- What advantages does storing data in a server have over reading data locally? What are the disadvantages of storing data in a server?
- The article mentions that the app checks locally stored data on the user’s laptop and phone to suggest news stories to them.
- Are there any potential legal and ethical concerns that arise from this method of tracking data?
- What legal and ethical concerns would arise from storing this data in an online database?
- Which do you personally feel is more invasive?
- What apps do you use that store your personal information on a server?
- Do you feel they store too much personal content?
- Would you prefer to use an app like the one described in this story?
Relating This Story to the CSP Curriculum Framework
Global Impact Learning Objectives:
- LO 7.3.1 Analyze the beneficial and harmful effects of computing.
Global Impact Essential Knowledge:
- EK 7.1.1N The Internet and the Web have changed many areas, including e-commerce, health care, access to information and entertainment, and online learning.
- EK 7.3.1G Privacy and security concerns arise in the development and use of computational systems and artifacts.
- EK 7.3.1J Technology enables the collection, use, and exploitation of information about, by, and for individuals, groups, and institutions.
- EK 7.3.1K People can have instant access to vast amounts of information online; accessing this information can enable the collection of both individual and aggregate data that can be used and collected.
Other CSP Big Ideas:
- Idea 3 Data and Information
- Idea 6 The Internet
Banner Image: “Network Visualization – Violet – Offset Crop”, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0