by Linda Mork
Quick Summary
"Increasingly online, it's become impossible to escape your own point of view." -Eli Pariser
"Increasingly online, it's become impossible to escape your own point of view." -Eli Pariser
"A squirrel dying in front of your house may be more relevant to your interests right now than people dying in Africa." -Mark Zuckerberg
"It will be very hard for people to watch or consume something that has not been tailored for them." -Eric Schmidt
These are the provocative quotes with which presenter Renee Hobbs, Founder and Director of the Media Education Lab, opened at this fall's Minnesota Council of Teachers of English (MCTE) workshop. During the full-day workshop for teachers and media specialists, Hobbs asked attendees to consider the ways in which our digital worlds are becoming increasingly personalized. For example:
- Why do the shoes I was looking at on Zappos follow me from one website to another?
- Why do some FB friends never show up on my news feed?
- Why do Google results seem so different when I use Grandma's computer?
Algorithmic personalization is the process of gathering, storing, and using information from your search history to deliver information specific to your needs and wants. While we may enjoy individualized search results about our product and entertainment choices, personalization and localization of news and information can be much less desirable, especially when the goal is to seek out multiple voices in any given scholarly conversation.
Hobbs shared screenshots of an activity done with students across the world comparing and contrasting the results of Google searches which were conducted at the same time, using the same keywords. Results varied widely depending on the physical location and search history of the user.
Knowing this, she asked, what can educators and librarians do to raise awareness and spark critical thinking as our students and patrons look for and evaluate information? Certainly one way to help users break out of their "filter bubbles" is to encourage them to use library databases, such as those available in eLibrary Minnesota (ELM), that do not utilize algorithmic personalization to find relevant, credible, and diverse perspectives on research topics.
