Information Literacy: critical thinking and practical skills - - PowerPoint PPT Presentation

Information Literacy:

critical thinking and practical skills

TERESA SCHMIDT MERCER PUBLIC LIBRARY SEPTEMBER 18, 2020

Week 2

BUT WHY DO THEY DO IT?

Ground Rules

▪ Listen respectfully, without interrupting. ▪ Listen actively and with an ear to understanding others' views. ▪ Criticize ideas, not individuals. ▪ Commit to learning, not debating. ▪ Avoid blame, speculation, and inflammatory language. ▪ Allow everyone the chance to speak. ▪ Avoid assumptions about any member of the class or generalizations about social groups. ▪ Do not ask individuals to speak for their (perceived) social group. ▪If you don’t want to appear in the recording, please turn

• ff your video feed before you ask a question.

University of Michigan Center for Research on Learning & Teaching, https://crlt.umich.edu/publinks/generalguidelines

Questions & Comments

NOTES FROM LAST WEEK

TikTok

POLITICAL FOOTBALL OR SECURITY RISK?

Misinformation in Mainstream Media

CDA, secti tion

• n 230: “No provider or user of an interactive computer

service shall be treated as the publisher or speaker of any information provided by another information content provider.”

Take-aways from these examples…

1. Mainstream media are not perfect! 2. Suing someone is not proof of their guilt. 3. Mainstream media can, in fact, serve to increase the dissemination of fake news.

https://www.tandfonline.com/doi/full/10.1080/23808985.2020.1759443

Psychology of Misinformation

HOW DOES OUR PSYCHOLOGY WORK AGAINST US?

Cognitive Biases

“A collection of faulty ways of thinking that are hardwired into the human brain.”

Photo by Robina Weermeijer on Unsplash https://www.theatlantic.com/magazine/archive/2018/09/cognitive-bias/565775/

Cognitive bias in info literacy

Confirmation bias

“The tendency to interpret new evidence as confirmation of one's existing beliefs or theories.” Oxford Languages

Illusory truth effect

“The illusory truth effect (also known as the illusion of truth effect, validity effect, truth effect, or the reiteration effect) is the tendency to believe false information to be correct after repeated exposure.” Wikipedia

In-group bias

The tendency for people to give preferential treatment to others who belong to the same group that they do.” The Decision Lab

Proportionality Bias

Our innate tendency to assume that big events have big causes. May also explain our tendency to accept conspiracy

• theories. Wikipedia

Dunning- Krueger Effect

"The best lack all conviction, while the worst Are full of passionate intensity."

• W. B. Yeats,

The Second Coming (1919)

Graph used under CC Public Domain dedication by 忍者猫

Backfire Effect

A biological way of protecting a worldview

https://theoatmeal.com/comics/believe_clean The Backfire Effect is mostly a myth: www.niemanlab.org/2019/03/the-backfire-effect-is-mostly-a-myth-a-broad-look-at-the-research-suggests/

Discussion

WHAT STRUCK YOU FROM THIS WEEK’S READINGS? HAVE YOU EVER SEEN EXAMPLES OF THESE COGNITIVE BIASES?

Bots, Trolls, and Imposters

WHAT ARE SOME OTHER WAYS YOUR NEWSFEED GETS DISTORTED?

Imposters

Source goes here!

Trolls

Photo by Mark König on Unsplash

Real people who (are paid to) spread misinformation through social media and comments sections.

Troll Farms

50 Cent t Army y – Chinese government initiative.

One 2016 estimate showed 440M+ fake posts per year.

Intern ernet t Resear search ch Agency cy – Russian company promoting government and business interests

Facilities in Ghana and Nigeria; hundreds of accounts

Turning ing Point t Ac Action ion (TPA) ) – Arizona-based conservative group focusing on young people.

Paid people (some minors) to coordinate posts using their own social media accounts, according to reporting by the Washington Post.

Spot

• t the

e Troll ll – spotthetroll.org

Source goes here!

Bots

“Everyone is talking about it!” – an example of the illusory truth effect 2017 USC study: up to 15% of Twitter accounts are bots 2016 USC study: 19% of election-related tweets during the study were generated by bots 2020 Carnegie Mellon study:

• Of the top 50 influential retweeters discussing the

coronavirus, 82% are bots

• Bots are “dominating the conversation about ending stay-

at-home orders and ‘reopening America,’” and there is evidence that the bot activity is coordinated.

Photo by Markus Spiske on Unsplash https://www.cmu.edu/news/stories/archives/2020/may/twitter-bot-campaign.html

Predictive Analytics

“Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.” Wikipedia

Photo by Mika Baumeister on Unsplash

Filter Bubbles

“A situation in which an Internet user encounters only information and opinions that conform to and reinforce their own beliefs, caused by algorithms that personalize an individual’s online experience.” – Oxford Languages

“…what’s in your filter bubble depends on who you are, and it depends on what you

• do. But the thing is that you don’t decide

what gets in. And more importantly, you don’t actually see what gets edited out.”

– Eli Pariser

Filter bubbles and echo chambers effectively serve different realities to different people.

Next week

IDENTIFYING BAD INFORMATION

Readin ing: g: feuniversity.org/information-literacy-fall-2020/

Thank you!

TERESA SCHMIDT Mercer Public Library

d i r e c t o r @ m e r c e r p u b l i c l i b r a r y. o r g

715.476.2366 feuniversity.org/information- literacy-fall-2020/