Social Issues II

Question 1

Online Social Issues

Answer 1

Cambridge Analytica Scandal
* Overview:
* Exploited Facebook data to target users with political messages.
* Worked with the 2016 presidential campaigns of Ted Cruz and Donald Trump.
* Accused of interfering with the Brexit referendum, though no evidence was found.
* How They Obtained Data:
* Collected data from ~270,000 users through a personality quiz.
* Exploited Facebook’s API loophole to access data from users’ friends without consent.
* Psychographic Microtargeting:
* Combined psychological attributes with marketing techniques to influence individuals.
* Targeting ads based on the Big-5 Personality Traits (OCEAN):
* Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism.
* Results showed increased ad clicks but no conclusive evidence of influencing voting behavior.

Question 2

Misinformation and Disinformation (Definitions)

Answer 2

• Misinformation: False information spread unintentionally.
• Disinformation: Deliberate spread of false information.

Question 3

DisInfo Mitigation Strategies

Answer 3

• Fact-checking.
  
  • Content moderation on digital platforms.
  • Debate over whether social media platforms should fact-check advertisements.

Question 4

Filter Bubble

Answer 4

• Online platforms curate content based on past behavior, search history, and demographics.
• Leads to intellectual isolation by limiting exposure to diverse perspectives.

Question 4

Echo Chamber:

Answer 4

• Environments where individuals only encounter opinions reinforcing their beliefs.
  
  • Outsiders are discredited, increasing polarization.

Question 5

Offline Social Issues

Answer 5

1. Computer Models and Simulations
2. Algorithms in Healthcare
3. Algorithms in Judicial Systems

Question 6

Computer Models and Simulations

Answer 6

Systems designed to predict outcomes of real-world phenomena.
* Examples: Weather modeling, population growth.

Limitations: “All models are wrong, but some are useful.”

Question 7

Algorithms in Healthcare

Answer 7

• Example:
  
  • Algorithm for prioritizing patient care based on cost vs. need.
  • Dissected racial bias in prioritization models.
  • Cost-based model: Black patients prioritized 18%.
  • Needs-based model: Black patients prioritized 46.5%.