Course Intro & Overview
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Course Intro & Overview

Dates
May 24, 2023
Type
LectureLab
Section
Introductions
Guest Speaker

Topic: Course introduction and overview

Lecture Notes

Key Terms

Ethics, moral philosophy, consequentialism, deontology, virtue ethics

Guiding Questions

  1. How do different ethical theories approach moral decision-making?
  2. How can ethical theories be applied to AI and technology?
  3. What challenges do AI and technology pose for traditional ethical theories?

To Read

📕Ethics: The Essential Modern Writings (Introduction)

Key Quote

image

To Watch

Journal Prompt & Group Work

Group Prompts & Case Study
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Let’s dive into the deepend. Your group’s answers don’t have to be perfect. You may not have a way to find out the information you’d like to have. Call out those gaps, questions, and places where the group struggles.

As a group, create a visual representation on a whiteboard, paper, or you computer that illustrates an ethical dilemma and its implications on AI development within the assigned company. The visual representation should include key elements such as stakeholders (i.e., people involved), potential consequences, and the interplay between ethics, AI algorithms, and the company's products or user experience. Work as a group to develop answers based on your prompts below. The numbers refer to the group number.

People —> Actions (Consequences) —> Results

  1. Google: Algorithmic Bias in Search Results
    • How can Google address the issue of algorithmic bias in search results to ensure fair and unbiased access to information for users?
    • What steps can be taken to increase transparency and accountability in Google's search algorithms?
  2. Facebook: Content Moderation and Freedom of Speech
    • How should Facebook balance the responsibility to moderate harmful or offensive content while respecting users' freedom of speech in the context of AI-powered content moderation?
    • What measures can be implemented to address the challenges of algorithmic content moderation, such as false positives or false negatives?
  3. Twitter: Tackling Online Harassment and Hate Speech
    • How can Twitter effectively leverage AI algorithms to detect and combat online harassment and hate speech without inadvertently suppressing legitimate speech or creating algorithmic biases?
    • What ethical considerations should Twitter take into account when implementing AI-based moderation mechanisms?
  4. Amazon: Privacy and Data Protection in Smart Devices
    • How can Amazon ensure robust privacy and data protection for users of its smart devices, such as Amazon Echo or Ring, which rely on AI technologies for voice recognition and data processing?
    • What are the potential implications of AI-driven smart devices on personal privacy, and how can these concerns be addressed?
  5. Apple: Balancing User Privacy and Surveillance
    • How does Apple navigate the ethical dilemma of balancing user privacy and the need for effective surveillance, particularly in cases where AI algorithms are used for device security or data analysis?
    • What steps can Apple take to enhance user privacy while still addressing security and public safety concerns?
  6. YouTube: Recommendation Algorithms and Filter Bubbles
    • How can YouTube address the issue of filter bubbles and echo chambers created by its recommendation algorithms, ensuring that users are exposed to diverse perspectives and reliable information?
    • What are the ethical implications of AI-driven recommendation systems and the potential impact on societal discourse?
  7. TikTok: Data Privacy and User Consent
    • How can TikTok address concerns related to data privacy and user consent, considering the vast amount of user data collected and processed by AI algorithms?
    • What measures can TikTok implement to enhance transparency and empower users to make informed decisions about their data and privacy settings?
    • How might TikTok strike a balance between providing personalized and engaging content while respecting user privacy preferences?
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Post the answers you came up with on Teams along with the name of everyone in your group and the company you were researching. You only need to post once per group.