No description, website, or topics provided.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
readings fix Sep 21, 2018
.gitignore some readings added Aug 23, 2018 just backup Sep 21, 2018
reading_guidelines.pdf edited for reading guidelines Sep 5, 2018

Ethical Issues Surrounding Artificial Intelligence Systems and Big Data

Course description

This course will consider some large questions surrounding ethics in artificial intelligence systems. These questions include:

  • Do computers make decisions in a way that is more fair and less biased than people?

  • What are the political, legal, social, economic and technological forces that govern the digital world? Which forces are in opposition? Which forces are aligned?

  • What role does the government currently play in directing AI technology in the United States? What role could the government play? What are the advantages and disadvantages of different approaches?

Schedule and readings

Readings and videos listed under each week are to be done before that week's class.

Reading response guidelines and a sample response can be found here.

Week 1: Inspiration

Week 2: Machine Learning Foundations

Machine Learning and Human Bias

AI can be sexist and racist — it’s time to make it fair

Introduction to Weapons of Math Destruction. Check Moodle for the week's reading.

Week 3: Ethical Intuitions

Advances in AI are used to spot signs of sexuality

Why Stanford Researchers Tried to Create a ‘Gaydar’ Machine, New York Times

Challenge: Author's Note, Kosinski and Wang

Week 4: Ethical Foundations

Social Philosophy: Marx, Rawls and Nozick

  • Reading is from Donald Palmer, Does the Center Hold?

Challenge: Stanford Encyclopedia of Philosophy: Philosophy of Technology

Week 5: Fairness

Machine Bias

A computer program used for bail and sentencing decisions was labeled biased against blacks. It’s actually not that clear.

Challenge: Even Imperfect Algorithms Can Improve the Criminal Justice System

Week 6: Fairness

Semantics derived automatically from language corpora contain human-like biases

How Vector Space Mathematics Reveals the Hidden Sexism in Language

Challenge: Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

Week 7: Fairness

'Three black teenagers' Google search sparks outrage

Racism is Poisoning Online Ad Delivery, Says Harvard Professor

Facebook Lets Advertisers Exclude Users by Race

Week 8: Privacy

Amazon’s facial recognition matched 28 members of Congress to criminal mugshots

Want to Predict the Future of Surveillance? Ask Poor Communities

Challenge: Face Off: Law Enforcement Use Of Face Recognition Technology

Week 9: Privacy

Amazon Echo and the Hot Tub Murder

How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did

Congressional Republicans just voted to let ISPs sell your browsing history to advertisers

Challenge: Simple Demographics Often Identify People Uniquely

Week 10: Automated Decision-Making and Interpretability

The Dark Secret at the Heart of AI

When Is It Important for an Algorithm to Explain Itself?

Week 11: Accountability and Regulation

The next big battle over internet freedom is here

What the government could actually do about Facebook

Week 12: Diversity

The Tech Industry’s Gender-Discrimination Problem

The Real Reason Women Quit Tech (and How to Address It)

We tested bots like Siri and Alexa to see who would stand up to sexual harassment

Week 13: AI for Social Good and Reflection


Your grade will be based equally on the following:

  • 50% Online reading responses. Each week in this course you will write an online response to the readings on Moodle. You must turn in your response before class to receive credit for the week.
  • 50% Participation during class discussions. This class will have weekly in-class discussions. Different students may participate in different ways: for instance by talking in large groups, talking in small groups or listening carefully to others.

Class policies

The following guidelines will create a comfortable and productive learning environment throughout the semester.

You can expect us:

  • To start and end class on time
  • To reply to emails within 24 hours on weekdays and 48 hours on weekends
  • To assign readings and class activities that will foster engaging discussion

We can expect you:

  • To come to class on time
  • Since we will be discussing complex issues, to come with an open mind
  • To assume the best of others' intentions in discussion
  • To be respectful of others' viewpoints
  • As much as possible, back up comments with evidence, argumentation, or recognition of inherent tradeoffs