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Big Data, Artificial Intelligence, and Ethics
  • Level Foundation
  • Duration 12 hours
  • Course by University of California, Davis
  • Offered by

About

This course gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. With more than 99% of all mediated information in digital format and with 98% of the world population using digital technology, humanity produces an impressive digital footprint. In theory, this provides unprecedented opportunities to understand and shape society. In practice, the only way this information deluge can be processed is through using the same digital technologies that produced it. Data is the fuel, but machine learning it the motor to extract remarkable new knowledge from vasts amounts of data. Since an important part of this data is about ourselves, using algorithms in order to learn more about ourselves naturally leads to ethical questions. Therefore, we cannot finish this course without also talking about research ethics and about some of the old and new lines computational social scientists have to keep in mind. As hands-on labs, you will use IBM Watson's artificial intelligence to extract the personality of people from their digital text traces, and you will experience the power and limitations of machine learning by teaching two teachable machines from Google yourself.

Modules

University of California Computational Social Science (UCCSS)

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • What is this Specialization About?

1 Readings

  • About UCCSS

Getting Started

    • 1 Videos
    • 1 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Learning Goals

1 Videos

  • Course Introduction

1 Readings

  • A Note From UC Davis

Big Data Opportunities

    • 8 Videos
Show info about module content

8 Videos

  • Big Data Overview
  • What is "Big Data"?
  • Digital Footprint
  • Political Data-fusion and No-Sampling (Part 1)
  • Political Data-fusion and No-Sampling (Part 2)
  • Real-time
  • Machine Learning
  • Machine Learning Recommender Systems

Review

    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 1 Quiz

1 Readings

  • Optional/Complementary

Big Data Limitations

    • 7 Videos
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7 Videos

  • Introduction to Big Data Limitations
  • Footprint ≠ Representativeness
  • Data ≠ Reality
  • Meaning ≠ Meaningful
  • Discrimination ≠ Personalization
  • Correlation ≠ Causation
  • Past ≠ Future

Natural Programming Language Activity

    • 1 Readings
    • 1 PeerReview
    • 1 Assignment
Show info about module content

1 Assignment

  • Natural Language Processing (NLP) Assignment Task

1 Peer Review

  • Natural Language Processing (NLP)

1 Readings

  • Welcome to Peer Review Assignments!

Review

    • 1 Assignment
Show info about module content

1 Assignment

  • Module 2 Quiz

Artificial Intelligence

    • 15 Videos
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15 Videos

  • Introduction to Artificial Intelligence
  • A Short History of AI
  • State of the Art
  • The Most Intelligent Gamer
  • Search and Robotics
  • Vision and Machine Learning
  • AI Challenges
  • Moral Frames
  • Predictions From Morals
  • Moral Brain Signatures
  • Computational fMRI
  • (A Personal) History of Dialogue Systems
  • The Art of Dialogue
  • Making Conversations
  • AI Telling Stories

Review

    • 1 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 3 Quiz

1 Discussions

  • Artificial Intelligence: drawing

1 Readings

  • Optional/Complementary

Technology and Ethics

    • 8 Videos
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8 Videos

  • Human Downgrading
  • Attention Economy
  • Exploiting Cognitive Biases
  • Persuasive Tech is Everywhere
  • Digital Exit Strategy - Part 1
  • Digital Exit Strategy - Part 2
  • Digital Exit Strategy - Part 3
  • Digital Exit Strategy - Part 4

Research Ethics

    • 7 Videos
    • 1 Readings
Show info about module content

7 Videos

  • Introduction to Research Ethics
  • Origins: Unethical Medical Research
  • Unethical Social Research
  • Taking Responsibility
  • The Common Rule
  • Ethical Computational Social Science
  • Concerns of an AI Pioneer

1 Readings

  • Slaughterbots

Review

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 4 Quiz

1 Discussions

  • Self-Reflection

Complementary: Ethics in the Day-to-Day of a Computational Social Scientist

    • 2 Videos
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2 Videos

  • Walker on Ethics (Complementary)
  • Shelton on Ethics (Complementary)

Complementary: Language Acquisition Models

    • 4 Videos
Show info about module content

4 Videos

  • Language Acquisition (Complementary)
  • Modeling Framework (Complementary)
  • Computational Model (Complementary)
  • Lessons Learned (Complementary)

Auto Summary

Explore the transformative world of Big Data and Artificial Intelligence with this foundational course. Led by Coursera, it delves into the vast digital footprint of humanity, teaching you to harness AI and machine learning for extracting insights. This 720-minute course also tackles crucial ethical considerations, ensuring a holistic understanding of the field. Engage in hands-on labs using IBM Watson and Google’s teachable machines. Ideal for beginners, it offers flexible subscription options including Starter, Professional, and Paid plans. Perfect for aspiring data scientists and AI enthusiasts.

Martin Hilbert
Instructor

Martin Hilbert