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SubscriptionThe Ethics of AI & Machine Learning [Full Course]
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The full course starts with what AI is and how machine learning and neural networks work, then turns to datasets and the black-box problem. Only after that foundation does it move into ethical theory, thought experiments and the risks of advanced AI.
Healthcare, education, finance and employment each get a chapter, followed by a segment on AI and policy. The closing chapter looks at the future of ethical AI, which gives the course a practical arc from theory to real-world sectors.
The description says segments feature speakers from Encode Justice, Fidutam and the Future of Life Institute. Their segments add outside perspectives on advocacy and research to the main material.
Listed as beginner, it works for anyone who wants a broad first pass at AI ethics in one sitting of around 90 minutes.
Should AI systems have personhood? Is AI biased? Go from 0 to 1 in AI ethics in 90 minutes!
In this video, you will learn about the foundations of AI, its applications, and the ethical considerations that shape this transformative field.
✏️ Course created by Seth Goldin - https://twitter.com/seth_goldin
❤️ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba)
⭐️ Course Contents ⭐️
✨ (00:00) Opening Remarks
📝 (02:08) Intro to AI Ethics
🤖 (10:52) Basics of AI/ML
🧠 (18:37) Neural Networks
🐶 (25:56) Datasets
⬛ (28:54) Limitations of AI & Black Boxes
⚖️ (38:48) Intro to Ethics
💭 (45:38) Thought Experiments
☣️ (52:06) The Singularity and AI Risk
🫀 (01:02:16) AI in Healthcare
✏️ (01:08:45) AI in Education
📈 (01:13:29) AI in Finance
🫂 (01:18:37) AI in Employment
🌏 (01:27:00) AI and Policy
🌱 (01:37:49) Future of Ethical AI
This course also showcases segments from guest speakers Sneha Revanur (https://twitter.com/sneharevanur) from Encode Justice, Okezue Bell (https://twitter.com/okezuebell) from Fidutam, and Emilia Javorsky (https://futureoflife.org/person/emilia-javorsky-md-mph/) from the Future of Life Institute.
Mostly unaffiliated links to dive deeper into topics discussed in this course:
🔗Deep Reinforcement Learning Visualized: https://www.youtube.com/watch?v=2tamH76Tjvw
🔗Deep Learning Crash Course: https://www.youtube.com/watch?v=VyWAvY2CF9c
🔗The Rise of the Machines - Why Automation is Different this Time: https://youtube.com/watch?v=WSKi8HfcxEk
🔗Do Robots Deserve Rights? What if Machines Become Conscious?: https://www.youtube.com/watch?v=DHyUYg8X31c
🔗The big debate about the future of work, explained: https://www.youtube.com/watch?v=TUmyygCMMGA
🔗A Collection of Lectures on the Ethical implications of Data and Artificial Intelligence from Different Perspectives: https://aiethicscourse.org/
🔗Predictive Policing: https://www.youtube.com/watch?v=A-PrLbawdgg
🔗Elections and Disinformation: https://www.goodreads.com/en/book/show/28186015
🔗AI Safety – Full Course on Machine Learning & Ethics (Center for AI Safety): https://www.youtube.com/watch?v=agEPmYdbQLs
🔗How AI Could Save (Not Destroy) Education | Sal Khan: https://www.youtube.com/watch?v=hJP5GqnTrNo
🔗ProPublica Study on Recidivism: https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm
🔗Course on AI Safety: https://aisafetyfundamentals.com/
YouTube videos with brief clips utilized in this course:
📼The Trolley Problem | The Good Place: https://www.youtube.com/watch?v=DtRhrfhP5b4
📼AlphaFold: The making of a scientific breakthrough: https://www.youtube.com/watch?v=gg7WjuFs8F4
📼Stock Market Crash - Flash Crash May 6, 2010: https://www.youtube.com/watch?v=E1xqSZy9_4I
📼Taylor Swift – Starboy (AI) and Barack Obama Deepfake supplied by Encode Justice
🎉 Thanks to our Champion and Sponsor supporters:
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👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
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