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Artificial Intelligence (AI) Learning Resources from MIT

An Introduction by Dr. Dave Dixon

As head of AI Education & Innovation at MIT Open Learning, I get to spend a lot of time discussing the implications of Artificial Intelligence in all sorts of areas from education to business to national defense. There is a lot of noise around AI right now, from wildly optimistic to deeply doomful. We’ve seen similar noise around new technologies like this before. The .com boom (and bust) in the early 2000s certainly commanded the discussion for years, so did social media a little later, and then smartphones most recently. Each of these technologies was truly disruptive and changed quite a bit about how we live, learn, and interact.

It would be tempting to group the current Artificial Intelligence boom with those previous disruptions. I believe that there's something different about this intelligence explosion, however, that deserves special attention.

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David Dixon, Head of AI Education & Innovation, MIT Horizon davedxn@mit.edu
David Dixon, Head of AI Education & Innovation, MIT Horizon davedxn@mit.edu
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I believe Artificial Intelligence is more akin to earlier knowledge revolutions: written language, the printing press, and the internet. Each one of these innovations fundamentally transformed how humans create, process, store, and disseminate knowledge. Written language externalized our thoughts, preserving knowledge between groups and across generations. The printing press democratized access to information, sparking widespread literacy and accelerating the spread of ideas. The internet connected the world's knowledge, enabling instant global communication and collaboration.

Artificial Intelligence is likely to have no less of an impact. We've become so accustomed to new tech breakthroughs making a splash and then normalizing into our daily lives. This phenomenon leads to these breakthroughs becoming mostly taken for granted in a very short time period. The speed of normalization tempt us to see the AI explosion as more underwhelming than it actually is.

Henry David Thoreau explained that, "Before printing was discovered, a century was equal to a thousand years." Yet even for something as revolutionary (and relatively easy to copy) as the printing press was, it took 10 full years for the first printing shop to open after Gutenberg printed his first bible. It was another 10 years before Paris and England would both get their first press shop. By 1500 over 250 cities across Europe would have printing presses, but that was 45 years after Gutenberg’s invention. Its broader cultural and social impacts unfolded over a century or more as the printing press was a major contributing catalyst for the Renaissance, the Scientific Revolution, and the Reformation.

As fast as that explosion was, I don’t know of one knowledgeable person who expects the state of AI in 45 years from now to even be remotely recognizable to what we have today.

This is why it is so important for us to understand AI now – what it is and how it works (to the extent possible). This is especially true for a technology that is designed in so many ways to emulate the cognitive, communication, and social interactions of humans. Just like the three knowledge revolutions before it, this one will neither be all good nor all bad, but it will bring both positive and negative impacts. And the degree to which the good outweighs the bad will largely be in our hands.

In order to help you better understand these new innovations, we have created a constantly updating repository of resources from MIT designed to help you understand Artificial Intelligence. From understanding the foundational science, to predicting the next few steps forward, to diving deep in a wide range of areas, we want you to be able to learn from the best and brightest minds in this space to empower you to be an informed user and leader in AI in your own sphere. I invite you to use the full list, and come back often to it as we update it with new offerings to help you find what you need, but I also want to give you a head start.

Below is a learning pathway that I would recommend for anyone looking for a good place to start. The overall progression broadly follows this path: What is AI & Machine Learning What about Generative AI specifically? What does this mean for certain areas and where can you do a deep dive?

To help you get started and choose your own path, I'll give you an annotated overview of each resource I recommend getting started with:

TOPIC 1:

What is AI and Machine Learning?⁠

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4 Resources;

3 Total videos,

1 Podcast

TOPIC 2:

How Generative AI Models such as ChatGPT Work?⁠

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2 Resources;

1 Video Presentation and the set of Slides used

1 Recommended Article

TOPIC 3:

Current State and Future Directions of AI⁠

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1 Resource;

1 Segmented Video

TOPIC 4:

AI and the Future of Humanity⁠

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1 Resource;

1 Segmented Video

TOPIC 5:

AI in Education⁠

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6 Resources;

1 Video

1 Guide

1 Podcast

1 Article

2 Courses

TOPIC 6:

Application in Various Fields⁠

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2 Resources;

2 Videos

TOPIC 7:

Deep Dive in AI Topics⁠

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1 Resource;

1 Course

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