MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)

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Introductory lecture on Human-Centered Artificial Intelligence (MIT 6.S093) I gave on February 1, 2019. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.

INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/2IDMd0U
Transcript: http://bit.ly/2IDMkcQ
Playlist: http://bit.ly/deep-learning-playlist

OUTLINE:
0:00 - Introduction to human-centered AI
5:17 - Deep Learning with human out of the loop
6:11 - Deep Learning with human in the loop
8:55 - Integrating the human into training process and real-world operation
11:53 - Five areas of research
15:38 - Machine teaching
19:27 - Reward engineering
22:35 - Question about representative government as a recommender system
24:27 - Human sensing
27:06 - Human-robot interaction experience
30:28 - AI safety and ethics
33:10 - Deep learning for understanding the human
34:06 - Face recognition
45:20 - Activity recognition
51:16 - Body pose estimation
57:24 - AI Safety
1:02:35 - Human-centered autonomy
1:04:33 - Symbiosis with learning-based AI systems
1:05:42 - Interdisciplinary research

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Comments

Lex Fridman says:

Human-centered AI is the topic I'm most passionate about and hope to make my life's work. I believe that solving the human-centered grand challenges I outline will lead to big leaps in impact of AI in real-world applications in the next decade. Here's the outline of the lecture:

0:00 – Introduction to human-centered AI

5:17 – Deep Learning with human out of the loop

6:11 – Deep Learning with human in the loop

8:55 – Integrating the human into training process and real-world operation

11:53 – Five areas of research

15:38 – Machine teaching

19:27 – Reward engineering

22:35 – Question about representative government as a recommender system

24:27 – Human sensing

27:06 – Human-robot interaction experience

30:28 – AI safety and ethics

33:10 – Deep learning for understanding the human

34:06 – Face recognition

45:20 – Activity recognition

51:16 – Body pose estimation

57:24 – AI Safety

1:02:35 – Human-centered autonomy

1:04:33 – Symbiosis with learning-based AI systems

1:05:42 – Interdisciplinary research

Hospitality Hero says:

Go watch his interview with Eric Weinstein, before this and you hear it from a different perspective. Thanks for posting such great content Mr.Fridman.

ХОРОШО says:

Human morals are naturally developing. You can impose your morals on the machine today, and reap consequancies 100 years later, when you have to deal with world-ruling machine that have 100 years old morals.

Isaac Yang says:

Thanks a lot for make this publicly available. Would it be possible to have an interview with Prof. Harari, like this this one in Stanford (

, in your Podcast?

Joseph A. Benjamin says:

Brilliant lecture

Callum says:

The problem I have with artificial intelligence has nothing to do with your work Mr Fridman nor MIT.
The problem I have with it is a simple one, how long I'm I going to have a job for?.

These technologies are worrying to me, I've seen shops fire employees replaced by simple
servering kiosks, with the possibly of understanding human expression and emotions and responding accordingly, how much longer in till machines will able to offer the same if not better customer service than me?.

Great talk by the way, just incredibly depressing.

Mike Hatzl says:

Fridman lunch can be eaten by any real OG American mechanic. If presented with realism he would not know what he sees.

Mike Hatzl says:

Y’all are kinda very dumb attempting to explain science without ever taking OG calculus or critical thinking. Fridman speaks sophomorically like he is talking to children. Oh…hahahaha….he is. It is their level. Fridman cannot change a tire or troubleshoot any engine or tune anything ever…..by the way. He attempts to play guitar. He is low level. Calicornication. Is Idiocracy

Voodoolady Ink says:

"This world is full of the most outrageous nonsense. Sometimes things happen which you would hardly think possible."
I learn so much from you! I'm still not married…🖤💗💜💗🖤

Nadja Niemann says:

On a meta-level it is quite interesting: to make machine learning more scalable, deep learning extracts the features without the human labour. Now we are putting the human labour/supervision back again into the system, just into a different role. So that's our human learning curve… Thanks for sharing the lecture. Great to see progress on the human-machine interaction front.

SaintCergue says:

'Arguing machines' reminds me of the recent Boeing 737 MAX crashes. They could have been avoided if redundancy had been taken seriously when designing the MCAS system.

carbon1479 says:

31:00 something to think about with this – deep fakes may not just be videos but phone calls too. Imagine not getting an email from your boss to do an emergency wire for 1.6 million dollars but actually getting a phone call from him, with all his vocal and social nuance, telling you to do it. We'll really have to think security, on everything at every level.

Pablo God says:

Very important

Trezker says:

If netflix and youtube recommendations should inform my view on AI running government, I'd rather keep Trump. Those recommendations only fan the flames of my worst habits.

Christian Nilsson says:

13,832 views

Seems like a very low number

Tom Ganks says:

This is really awesome. I'm watching lectures on a new major discovery. When I look at modern videos of AI, It's like I'm watching the origins of its discovery. The teachings are primal compared to what they will be as time goes by.

Nathan Smith says:

I'm so passionate about AI. It will be one hell of a day once we get true AI. We will have created a god.

amaraa batsukh says:

ya yanggang

eXacognition says:

Excellent video. Looking around the world at the rampant hate, division, war, crime, greed, subjugation and narcissism we have difficulty in our AI cognition work of accepting that the supervision should be one way (i.e. human over AI) even when a 'crowd' or mob is used. We are working to have an AI oversee human supervision to detect bias based on what we call 'seeds' which are very basic conceptual guide posts as a relative measure that most humans should agree on but often don't (i.e. don't kill, don't hate, don't steal, don't lie, etc.). This at least gives an oversight cycle that reports on human guidance infractions. What mechanism in human centered AI addresses the severity of human bias that has produced today's angry world given that some of the worst historical human atrocities were 'crowd' supported?

Impolite Vegan says:

"AI will not be provable fair" -> Human supervision is required.
Since when is the human fair? We need smart AI to make it the unfair created by humans fair.

David Saliba says:

Awesome lecture Lex thanks. If you work a bit on your presentation skills it will be better. The points are not as important as you engaging with your audience. Material is great though. So thanks for this..

Gha Lha Bha says:

Sir Lex Fridman, would you need a vlog publicity partner … I need a normal per event job. I am considering a Q&A portion in my vlog with a sophisticated AI. Kindly See my YouTube Profile. #SacredGeometryCompass #NeutralPossibilitiesSolutions #GlobalInitiatives

Vanessa Ann says:

Showing my son this lecture-it will count for science n tech learning

heems97 says:

Your doing amazing work lex!

Vincent Vincent says:

1:00
Human will not be provably safe => AI supervision is required
Human will not be provable fair => AI supervision is required
Human will not be perfectly explainable => => AI supervision is required

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