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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