Autoplay
Autocomplete
Previous Lesson
Complete and Continue
The Building Blocks of Inclusive AI
Introduction and Overview
Welcome! Learning goals for each module, copyright, trigger concerns, and referral codes (11:13)
Core Concepts in AI
Core Concepts Module intro and PDF (1:04)
AI in historical context (11:07)
The innovation of machine learning (15:17)
High dimensional space (6:50)
The importance and role of data (10:07)
AI as sociotechnical (22:07)
The AI lifecycle (7:29)
Module quiz (10 questions)
Training an AI Model
Training an AI model intro and PDF (1:03)
4 types of training (21:28)
The training process (supervised) (11:31)
Defining "Success" in AI (23:54)
Difference between statistics and AI (16:17)
Module quiz (10 questions)
Data and Data Bias
Data and Data Bias Intro and PDF (0:59)
The Global Digital Divide (11:15)
Ask: Who is in the Data? (8:44)
Ask: how are they in the data? (10:36)
Ask: what are the politics of data? (11:29)
Sociotechnical framework for train/test datasets (2:43)
Unintended consequences of AI-driven data hunger (10:26)
Best practice: Contextual datasets (14:20)
Module quiz (10 questions)
Building Blocks of AI Closer
Rapid review, congratulations, and link to review/referral codes (3:32)
Optional: Please leave me a review and let me know what I did well and how I can improve!
Teach online with
Defining "Success" in AI
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock