Join Barton Poulson for an in-depth discussion in this video Supervised and unsupervised learning, part of AI Accountability Essential Training.
- [Instructor] The two major tasks…that artificial intelligence does are first,…unsupervised learning, and two, supervised learning,…and I just want to take a moment to…explain briefly what each of these mean,…and how they work in to some of the issues…that pop up when dealing with artificial intelligence.…Let's begin with unsupervised learning.…The goal here is to sort things.…The data's not labeled with an outcome category.…It's not we're trying to predict this one thing,…but we're simply looking at all the variables together,…and we want to put like with like.…
The goal is to find cases that are similar to each other…based on whatever data you have…in your current data set.…It's a form of clustering, and that can be…really helpful for things like market segmentation…and other practical purposes,…where you want to find groups of cases that are similar…that maybe you can treat in the same way.…The important thing to remember is that…with unsupervised learning, this kind of clustering task,…there is no one correct answer.…
- Bias in AI
- Navigating the social challenges of AI
- Moral reasoning and relational ethics
- General Data Protection Regulation (GDPR) and AI
- Discrimination in data
- Liability and AI
- AI in life-and-death situations
- Confronting the challenges of AI as a developer, executive, and consumer
Skill Level Intermediate
1. The Context for AI
2. Technical Challenges of AI
3. Social Challenges of AI
4. Legal Challenges of AI
5. Safety Challenges of AI
AI in the military4m 36s
6. Confronting the Challenges of AI
Next steps2m 52s
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