Several recommendations are made for how developers can identify the challenges that are most relevant to their work in AI and how they can best mitigate the risks while maximizing the benefits of their work.
- [Instructor] If you're the developer…who is creating the actual code and algorithms…for your artificial intelligence project…then I want to recommend a few strategies…that you can use to make your project more effective…and better able to function within the legal,…social, and ethical guidelines…that we've talked about in this course.…The first set of recommendations…have to do with preparing your project…or simply knowing what it is you're trying to accomplish.…First, think about what it is you're trying to maximize,…because any algorithm is going to try to maximize something,…like classification accuracy…or generalize ability in new situation,…think about what it is you're trying to accomplish.…
Also, think about what data you have…that is available for use in your algorithm…and that is legal usable,…because there are certain restrictions.…You may have data available in-house,…but because of something…like the General Data Protection Regulation…you may not be able to use it in the production version…of your algorithm.…
- 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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