Trustworthy AI Series: Ethical AI Concepts [AI Today Podcast]

AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion - Un podcast de AI & Data Today - Les mercredis

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What are the 5 ethics in artificial intelligence? AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas. Trustworthy AI includes 5 main layers: Ethical AI, Responsible AI, Transparent AI, Governed AI, and Explainable AI. What is ethical AI principles? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer we go over the Ethical AI level of Trustworthy AI. We explain what it is, and review the ethical principles that make up this layer of the Trustworthy AI framework. When discussing ethics, it's important to have conversations around Right/Wrong and what is means in an AI discussion to "Do No Harm". What are some examples of ethical AI use? In this layer of Trustworthy AI, you need to make sure you're addressing aspects related to human values and creating AI for human benefit. Additionally you need to take into account dignity, fairness, respecting diversity, and avoiding bias as much as possible. Also, in this layer you need to keep the human in control! If you want to learn more about all the layers of Trustworthy AI, sign up for our Trustworthy AI certification. Show Notes: Free Intro to Trustworthy AI course Trustworthy AI certification Free Intro to CPMAI course CPMAI Certification AI Today Podcast: Trustworthy AI Series: Ethical AI In the Ethical AI layer of Trustworthy AI, you need to make sure you're addressing aspects related to human values and creating AI for human benefit. Additionally you need to take into account dignity, fairness, respecting diversity, and avoiding bias as much as possible. Also, in this layer you need to keep the human in control! This

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