The Layers of Trustworthy AI Revisited [AI Today Podcast]
Jan 26, 2024
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In this podcast, the hosts discuss the importance of trustworthy AI and the need for ethical guidelines. They delve into topics such as building AI for positive purposes, complying with regulations, and ensuring transparency and trustworthiness. The podcast also explores the different layers of trust in AI systems, including transparency, governed AI, contestability, and interpretable/explainable AI. Additionally, they emphasize the significance of addressing various AI layers and the availability of a trustworthy AI certification.
The first layer of trustworthy AI is ethical AI, which focuses on building AI projects ethically, avoiding harm, and implementing strict controls if necessary.
The next layer of trustworthy AI is responsible AI, which emphasizes doing things the right way, complying with laws and regulations, and avoiding major workforce disruption.
Deep dives
Ethical AI: Guidelines for Building Trustworthy AI Systems
One of the first layers of trustworthy AI is ethical AI. This layer focuses on the guidelines and considerations for building AI projects ethically. It emphasizes the importance of avoiding harm, whether it be physical, emotional, financial, or environmental. The podcast highlights the need for guidelines and guardrails to prevent unethical implementation of AI, or to provide strict controls if necessary. The episode discusses the various ethical considerations in AI and the importance of addressing them to build trustworthy AI systems.
Responsible AI: Doing Things the Right Way
The next layer of trustworthy AI is responsible AI. It emphasizes the importance of doing things the right way and being mindful of potential implications. The episode mentions the need to build AI for positive purposes, ensure compliance with laws and regulations, and avoid major workforce disruption. Responsible AI involves addressing various aspects such as workforce impact and staying aware of laws and regulations in different regions. By being responsible in AI practices, organizations can uphold trust and build ethical and sustainable AI systems.
Transparent AI: Providing Visibility and Mitigating Bias
Transparent AI is another layer of trustworthy AI that focuses on providing visibility into how AI systems work. It highlights the importance of open systems, human decision-making, and data visibility. The episode emphasizes the need to address bias measurement and mitigation, as well as the significance of disclosure and respecting user consent. Transparent AI aims to build trust by ensuring users understand how AI systems operate and by mitigating potential biases. It also involves making data and decision-making processes transparent for increased user confidence.
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 for organizations. You need to know how to build, use, and interact with these systems ethically and responsibly.