The podcast discusses the importance of transparent AI concepts, including managing and running AI systems, addressing visibility into AI creation and application, exploring challenges in AI training data, and highlighting the role of transparency in building trust with users.
Transparency in AI systems builds trust by providing visibility into data processes and model design.
The Trustworthy AI Framework emphasizes transparency, bias mitigation, open systems, disclosure, and consent for trustworthy AI implementation.
Deep dives
Importance of Transparency in AI Systems
Transparency in AI systems is vital for engendering trust, as it provides visibility into the data collection, aggregation, and model design processes. Without transparency, users cannot understand the basis for AI decisions and may face challenges in detecting and addressing data issues. By offering visibility into all system components, organizations can build trust and address problems early on to ensure the system's accuracy and reliability.
Elements of Trustworthy AI Framework
The Trustworthy AI Framework emphasizes key elements such as AI system transparency, bias measurement and mitigation, open systems, and disclosure and consent. Organizations must disclose the data and system components used, actively mitigate biases, operate with open-source technology, and ensure transparency and consent for human interactions with AI systems. Providing these elements fosters trust, allows individuals to opt-out, and ensures ethical AI usage.
Training and Certification for Trustworthy AI
Cognitica offers training and certification programs to enhance AI project management and ensure trustworthy AI implementation. The courses cover aspects of ethical, responsible, transparent, governed, and explainable AI, preparing individuals to navigate emerging AI laws and regulations. By enrolling in these programs, participants gain expertise in building and managing trustworthy AI systems, combining essential practices for successful AI projects.
AI system transparency is about how we manage and run our AI systems. Transparency needs to address how you plan to provide visibility or transparency into how AI systems are created or applied. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the transparent layer of AI as part of Cognilytica’s Trustworthy AI Framework.