Trusted AI 101 A Guide to Building Trustworthy and Ethical AI Systems for Healthcare BKG

Trusted AI 101: A Guide to Building Trustworthy and Ethical AI Systems for Healthcare

Fostering trust in AI systems is a tremendous obstacle to bringing the most transformative AI technologies into reality, such as large-scale integration of machine intelligence in medicine. The challenge is to implement guiding ethical principles and aspirations and make the responsible practice of AI accessible, reproducible, and achievable for all who engage with the AI system. Meeting this challenge is critical to ensuring that medical professionals are prepared to properly leverage AI in their practice — and ultimately, save lives.

This guide offers a deep dive into practical concerns and considerations, along with frameworks and tools that can empower you to address the issues of trust and bias in AI.

Download now to learn about:

  • Practical data quality, model accuracy, robustness, stability, and velocity dimensions of trusted AI
  • Compliance, security, humility, and governance considerations, vital for operational trust in AI
  • Transparency, bias and fairness, and privacy implications for AI systems striving to deliver unparalleled levels of trust aligned with your organizational values
  • Trust is not an option, it is a requirement. Building AI systems without trust tenets invites disaster, for your organization, your own personal brand and for stakeholders impacted by the AI system.
    Ted Kwartler
    Ted Kwartler

    VP of Trusted AI, DataRobot