10 Questions
What is a key benefit of making AI systems explainable?
It helps organizations comply with legal requirements and build trust with customers
What does the GDPR's "right to explanation" requirement specifically stipulate?
Users must be given information about how to challenge an AI system's decision
What is a limitation of the report on "Explaining AI in practice"?
It does not provide sample screen designs or user testing results
What is the purpose of the three reports mentioned in the text?
To provide guidelines for developing explainable AI systems
Which of the following is NOT mentioned in the text as a requirement for explanations of AI decisions?
Providing a technical breakdown of the AI model's architecture
Which level of governance is responsible for developing and implementing HCAI systems?
Software engineering teams
What does the text imply is necessary for bridging the gap between ethical principles of HCAI and practical steps?
Establishing governance structures at multiple levels
Which level of governance is NOT explicitly mentioned in the text as potentially providing comprehensive attention to HCAI systems?
Academic institutions
Based on the text, which of the following statements is true regarding decision-makers in the context of HCAI systems?
They need to take meaningful actions at various governance levels.
Which of the following sectors is NOT mentioned in the text as already applying comprehensive attention to technologies?
Information technology
Explore the arguments presented by Weld and Gagan Bansal from the University of Washington on the importance of explainability in machine learning, beyond just user understanding and legal requirements. Learn how explainability can enhance correctness, improve training data, adapt to evolving scenarios, empower users, and boost user acceptance.
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