Transparent AI Exercises (Part 2)

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Question 1 of 10

1. Question
How does open source AI technology provide transparency? (select all that apply)
- The code is visible and available for inspection
- People you hire can know how it works and often already have experience using it
- They provide an open means for understanding ROI
- They provide alternatives to cloud-based AI approaches
- Others are able to add and modify the code
- Communities exist that can support, value add, and fix major issues
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Question 2 of 10

2. Question
When putting together your Trustworthy AI Framework, addressing disclosure and consent means addressing (select all that apply):
- When to disclose when a human is interacting with a bot when they are expecting to interact with a human
- When to disclose when a human is interacting with an AI system
- When to disclose when a human is interacting with a human when they are expecting to interact with a machine
- When to disclose when a human is interacting with a database
- When to disclose when a human is interacting with any automated system
- When to disclose when a human is interacting with government officials
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Question 3 of 10

3. Question
When addressing Data and configuration transparency, it’s important to have: (select all that apply)
- Complete view of all the data in the organization
- Understanding of the organizational chain of command
- Visibility into training data
- Methods and means of data selection
- Understanding of Configuration and parameter settings used
- Determination of algorithm selection
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Question 4 of 10

4. Question
When AI systems are informing significant decisions you need to consider the following: (select all that apply)
- When to have an opt-out mechanism if it impacts people’s lives
- When to provide alternative data sets
- When to have a feasible alternative to the use of any AI systems
- When to have a human in the loop
- When to require AI systems to be shut down
- When to require bias-free AI systems
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Question 5 of 10

5. Question
What are Model Cards? (Select the best answer)
- A method for determining which algorithm is the best to use for that given problem
- A method for creating a model repository that others at your organization can easily access
- A means for documenting details about a model, its application, methods of interaction, limitations, performance, and other considerations before use
- Approaches to mitigate AI system bias
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Question 6 of 10

6. Question
What is the Model Transparency Assessment? (Select the best answer)
- A way for providers of models to declare how open they are about sharing different aspects of the model and data to potential users or consumers of that model
- An approach for measuring algorithmic explainability
- A means to document what an AI model does and how to work with it
- A third-party organization that measures AI system bias and fairness
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Question 7 of 10

7. Question
What are the five axes to consider in the Model Transparency Assessment? (Select all that apply)
- Identification of data sources
- Model versioning approach and method
- Methods of data selection
- Choice of machine learning algorithm
- Identification and reduction of data set bias
- Algorithmic Explainability
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Question 8 of 10

8. Question
When addressing AI transparency your framework should address the following: (Select all that apply)
- What methods will you use to document and communicate model and data transparency internally?
- What methods will you use to communicate with external third-party governance groups?
- The cost of implementing AI transparency
- The difficulty of getting approvals for AI transparency from senior-level management
- How will you use model transparency methods to share or consume models and data from third-parties?
- How will you use model transparency methods to share or consume models internally?
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Question 9 of 10

9. Question
Which of the following are aspects of Consent in the context of AI systems? (select all that apply)
- Users should have the right to consent to the use of AI systems
- AI systems informing significant decisions should not attempt to make value judgements on people’s behalf without prior consent
- Provide a means for people to opt-out of the use of AI systems
- There should be a feasible alternative to the use of any AI systems
- Users should have a choice as to which data is used for an AI system
- AI systems informing significant decisions should have an opt-out mechanism if it impacts people’s lives
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Question 10 of 10

10. Question
What are reasons to measure bias in your AI systems?: (select all that apply)
- How do you know you’re effectively serving your audience?
- How are you avoiding potential legal liability?
- To determine what ROI an AI system can provide
- To limit the number or type of people who use an AI system
- How do you know how to fix any issues of overrepresentation or underrepresentation or misrepresentation?
- How will you prove your systems are trustworthy?
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Transparent AI Exercises (Part 2)

Transparent AI Exercises (Part 2)

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