AI Governance and Ethics Quiz

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Questions and Answers

Which of the following is NOT a core principle of AI Ethics BOK, as presented in the text?

Internal governance.

Transparency, fairness, and explainability.

Human-centricity.

Sustainability and environmental impact. (correct)

What is the primary objective of the AI Model Governance Framework (sg)?

To standardize AI technologies across different industries.

To promote the development of specific AI algorithms.

To ensure the ethical and responsible use of AI by organizations. (correct)

To create a uniform set of regulations for AI development.

Which of the following is NOT a key feature of the AI Model Governance Framework?

It is suitable for organizations of all sizes and business models.

It can be applied across various industries, irrespective of the specific sector.

It is tailored to specific technologies and systems, ensuring maximum compatibility. (correct)

It is applicable to all AI methods, regardless of the specific algorithm.

What is the main purpose of "Internal Governance" within the AI Ethics BOK?

Establishing processes for managing risks and responsibilities associated with AI usage. (C) Signup and view all the answers

How does the AI Model Governance Framework contribute to building confidence in AI?

By promoting transparency, fairness, and responsible usage of AI. (C) Signup and view all the answers

Which of the following is a key element of "Human-centricity" in the AI Ethics BOK?

Ensuring AI systems prioritize human safety and well-being. (D) Signup and view all the answers

What is the primary goal of "Operations Management" within the AI Ethics BOK?

Ensuring the quality, reliability, and ethical use of AI models. (C) Signup and view all the answers

Which of the following is NOT a benefit of the AI Model Governance Framework being applicable across industries?

Increased standardization and consistency in AI development across different sectors. (A) Signup and view all the answers

What is the importance of "Stakeholder Communications" within the AI Ethics BOK?

To promote public awareness and understanding of AI technologies. (A) Signup and view all the answers

How does the AI Model Governance Framework differ from other existing frameworks for AI governance?

It is not specifically tied to specific technologies, making it more widely applicable. (C) Signup and view all the answers

Which of the following examples represent a scenario where "Human in the loop" is most appropriate for AI implementation?

A medical imaging system uses AI to analyze scans and provide support for diagnoses. (B) Signup and view all the answers

Which of the following is NOT a principle of "Human-centric" AI as mentioned in the text?

Maximizing AI efficiency even if it compromises human control. (D) Signup and view all the answers

Based on the text, which of the following actions helps organizations minimize bias in AI systems?

Ensuring data used to train AI models is diverse and representative. (D) Signup and view all the answers

Which of the following best describes the concept of "data lineage" as it relates to AI?

The recording and tracking of data from its origin to its final use in AI systems. (C) Signup and view all the answers

Which of the following actions would be considered a "Human over the loop" AI implementation?

A pilot monitors and intervenes in an aircraft's flight system powered by AI. (A) Signup and view all the answers

Which of the following best describes the relationship between "Human in the loop" and "Human out of the loop" approaches to AI implementation?

They represent different levels of human involvement based on the complexity and risk of the task. (B) Signup and view all the answers

Based on the text, which of the following is a primary goal of "Stakeholder Interaction and Communication" in AI implementations?

Ensuring transparency and user trust in AI solutions. (A) Signup and view all the answers

Which of the following is a key consideration when developing effective AI policies for an organization?

Defining clear roles and responsibilities for managing and using AI systems within the organization. (B) Signup and view all the answers

Based on the text, which of the following is a primary advantage of using a "Risk Impact Matrix" for AI implementation?

It provides a framework for assessing the potential harm and likelihood of risks associated with AI systems. (A) Signup and view all the answers

Which of the following statements best reflects the concept of "balancing control and efficiency" in human-centric AI implementations?

Human oversight is crucial in AI systems to ensure safety and accountability. (C) Signup and view all the answers

What is a primary goal of AI governance?

To align AI design with organizational goals (C) Signup and view all the answers

Which of the following best describes the concept of explainability in AI?

Providing transparency on how AI makes decisions (C) Signup and view all the answers

What is a significant risk associated with biased AI systems?

They can lead to unfair decisions favoring certain groups (B) Signup and view all the answers

What does the term 'misclassification' refer to in AI?

Incorrect decisions made by AI due to contextual discrepancies (D) Signup and view all the answers

What role does AI ethics play in decision-making?

To guide AI in making decisions while retaining human oversight (C) Signup and view all the answers

How can AI systems be mitigated against the risk of unexplainability?

By implementing human oversight to verify AI decisions (D) Signup and view all the answers

What is a key factor that contributes to bias in AI outcomes?

Insufficient representation in training data (D) Signup and view all the answers

Which principle is a guiding element of the AI Body of Knowledge (BoK)?

Informing about best practices in AI usage (B) Signup and view all the answers

What is the ultimate goal of ensuring trustworthy AI?

To promote responsibility and ethical conduct in AI operations (D) Signup and view all the answers

What is necessary to enhance the acceptance of AI among users?

Demonstrating how AI reaches its conclusions (D) Signup and view all the answers

What level of human involvement is necessary when deploying an automated system that can potentially cause irreversible harm?

Manual human operation is essential at all times. (B) Signup and view all the answers

Which of the following principles emphasizes that AI should enhance human skills rather than limit human freedom?

Respect for human autonomy (D) Signup and view all the answers

Which ethical principle requires AI to protect vulnerable populations and ensure safety from physical and mental harm?

Prevention of harm (C) Signup and view all the answers

What is the primary purpose of data lineage in AI governance?

To track the origin and movement of data. (B) Signup and view all the answers

Which of the following factors does NOT pertain to data quality?

Sentiment (A) Signup and view all the answers

What risk could arise from fully automating an AI system without human oversight?

Potential for recommending inappropriate items. (B) Signup and view all the answers

Which of the following is a requirement for AI system implementations that ensures accuracy and reliability?

Technical robustness and safety (D) Signup and view all the answers

In the context of AI ethics, what does explicability refer to?

The clarity of AI's purpose and capabilities. (D) Signup and view all the answers

Which of the following describes measurement bias in data?

Data influenced by a biased device or method. (C) Signup and view all the answers

What is the main purpose of involving diverse teams in AI design?

To prevent bias and foster inclusivity. (B) Signup and view all the answers

Study Notes

AI Governance

AI and machine learning (ML) systems make decisions faster than humans
AI should be designed to support organizational goals
AI must meet ethical standards and not break rules
Trustworthy AI works responsibly and ethically
AI is part of information technology (IT), but it's evolving rapidly and less clearly defined than other branches of IT
AI is treated like an emerging technology due to risks and a lack of established best practices

Need for AI Ethics

AI will take over some decision-making from humans
AI systems need to make ethical decisions
AI ethics prevents unfair AI decisions and requires humans to retain control as AI systems make more decisions
AI systems must not be allowed to act on their own
Ensure AI systems do not cause harm
Keep AI human-centered without limiting benefits
Ensure AI outcomes stay within appropriate boundaries, such as healthcare, law, and engineering

AI Risks

Unexplainability: Difficult to understand how AI makes decisions; cannot explain its decision-making process
- Explainability:
  - Shows how AI makes decisions
  - Builds trust in system performance
  - Helps users accept AI and trust its performance
  - Reduces the risk of unexpected behavior
- Mitigation:
  - Spend more to understand AI systems
  - Implement human oversight to check AI decisions
Bias/discrimination: AI results can favor specific groups (gender, race, etc.) due to biased training data
- Causes: Biased training data
- Fix: Use balanced training data with equal representation of groups

AI Ethics (Body of Knowledge)

Developed by SCS to guide AI use
Designed for AI solution providers, businesses, and consumers
Guiding principles of AI to promote trust:
- Transparent, fair, and explainable
- Human-centric, protecting well-being and safety

AI Ethics BOK Approach to AI

Internal governance: Implementing structures for accountability for AI decisions and management of risks
Human-centricity: Setting acceptable risk levels for AI usage; deciding how much human involvement is needed in AI decisions
Operations management: Building, choosing, and maintaining AI models for data management and ensuring auditability
Stakeholder communications: Effectively communicating with stakeholders

AI Model Governance Framework

Practical guidance for organizations to address ethical and governance issues in AI usage
Not limited to specific algorithms or technologies; applicable to all AI methods
Applicable across industries and organization sizes
Objective: Build confidence in responsible AI usage and gain stakeholder trust
Guiding principles: ensure decision-making is explainable, transparent, and fair; human-centric AI
Internal Governance:
- Define roles and responsibilities for managing AI systems
- Assign specific responsibilities for AI usage
- Manage AI risks (including in risk management systems)
- Align with ethical standards
Operations Management:
- Minimise bias
- Balance needs and obligations
- Focus on data quality
- Define data origin, use, and transformation (data lineage and provenance)
Stakeholder Interaction and Communication:
- Create and share policies to ensure stakeholder awareness
- Initiate efforts to encourage feedback and improve communication with stakeholders
- Provide tailored communication styles for different audiences
- Implement opt-out options, as appropriate

Human Involvement Model

Depending on the context, AI may be used in tandem with human input or operate independently.
Human in the loop: (e.g., medical diagnosis, operational tech) Human oversight essential
Human out of the loop: (e.g., personal assistants) Automatic AI operation; limited human involvement, low impact
Human over the loop: AI operates, but human intervention may be required

Risk Impact Matrix

Assesses risk based on potential harm, reversibility, and likelihood
Defines the level of human involvement in the AI system
Green: Human out of the loop (low risk, minimal harm)
Yellow: Human over the loop (some risk, potential harm)
Orange: Human in the loop (moderate risk, higher harm needs human intervention)
Dark red/red: Human involvement is inadvisable; high impact, irreversible harm; human intervention needed

Ethical Principles and Requirements

Respect for human autonomy: Maintain human freedom and enhance skills
Prevention of harm: Prevent physical and mental harm to humans and the environment
Fairness: Ensure fair distribution of benefits and costs (including in the case of existing inequalities)
Explicability: Understanding AI's decisions and capabilities
Human agency and oversight: Respect human rights and allow control over AI systems
Technical security and safety: Secure and reliable AI functionalities
Privacy and data governance: Protection of data and guarantees of quality
Transparency: Clear, explainable AI to everyone
Diversity, non-discrimination, fairness: Avoiding biases in favor of specific groups
Societal/environmental well-being: Promotion of sustainability
Accountability: Transparent processes, reducing harm, and offering solutions to problems

Data Governance & Bias

Data bias:
- Selection bias: Data used may not be representative (incl. potentially biased sampling).
- Measurement bias: Data may be influenced by the measuring device and result in biased results (favoring some results over others).
Training, testing, and validation: Using separate data sets—avoid overfitting
Updating: Regular checks on data for accuracy, quality, and relevance. New data can help improve existing systems.

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Description

Test your understanding of AI governance, its ethical implications, and the associated risks. This quiz covers critical aspects like decision-making, accountability, and the importance of ethical standards in AI systems. Explore how AI can align with organizational goals while safeguarding against potential harms.