AI Ethics and Responsibilities Quiz

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Questions and Answers

What is one of the main responsibilities of AI actors regarding traceability?

Avoid systematic risk management approaches

Limit cooperation between AI stakeholders

Ensure complete secrecy of datasets and processes

Enable analysis of AI system outputs and responses (correct)

Which of the following is NOT identified as a risk related to AI systems?

Harmful bias

Human rights violations

Economic growth opportunities (correct)

Privacy concerns

What principle emphasizes the need for transparency and explainability in AI systems?

Accountability (correct)

Robustness and security

Data privacy

Safe and effective systems

What is the main mission of the Office of Science and Technology Policy (OSTP)?

Advise the U.S. government on science and technology Signup and view all the answers

Which of the following principles is included in the blueprint for an AI Bill of Rights?

Algorithmic discrimination protections Signup and view all the answers

Which principle emphasizes the need for transparency in AI systems?

Transparency and explainability Signup and view all the answers

What is a key component of ensuring accountability in AI systems?

Implementing human oversight Signup and view all the answers

Which of the following best describes the role of human agency in AI implementation?

To address risks from misuse of AI Signup and view all the answers

What should AI actors provide to stakeholders interacting with AI systems?

Plain and easy-to-understand information Signup and view all the answers

According to the principles, how should AI systems be designed to ensure safety?

To function properly under all circumstances Signup and view all the answers

What is the purpose of implementing safeguards in AI systems?

To ensure appropriate functionality and mitigate risks Signup and view all the answers

What should be prioritized when addressing misinformation and disinformation related to AI?

Ensuring freedom of expression while respecting rights Signup and view all the answers

What is essential for stakeholders to understand the output of an AI system?

Plain information on decision-making factors Signup and view all the answers

What is the primary goal of accountability in AI systems?

To promote ethical and transparent system operations Signup and view all the answers

Which principle emphasizes the ability to question AI system outputs?

Contestability Signup and view all the answers

What does explainability in AI primarily promote?

Transparency and trust Signup and view all the answers

Which of the following is a key consideration in ensuring fairness within AI systems?

Preventing adverse impact on sensitive characteristics Signup and view all the answers

What is meant by robustness in AI systems?

The capacity to perform reliably under various conditions Signup and view all the answers

Which principle focuses on minimizing potential harm caused by AI systems?

Safety Signup and view all the answers

What is the essence of transparency in AI systems?

The availability of information regarding AI usage and functioning Signup and view all the answers

Which value is NOT included in the OECD AI Principles?

Profit maximization Signup and view all the answers

The principle of trustworthy AI aligns closely with which other term?

Responsible AI Signup and view all the answers

What is the main focus of the first OECD AI principle?

Inclusive growth and well-being Signup and view all the answers

What role does UNESCO play in international relations?

Promotes world peace and security through cooperation in various fields Signup and view all the answers

Which of the following is NOT a value promoted by UNESCO?

Environmental destruction for economic growth Signup and view all the answers

Which principle emphasizes the importance of not causing harm in actions taken?

Proportionality and Do No Harm Signup and view all the answers

What is a key aspect of the principle of awareness and literacy?

Educating societies about technology and its implications Signup and view all the answers

Which of the following best describes the concept of multi-stakeholder adaptive governance?

Inclusive collaboration involving various stakeholders Signup and view all the answers

What is the function of the Asilomar AI Principles?

To provide guidelines on the ethical use and development of AI Signup and view all the answers

How many total principles are outlined in the Asilomar AI Principles?

23 Signup and view all the answers

Which principle focuses on the need for human oversight in AI management?

Human oversight and determination Signup and view all the answers

What was the purpose of the 2017 Asilomar Conference on Beneficial AI?

To discuss the ethical implications of AI Signup and view all the answers

Which of the following is NOT one of the Asilomar Principles related to ethics and values?

Economic empowerment Signup and view all the answers

How many categories are the Asilomar Principles divided into?

Three Signup and view all the answers

What does the principle of 'failure transparency' emphasize?

Understanding the reasons behind system failures Signup and view all the answers

Which organization is responsible for organizing the Asilomar Conference on Beneficial AI?

Future of Life Institute Signup and view all the answers

What is one of the concerns related to the AI arms race as per the Asilomar Principles?

The potential for a lack of accountability in military use Signup and view all the answers

What category includes principles related to long-term AI concerns?

Longer-term issues Signup and view all the answers

Which of the following statements is true regarding the IEEE?

It was formed in 1963 and is the largest technical organization for engineering. Signup and view all the answers

What is one of the primary roles of the European Commission within the EU?

Proposing new legislation Signup and view all the answers

Which of the following is NOT a requirement of Trustworthy AI?

Low-cost implementation Signup and view all the answers

Which principle focuses on the need for justice in AI outcomes?

Non-discrimination Signup and view all the answers

What harm to individuals can arise from the use of AI in hiring practices?

Bias against certain demographics Signup and view all the answers

Which of the following best describes 'disinformation'?

Deliberately deceptive or misleading information Signup and view all the answers

What is a common risk associated with AI technologies that operate without oversight?

Lethal autonomous weapons Signup and view all the answers

In the context of AI, what does data governance primarily focus on?

Overall management of data throughout its lifecycle Signup and view all the answers

What is a significant consequence of 'deepfakes' in society?

Undermining trust in institutions Signup and view all the answers

What is one potential economic harm caused by AI?

Job displacement due to automation Signup and view all the answers

Which of the following roles focuses on ensuring that AI systems align with legal standards?

Legal and compliance Signup and view all the answers

Which type of algorithm demonstrates a high false positive rate, particularly affecting marginalized communities?

Predictive policing algorithms Signup and view all the answers

What foundational control involves implementing policies to address risks associated with AI?

Developing organization-specific principles Signup and view all the answers

How can AI contribute to societal harms related to misinformation?

Creating echo chambers of ideologically similar content Signup and view all the answers

Which aspect of AI management requires cross-functional teams throughout the AI lifecycle?

Equitable design Signup and view all the answers

Study Notes

Fair Information Practices (FIPs)

Guidelines for managing data with privacy, security, and fairness.
Aims to handle data using ethical principles.

Lecture Topics

Disambiguation: Clarifying different terms related to FIPs (Fair Information Practices).
What are the FIPs? Defining FIPs, including OECD Guidelines (1980) and global interpretations.
History of the FIPs: U.S. Department of Health, Education, and Welfare (HEW) Report (1973), and its five principles.
Common Principles: Key concepts like access/individual participation, purpose specification, data minimization, data quality, safeguards/security, notice/openness, accountability, and use limitation.

Mnemonic Device

A memory aid using a series of words to help recall FIPs-related topics.

Access/Individual Participation

Data subjects have the right to access (and amend) their personally identifiable information (PII).
Data should be collected directly from the data subject, not from secondary or third parties.

Purpose Specification

The purpose for collecting data should be explicitly defined (e.g., why is the data being gathered?).

Data Minimization

Collect only the necessary data.
Retain data only for the duration required.

Data Quality/Relevance

Data should be accurate, complete, and up-to-date.
Data collected should be relevant to the specified purpose.

Safeguards/Security

Implement measures (administrative, technical, physical) to protect data security.

Notice/Openness

Provide advance notice regarding data collection practices.
Policies and procedures should be transparent.

Accountability

Organizations are held responsible for their policies and procedures.

Use Limitation

Collected data should only be used for the intended purposes.
No secondary use of data for different aims.

OECD AI Principles

Created to direct AI development in a trustworthy manner.
Principles cover inclusive growth, human rights, transparency, robustness, safety and security, and accountability.

AI Principle #1

Stresses the importance of inclusive growth, sustainable development, and well-being.
Underscores the need for trustworthy AI to contribute positively to people and the planet.

AI Principle #2

Emphasizes respecting human rights, democratic values, fairness, and privacy.
States that AI actors should adhere to the rule of law, human rights, democracy, and human-centered values throughout the AI system lifecycle.
Mechanisms for addressing risks related to inappropriate use, misuse, or unintended consequences should be implemented.

AI Principle #3

Focuses on the importance of transparency and explainability in AI systems.
Emphasizes that AI actors should foster a general understanding of how Al systems work and provide information related to interactions, sources of data, and decision-making processes.

AI Principle #4

Highlights the need for robustness, security, and safety in AI systems.
Maintains that appropriate mechanisms should be developed and implemented to protect from misuse and unintended consequences.
Provides a framework for bolstering data integrity while respecting freedom of expression.

AI Principle #5

Addresses accountability in the entire Al lifecycle, covering traceability of processes and decisions made during Al system development.
Emphasizes comprehensive risk assessments.
Sets out a systematic risk management and ethical conduct framework for AI actors.

Asilomar AI Principles

Principles covering research, ethics and values, and longer-term issues, with a focus on safety, responsibility, human values, personal privacy, etc.

IEEE Global Initiative on Ethics and Autonomous and Intelligent Systems (A/IS)

Aims to articulate high-level ethical considerations relating to autonomous and intelligent systems.
Objectives to prioritize benefits to humanity and the natural environment and to mitigate risks and negative impacts.
General principles cover human rights, well-being, accountability, transparency, and awareness of potential misuse.

CNIL AI Action Plan

Policy put together by the French Data Protection Authority (CNIL) highlighting four key objectives: understanding AI's impact on people, respecting personal data, supporting innovation, and ensuring auditing and controls.

Ethics Guidelines for Trustworthy Al by the European Commission High-Level Expert Group on Al

Guidelines set out 7 requirements for trustworhty Al, including human oversight, technical robustness, privacy, diversity, fairness, societal well-being, and accountability.

Harms to Individuals

General harms like civil rights violations or economic inequality.
Specific harms in employment, housing, education, and credit systems.
Privacy harms like data aggregation, inference from data, misuse of data.
Economic harms like job displacement or biased opportunities.

Harms to Society

Harm to the democratic process and trust in institutions due to technological biases.
Impacts relating to access to public services(education, healthcare) and employment.
Negative consequences from misinformation and disinformation spread via AI.
Harms (e.g., profiling) related to tracking and predicting behavior.

Harms to Groups and Ecosystems

Impacts affecting civil rights, racial and socioeconomic divides, and discrimination of specific groups.
Environmental effects such as natural resource depletion and the negative environmental impacts of AI technology.
The importance of considering how AI technologies can be leveraged to enhance efforts promoting sustainability, well-being and positive development for individuals, groups and ecosystems.

Types of Bias

Algorithmic: Systematic and repeatable errors leading to unfair outcomes.
Computational: Systematic errors or deviations from a true value of prediction.
Cognitive: Distorted thinking and inaccurate judgments.
Societal: Systemic prejudice, favoritism, or discrimination.
Implicit: Unconscious bias toward a social group.
Sampling: When a data sample doesn't reflect the diversity of a population.
Temporal: When a model's performance isn't consistent across different time periods.
Overfitting: When a model is excessively tailored to training data, which reduces its generalization ability.
Underfitting: When a model is under-prepared to handle training data, which results in mediocre performance.
Edge cases/outliers: Data fall outside the boundaries of the training data and can cause issues.
Noise: Data that negatively impacts ML models by confounding outcomes.

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Description

Test your knowledge on the ethical responsibilities and principles related to artificial intelligence. This quiz covers traceability, risks in AI systems, and key initiatives such as the AI Bill of Rights. Explore the important role of organizations like the OSTP in promoting transparency and explainability in AI technology.