What are the pillars of AI ethics?

Homework Help: Questions and Answers: What are the pillars of AI ethics?

What are the pillars of AI ethics?

a) Explainability, fairness, robustness, transparency, privacy
b) Environmental impact, equitable impact, ethical impact
c) Trust, efficiency, compliance
d) Awareness, governance, operationalization

Answer:

The pillars of AI ethics refer to the key principles and considerations that should guide the development and deployment of AI systems in an ethical and responsible manner. 

To solve the question of identifying the pillars of AI ethics, let’s examine each option and see which aligns best with commonly recognized ethical principles in AI.

Given Options: Step by Step Answering

a) Explainability, fairness, robustness, transparency, privacy

  • Explainability: Ensures that AI systems can be understood by humans, which is crucial for trust and accountability.
  • Fairness: Involves creating systems that do not discriminate and ensure equitable treatment.
  • Robustness: Refers to the reliability and security of AI systems, ensuring they operate safely under various conditions.
  • Transparency: Involves being open about how AI systems work and how decisions are made.
  • Privacy: Protects individuals’ data and ensures that AI systems do not violate privacy rights.
  • All these elements are widely recognized as foundational to AI ethics.

b) Environmental impact, equitable impact, ethical impact

  • Environmental impact: Refers to the ecological footprint of AI technologies.
  • Equitable impact: Relates to ensuring AI benefits are distributed fairly.
  • Ethical impact: Broadly covers the moral implications of AI technologies.
  • While these are important considerations, but they are not typically described as the core pillars of AI ethics.

c) Trust, efficiency, compliance

  • Trust: Important for adoption, but more of an outcome than a specific pillar.
  • Efficiency: Refers to performance but is not directly related to ethical considerations.
  • Compliance: Involves adhering to regulations but is more about legal adherence than ethical principles.
  • This option lacks some of the key ethical principles.

d) Awareness, governance, operationalization

  • Awareness: Involves understanding AI’s impact but is not a core pillar.
  • Governance: Important for oversight but more related to policy than ethics.
  • Operationalization: Refers to implementing AI, not a specific ethical principle.
  • This set focuses more on management and implementation rather than ethical foundations.

Final Answer

Based on the above analysis, the correct answer is:

a) Explainability, fairness, robustness, transparency, privacy

The pillars of AI ethics are best captured by option a) Explainability, fairness, robustness, transparency, privacy. These elements are crucial for ensuring AI technologies are developed and used in an ethically responsible manner.

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