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Transparent, explainable, and accountable AI for robotics.

Sandra Wachter1, Brent Mittelstadt2,3,4, Luciano Floridi2,3

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Summary
This summary is machine-generated.

Creating fair and accountable artificial intelligence (AI) and robotics requires precise regulation. Better methods are needed to certify, explain, and audit complex, inscrutable AI systems for transparency and trust.

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Area of Science:

  • Artificial Intelligence and Robotics
  • AI Ethics and Governance

Background:

  • The increasing complexity of AI and robotics systems presents challenges in ensuring fairness and accountability.
  • Inscrutable AI systems lack transparency, making it difficult to understand their decision-making processes.

Purpose of the Study:

  • To highlight the necessity of precise regulation for fair and accountable AI and robotics.
  • To identify the need for improved methods for certifying, explaining, and auditing AI systems.

Main Methods:

  • This study is primarily a conceptual analysis and review of current challenges in AI governance.
  • It synthesizes existing literature on AI ethics, explainability, and auditability.

Main Results:

  • Current regulatory frameworks are insufficient to address the complexities of modern AI and robotics.
  • There is a significant gap in methodologies for certifying, explaining, and auditing inscrutable AI systems.

Conclusions:

  • Precise regulation is essential for the development of fair and accountable AI and robotics.
  • Advancements in certification, explainability, and auditability methods are crucial for building trustworthy AI systems.