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WAISE 2020 : 3rd International Workshop on Artificial Intelligence Safety Engineering

Lisbon, Portugal
Event Date: Sep 15, 2020 - Sep 15, 2020
Submission Deadline: May 11, 2020
Notification of Acceptance: May 29, 2020
Camera Ready Version Due : Jun 10, 2020

About

The WAISE workshop explores new ideas on safety engineering for AI-based systems, ethically aligned design, regulation and standards for AI-based systems. In particular, WAISE provides a forum for thematic presentations and in-depth discussions about safe AI architectures, bounded morality, ML safety, safe human-machine interaction and safety considerations in automated decision-making systems, in a way that makes AI-based systems more trustworthy, accountable and ethically aligned.

Call For Paper

Contributions are sought in (but are not limited to) the following topics:​

  • Regulating AI-based systems: safety standards and certification

  • Safety in AI-based system architectures: safety by design

  • Runtime AI safety monitoring and adaptation

  • Safe machine learning and meta-learning

  • Safety constraints and rules in decision-making systems

  • AI-based system predictability

  • Continuous Verification and Validation of safety properties

  • Avoiding negative side effects

  • Algorithmic bias and AI discrimination

  • Model-based engineering approaches to AI safety

  • Ethically aligned design of AI-based systems

  • Machine-readable representations of ethical principles and rules

  • Uncertainty in AI

  • Accountability, responsibility and liability of AI-based systems

  • AI safety risk assessment and reduction

  • Confidence, self-esteem and the distributional shift problem

  • Reward hacking and training corruption

  • Self-explanation, self-criticism and the transparency problem

  • Safety in the exploration vs exploitation dilemma

  • Simulation for safe exploration and training

  • Human-machine interaction safety

  • AI applied to safety engineering

  • Algorithmic bias and AI discrimination

  • AI safety education and awareness

  • Shared autonomy and human-autonomy teaming

  • AI safety regulation and education

  • Safety testing, verification and validation

  • Experiences in AI-based safety-critical systems, including industrial processes, health, automotive systems, robotics, critical infrastructures, among others

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