| Vol-3087 urn:nbn:de:0074-3087-8 Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# SafeAI 2022
Artificial Intelligence Safety 2022

### Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI 2022)
co-located with the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI2022)

### Virtual, February, 2022.

Edited by

### Gabriel Pedroza *
José Hernández-Orallo **
Xin Cynthia Chen ***
Xiaowei Huang ****
Huáscar Espinoza *****
Mauricio Castillo-Effen ******
John McDermid *******
Richard Mallah ********
Seán Ó hÉigeartaigh *********

* Commissariat à l´Energie Atomique, France
** Universitat Politècnica de València, Spain
*** University of Hong Kong, China
**** University of Liverpool, United Kingdom
***** ECSEL JU, Belgium
****** Lockheed Martin, USA
******* University of York, United Kingdom
******** Future of Life Institute, USA
********* University of Cambridge, United Kingdom

## Table of Contents

- Preface

### Session 1: Bias, Fairness and Value Alignment

- The Problem of Behaviour and Preference Manipulation in AI Systems
  Hal Ashton, Matija Franklin
- IFBiD: Inference-Free Bias Detection
  Ignacio Serna, Daniel DeAlcala, Aythami Morales Moreno, Julian Fierrez, Javier Ortega-Garcia
- Blackbox Post-Processing for Multiclass Fairness
  Preston Putzel, Scott Lee

### Session 2: Interpretability and Accountability

- A Gray Box Model for Characterizing Driver Behavior
  Soyeon Jung, Ransalu Senanayake, Mykel Kochenderfer
- Defining and Identifying the Legal Culpability of Side Effects using Causal Graphs
  Hal Ashton

### Session 3: Robustness and Uncertainty

- Efficient Adversarial Sequence Generation for RNN with Symbolic Weighted Finite Automata
  Mingjun Ma, Dehui Du, Yuanhao Liu, Yanyun Wang, Yiyang Li
- A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models
  Pascal Gerber, Lisa Jöckel, Michael Kläs
- Quantifying the Importance of Latent Features in Neural Networks
  Amany Alshareef, Nicolas Berthier, Sven Schewe, Xiaowei Huang
- Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
  Deebul Nair, Nico Hochgeschwender, Miguel Olivares-Mendez

### Session 4: Safe Reinforcement Learning

- Reinforcement Learning With Imperfect Safety Constraints
  Jin Woo Ro, Gerald Lüttgen, Diedrich Wolter
- Do Androids Dream of Electric Fences? Safety-Aware Reinforcement Learning with Latent Shielding
  Peter He, Borja Leon, Francesco Belardinelli
- HiSaRL: A Hierarchical Framework for Safe Reinforcement Learning
  Zikang Xiong, Ishika Agarwal, Suresh Jagannathan
- A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning
  Mathieu Godbout, Maxime Heuillet, Sharath Chandra Raparthy, Rupali Bhati, Audrey Durand

### Session 5: AI Testing and Assessment

- Beyond Test Accuracy: The Effects of Model Compression on CNNs
  Adrian Schwaiger, Kristian Schwienbacher, Karsten Roscher
- Using Adaptive Stress Testing to Identify Paths to Ethical Dilemmas in Autonomous Systems
  Ann-Katrin Reuel, Mark Koren, Anthony Corso, Mykel J. Kochenderfer

### Poster Papers

- The Dilemma Between Data Transformations and Adversarial Robustness for Time Series Application Systems
  Sheila Alemany, Niki Pissinou
- Interpretable Local Tree Surrogate Policies
  John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer
- Oases of Cooperation: An Empirical Evaluation of Reinforcement Learning in the Iterated Prisoner’s Dilemma
  Peter Barnett, John Burden
- Leveraging Multi-task Learning for Umambiguous and Flexible Deep Neural Network Watermarking
  Fangqi Li, Lei Yang, Shilin Wang, Alan Wee-Chung Liew
- Human-in-the-loop Learning for Safe Exploration through Anomaly Prediction and Intervention
  Prajit T Rajendran, Huascar Espinoza, Agnes Delaborde, Chokri Mraidha
- Safety Aware Reinforcement Learning by Identifying Comprehensible Constraints in Expert Demonstrations
  Leopold Müller, Lars Böcking, Michael Färber
- Combining Data-Driven and Knowledge-Based AI Paradigms for Engineering AI-Based Safety-Critical Systems
  Juliette Mattioli, Gabriel Pedroza, Souhaiel Khalfaoui, Bertrand Leroy
- Is it all a cluster game? – Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space
  Poulami Sinhamahapatra, Rajat Koner, Karsten Roscher, Stephan Günnemann
- A Practical Overview of Safety Concerns and Mitigation Methods for Visual Deep Learning Algorithms
  Saeed Bakhshi Germi, Esa Rahtu
- Comparing Vision Transformers and Convolutional Nets for Safety Critical Systems
  Michal Filipiuk, Vasu Singh

### Special Sessions

- EnnCore: End-to-End Conceptual Guarding of Neural Architectures
  Edoardo Manino, Danilo Carvalho, Yi Dong, Julia Rozanova, Xidan Song, Mustafa Mustafa, Andre Freitas, Gavin Brown, Mikel Luján, Xiaowei Huang, Lucas Cordeiro
- The wall of safety for AI: approaches in the Confiance.ai program
  Bertrand Braunschweig, Rodolphe Gelin, François Terrier

2022-02-01: submitted by Xin Cynthia Chen, metadata incl. bibliographic data published under Creative Commons CC0
2022-02-15: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|