| Vol-3215 urn:nbn:de:0074-3215-4 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).

# AISafety 2022
Artificial Intelligence Safety 2022

### Proceedings of the Workshop on Artificial Intelligence Safety 2022 (AISafety 2022)
co-located with the Thirty-First International Joint Conference on Artificial Intelligence and the Twenty-Fifth European Conference on Artificial Intelligence (IJCAI-ECAI-2022)

### Vienna, Austria, July 24-25, 2022.

Edited by

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

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

## Table of Contents

- Preface

### Session 1: AI Ethics: Fairness, Bias, and Accountability

- Let it RAIN for Social Good
  Mattias Brännström, Andreas Theodorou, Virginia Dignum
- Accountability and Responsibility of Artificial Intelligence Decision-making Models in Indian Policy Landscape
  Palak Malhotra, Amita Misra
- Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression Recognition
  Iris Dominguez-Catena, Daniel Paternain, Mikel Galar

### Session 2: Short Presentations - Safety Assessment of AI-enabled systems

- A Hierarchical HAZOP-Like Safety Analysis for Learning-Enabled Systems
  Yi Qi, Philippa Ryan Conmy, Wei Huang, Xingyu Zhao, Xiaowei Huang
- Increasingly Autonomous CPS: Taming Emerging Behaviors from an Architectural Perspective
  Jerome Hugues, Daniela Cancila
- CAISAR: A platform for Characterizing Artificial Intelligence Safety and Robustness
  Julien Girard-Satabin, Michele Alberti, François Bobot, Zakaria Chihani, Augustin Lemesle

### Session 3: Machine Learning for Safety-critical AI

- Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection
  Patrick Feifel, Benedikt Franke, Arne Raulf, Friedhelm Schwenker, Frank Bonarens, Frank Köster
- Improvement of Rejection for AI Safety through Loss-Based Monitoring
  Daniel Scholz, Florian Hauer, Klaus Knobloch, Christian Mayr

### Session 4: Short Presentations - ML Robustness, Criticality and Uncertainty

- Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers
  Georg Siedel, Silvia Vock, Andrey Morozov, Stefan Voß
- Safety-aware Active Learning with Perceptual Ambiguity and Criticality Assessment
  Prajit T Rajendran, Guillaume Ollier, Huascar Espinoza, Morayo Adedjouma, Agnes Delaborde, Chokri Mraidha
- Understanding Adversarial Examples Through Deep Neural Network's Classification Boundary and Uncertainty Regions
  Juan Shu, Bowei Xi, Charles Kamhoua

### Session 5: AI Robustness, Generative Models and Adversarial Learning

- Leveraging generative models to characterize the failure conditions of image classifiers
  Adrien Le Coz, Stéphane Herbin, Faouzi Adjed
- Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection
  Svetlana Pavlitskaya, Bianca-Marina Codău, J. Marius Zöllner
- Privacy Safe Representation Learning via Frequency Filtering Encoder
  Jonghu Jeong, Minyong Cho, Philipp Benz, Jinwoo Hwang, Jeewook Kim, Seungkwan Lee, Tae-hoon Kim
- Benchmarking and deeper analysis of adversarial patch attack on object detectors
  Pol Labarbarie, Adrien Chan Hon Tong, Stéphane Herbin, Milad Leyli-Abadi

### Session 6: AI Accuracy, Diversity, Causality and Optimization

- The impact of averaging logits over probabilities on ensembles of neural networks
  Cedrique Rovile Njieutcheu Tassi, Jakob Gawlikowski, Auliya Unnisa Fitri, Rudolph Triebel
- Exploring Diversity in Neural Architectures for Safety
  Michał Filipiuk, Vasu Singh
- Constrained Policy Optimization for Controlled Contextual Bandit Exploration
  Mohammad Kachuee, Sungjin Lee
- A causal perspective on AI deception in games
  Francis Rhys Ward, Francesco Belardinelli, Francesca Toni

2022-08-02: submitted by Xin Cynthia Chen, metadata incl. bibliographic data published under Creative Commons CC0
2022-09-15: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|