The 2021 ACAI School will take place on 11-14 October 2021.

We are going to use different locations all very close to each other. This allows us to keep up with the maximum occupancy restrictions:
• 3IT, Salzufer 6, Entrance: Otto-Dibelius-Strasse
• Forum Digital Technologies (FDT) // CINIQ Center: Salzufer 6 (main venue), 10587 Berlin ( Entrance Otto-Dibelius-Straße);
• Loft am Salzufer: Salzufer 13-14, 10587 Berlin 
• Hörsaal HHI, Fraunhofer Institute for Telecommunications (HHI): Einsteinufer 37, 10587 Berlin (across the bridge)

There will be a possibility to participate in the School's activities online.

According to the current regulations in Germany associated with the COVID-19, we are restricted to a maximum of 60 students attending in person. The format of the event is subject to the COVID-19 regulations at the time of the School.

The program will be updated regularly. (Download the program)

European Association for Artificial Intelligence

Cognitive Vision: On Deep Semantics for Explainable Visuospatial Computing, Mehul Bhatt, Örebro University - CoDesign Lab EU; Jakob Suchan, University of Bremen
(see Tutorial Outline)

Ethics and AI: An Interdisciplinary Approach, Guido Boella, Università di Torino; Maurizio Mori, Università di Torino
(see Tutorial Outline)

Children and the Planet - The Ethics and Metrics of "Successful" AI, John Havens, IEEE; Gabrielle Aruta, Filo Sofi Arts
(see Tutorial Outline)

Mythical Ethical Principles for AI and How to Operationalise Them, Marija Slavkovik, University of Bergen
(see Tutorial Outline)

Operationalising AI Ethics: Conducting Socio-Technical Assessment, Andreas Theodorou, Umeå University & VeRAI AB; Virginia Dignum, Umeå University & VeRAI AB
(see Tutorial Outline)

Explainable Machine Learning for Trustworthy AI, Fosca Giannotti, CNR; Riccardo Guidotti, University of Pisa
(see Tutorial Outline)

Why and How Should We Explain in AI?, Stefan Buijsman, TU Delft
(see Tutorial Outline)

Interactive Robot Learning, Mohamed Chetouani, Sorbonne Université
(see Tutorial Outline)

Multimodal Perception and Interaction with Transformers, Francois Yvon, Univ Paris Saclay, James Crowley, INRIA and Grenoble Institut Polytechnique
(see Tutorial Outline)

Argumentation in AI (Argumentation 1), Bettina Fazzinga, ICAR-CNR
(see Tutorial Outline)

Computational Argumentation and Cognitive AI (Argumentation 2), Emma Dietz, Airbus Central R&T; Antonis Kakas, University of Cyprus; Loizos Michael, Open University of Cyprus
(see Tutorial Outline)

Social Simulation for Policy Making, Frank Dignum, Umeå University; Loïs Vanhée, Umeå University; Fabian Lorig, Malmö University
(see Tutorial Outline)

Social Artificial Intelligence, Dino Pedreschi, University of Pisa; Frank Dignum, Umeå University
(see Tutorial Outline)

Introduction to Intelligent User Interfaces (UIs), Albrecht Schmidt, LMU Munich; Sven Mayer, LMU Munich; Daniel Buschek, University of Bayreuth
(see Tutorial Outline)

Machine Learning With Neural Networks, James Crowley, INRIA and Grenoble Institut Polytechnique
(see Tutorial Outline)

Deep Learning Methods for Multimodal Human Activity Recognition, Paul Lukowicz, DFKI/TU Kaiserslautern

Learning and Reasoning with Logic Tensor Networks, Luciano Serafini, Fondazione Bruno Kessler

Learning Narrative Frameworks From Multi-Modal Inputs, Luc Steels, Universitat Pompeu Fabra Barcelona
(see Tutorial Outline)

Law for Computer Scientists, Mireille Hildebrandt, Vrije Universiteit Brussel; Arno De Bois, Vrije Universiteit Brussel
(see Tutorial Outline)

Writing Science Fiction as An Inspiration for AI Research and Ethics Dissemination, Carme Torras, UPC
(see Tutorial Outline)

European Association for Artificial Intelligence

Yoshua Bengio, MILA, Quebec

Yoshua Bengio is recognized worldwide as one of the leading experts in artificial intelligence, Yoshua Bengio is most known for his pioneering work in deep learning, earning him the 2018 A.M. Turing Award, “the Nobel Prize of Computing,” with Geoffrey Hinton and Yann LeCun. He is a Full Professor at Université de Montréal, and the Founder and Scientific Director of Mila – Quebec AI Institute. He co-directs the CIFAR Learning in Machines & Brains program as Senior Fellow and acts as Scientific Director of IVADO. In 2019, he was awarded the prestigious Killam Prize and in 2021, became the second most cited computer scientist in the world. He is a Fellow of both the Royal Society of London and Canada and Officer of the Order of Canada. Concerned about the social impact of AI and the objective that AI benefits all, he actively contributed to the Montreal Declaration for the Responsible Development of Artificial Intelligence.

Kate Crawford

Kate Crawford, Professor, is a leading international scholar of the social and political implications of artificial intelligence. Her work focuses on understanding large-scale data systems in the wider contexts of history, politics, labor, and the environment. She is a Research Professor of Communication and STS at USC Annenberg, a Senior Principal Researcher at Microsoft Research New York, and an Honorary Professor at the University of Sydney. She is the inaugural Visiting Chair for AI and Justice at the École Normale Supérieure in Paris, where she co-leads the international working group on the Foundations of Machine Learning. Over her twenty year research career, she has also produced groundbreaking creative collaborations and visual investigations. Her project Anatomy of an AI System with Vladan Joler won the Beazley Design of the Year Award, and is in the permanent collection of the Museum of Modern Art in New York and the V&A in London. Her collaboration with the artist Trevor Paglen produced Training Humans – the first major exhibition of the images used to train AI systems. Their investigative project, Excavating AI, won the Ayrton Prize from the British Society for the History of Science. Crawford's latest book, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (Yale University Press) has been described as “a fascinating history of data” by the New Yorker, a “timely and urgent contribution” by Science. and named one of the best books on technology in 2021 by the Financial Times.

Yvonne Rogers, UCLIC - UCL Interaction Centre

Yvonne Rogers is a Professor of Interaction Design, the director of UCLIC and a deputy head of the Computer Science department at University College London. Her research interests are in the areas of interaction design, human-computer interaction and ubiquitous computing. A central theme of her work is concerned with designing interactive technologies that augment humans. The current focus of her research is on human-data interaction and human-centered AI. Central to her work is a critical stance towards how visions, theories and frameworks shape the fields of HCI, cognitive science and Ubicomp. She has been instrumental in promulgating new theories (e.g., external cognition), alternative methodologies (e.g., in the wild studies) and far-reaching research agendas (e.g., "Being Human: HCI in 2020"). She has also published two monographs "HCI Theory: Classical, Modern and Contemporary." and "Research in the Wild." with Paul Marshall. She is a fellow of the ACM, BCS and the ACM CHI Academy. 

Ben Shneiderman, University of Maryland

Ben Shneiderman is an Emeritus Distinguished University Professor in the Department of Computer Science, Founding Director (1983-2000) of the Human-Computer Interaction Laboratory, and a Member of the UM Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is a Fellow of the AAAS, ACM, IEEE, NAI, and the Visualization Academy and a Member of the U.S. National Academy of Engineering. He has received six honorary doctorates in recognition of his pioneering contributions to human-computer interaction and information visualization. His widely-used contributions include the clickable highlighted web-links, high-precision touchscreen keyboards for mobile devices, and tagging for photos. Shneiderman’s information visualization innovations include dynamic query sliders for Spotfire, the development of treemaps for viewing hierarchical data, novel network visualizations for NodeXL, and event sequence analysis for electronic health records. Ben is the lead author of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016). He co-authored Readings in Information Visualization: Using Vision to Think (1999) and Analyzing Social Media Networks with NodeXL (2nd edition, 2019). His book Leonardo’s Laptop (MIT Press) won the IEEE book award for Distinguished Literary Contribution. The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, 2016) describes how research can produce higher impacts. His forthcoming book on Human-Centered AI will be published by Oxford University Press in January 2022.

European Association for Artificial Intelligence

Mikel Artetxe at Facebook AI Research has been selected as the winner of the EurAI Doctoral Dissertation Award 2021.

In his PhD research, Mikel Artetxe has fundamentally transformed the field of machine translation, by showing that unsupervised machine translation systems can be competitive with traditional, supervised methods. This is a game-changing finding which has already made a huge impact on the field. To solve this challenging problem of unsupervised machine translation, he has first introduced an innovative strategy for aligning word embeddings from different languages, which are then used to induce bilingual dictionaries in a fully automated way. These bilingual dictionaries are subsequently used in combination with monolingual language models, as well as denoising and back translation strategies, to end up with a full machine translation system.

The EurAI Doctoral Dissertation Award will be officially presented at ACAI 2021 on Tuesday, October 12th, at 17.00 (CET). Mikel Artetxe will also give a talk:

Title: Unsupervised machine translation

Abstract: While modern machine translation has relied on large parallel corpora, a recent line of work has managed to train machine translation systems in an unsupervised way, using monolingual corpora alone. Most existing approaches rely on either cross-lingual word embeddings or deep multilingual pre-training for initialization, and further improve this system through iterative back-translation. In this talk, I will give an overview of this area, focusing on our own work on cross-lingual word embedding mappings, and both unsupervised neural and statistical machine translation.

European Association for Artificial Intelligence

The number of places for on-site participation is limited. The registration is now closed.

Members of EurAI member societies are eligible for a discount (30€).

Students attending on-site will have an opportunity to apply for scholarships.

By registering, you

• commit to attend the ACAI2021 School and do the assignments (where applicable),
• commit to receiving further instructions,
• confirm having acquired approval for participation in ACAI2021 School from your supervisor (where applicable).

Please note, the registration fee does not cover accommodation or travel costs.

Please check the information on entry restrictions, testing and quarantine regulations in Germany.

European Association for Artificial Intelligence

Virginia Dignum, Umeå University
ACAI 2021 General Chair

Paul Lukowicz, German Research Center for Artificial Intelligence
ACAI 2021 General Chair

Mohamed Chetouani, Sorbonne Université
ACAI 2021 Publications Chair

Davor Orlic, Knowledge 4 All Foundation
ACAI 2021 Publicity Chair

Tatyana Sarayeva, Umeå University
ACAI 2021 Organising Chair

European Association for Artificial Intelligence

Venue: Forum Digital Technologies // CINIQ Center: Salzufer 6 (main venue), 10587 Berlin

Travelling and staying in Berlin: The ACAI 2021 school participants are responsible for their own accommodation and trip to Berlin.

Visa: Organizing committee can provide the ACAI 2021 school participant with an invitation letter. For the invitation letter,  we need proof of enrollment at your university and a recommendation letter from your supervisor describing why is important for you to attend ACAI 2021. The ACAI 2021 school participant is responsible for the visa application.

COVID-19 guidance: Please check the information on entry restrictions, testing and quarantine regulations in Germany.

European Association for Artificial Intelligence