Fall Term 2022

The colloquia are held in English and take place from 5.15 to 6.30 p.m. in room 2.A.01 at the Department of Informatics (IfI), Binzmühlestrasse 14, 8050 Zürich. After the talks there is time for discussions and to exchange ideas while enjoying refreshing beverages and munchies.

Visiting a colloquium is free of charge and does not require registration. 

Details about the format of the talk shall be checked always just ahead of a certain presentation date.

If you have further questions please contact Karin Sigg.

Flyer to download (PDF, 226 KB)

The IFI colloquium talks will be held at the date indicated below. They start at 5:15 p.m. or see time below date.

** If you would like to get access to the talk please send an email to  studies@ifi.uzh.ch.

22.09.2022 – Bias by Design: How Digital Technology Can Fail its Diverse Users

Speaker:  Prof. Dr. Katharina Reinecke

Host: Prof. Abraham Bernstein, PhD

Abstract

From social media to conversational AI, digital technology has become a mainstay in the lives of many people around the world. Many of these inventions have been made in large technology centers, like Silicon Valley, that are inherently biased towards the views and experiences of product designers and developers who do not reflect a broad demographic in terms of age, education levels, culture, race, and physical abilities. 

In this talk, I will show how unconscious bias in the design of digital technology can systematically disadvantage specific groups of people. Specifically, I will present my lab’s prior work on diverse users’ experiences with digital technologies—ranging from websites and online communities to security & privacy interfaces and conversational AI—outlining how a lack of knowledge about diverse people can result in technology that is useful for some, but not all users. I will also present two approaches we have developed for recognizing biases in digital technology design: (i) Studying how diverse populations interact with technology using our volunteer-based Lab in the Wild platform and (ii) anticipating biases based on historical data on the unintended consequences of technology using our SpecTechle platform.
 

Bio

Katharina Reinecke is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington where she researchers and teaches human-computer interaction and computing ethics. Her research explores how people's interaction with digital technology varies depending on their cultural, geographic, or demographic background and how technology can be biased against people who are unlike the small groups of people that created it. Her lab has developed a number of approaches and systems that make technology better suitable for diverse user groups and that can help designers and developers anticipate unintended consequences of technology. 

Katharina is a co-founder of Lab in the Wild, a virtual lab for conducting large-scale behavioral studies with diverse participants, and of Augury Design Inc., a startup that predicts the success of website designs based on Lab in the Wild data. Katharina received a PhD in Computer Science from the University of Zurich and was a postdoctoral fellow at Harvard University. Prior to coming to the University of Washington, she was an Assistant Professor in the School of Information at the University of Michigan. Her lab is currently supported by the NSF, Google, Microsoft, Adobe, the Wikimedia Foundation, and Facebook.
 

20.10.2022 – Gravity Spy 2.0: Intelligent support for non-experts to navigate large information spaces

Speaker:  Prof. Kevin Crowston, Ph.D.

Host: Prof. Dr. Gerhard Schwabe

Abstract

he increasing use of automated scientific-data-collection instruments has led to an explosion in the amount of scientific data collected, challenging the ability of scientists to analyze them. Non-expert volunteers (“citizen scientists”) are interested in and seemingly able to contribute to data analysis but they lack expertise about the purpose, context, content, provenance and processes associated with the data, which limits their ability to contribute. We hypothesize that a system that provides the needed background knowledge will enable non-experts to make sense of richer data, thus enabling contributions to its analysis. 

This research is based on the Gravity Spy project, in which volunteers classify noise events (glitches) in the Laser Interferometer Gravitational-wave Observatory (LIGO). Along with the glitches observed in the main Gravitational Wave channel, the detectors record around 400,000 auxiliary channels of data that may provide information about the origins of the glitch. Gravity Spy 2.0 will enable volunteers to examine data from a subset of these additional channels to look for possible causes of glitches. To support this work, we are developing processes, techniques and tools to allow the volunteers to manage and efficiently process the data. A main goal of the project is to investigate how and when to introduce which different types of background knowledge about the data to enable non-experts to understand it, e.g., by providing maps and visualizations of particular data and relationships at the time they are most needed in the volunteers' work process.

The project has just completed its first of three years, with the goal of having a working citizen science project when the LIGO detectors resume operation (planned for March 2023). 

Bio

Kevin Crowston is a Distinguished Professor of Information Science in the School of Information Studies at Syracuse University. He received his Ph.D. (1991) in Information Technologies from the Sloan School of Management, Massachusetts Institute of Technology (MIT). 

His research examines new ways of organizing made possible by the extensive use of information and communications technology. Specific research topics include the development practices of Free/Libre Open Source Software teams and work practices and technology support for citizen science research projects, both with NSF support. His most recent project is a study of the evolution of newswork with new technologies and a research coordination network on Work in the Age of Intelligent Machines.

He is currently Editor-in-Chief for the journals ACM Transaction on Social Computing and Information, Technology & People. 

27.10.2022 – From Textual Data to Open Research Data Queryable by References

Speaker:  Dr. Sepideh Alassi

Host: Prof. Dr. Martin Volk

Abstract

Humanities textual data is full of references to persons and locations given in various languages. Researchers want to perform queries to retrieve data, in which a certain place or a person is mentioned, irrespective of the language of the text. 
In this talk, I will present how we automatically extract named entities (geolocation information and person references) from textual data and homogenize and store them as Linked Open Data (LOD) with unique identifiers such as the GeoName ID and the GND (Gemeinsame Normdatei) number. Then the plain references in the text are substituted with standoff links to the corresponding RDF resources and the textual document is stored in RDF format. This enables humanities scholars to perform advanced SPARQL queries to collect textual resources containing specific references regardless of the language of the text. Furthermore, I will present how we apply Natural Language Processing (NLP) to establish connections between the named entities in the text to add more semantic information to the knowledge graph.

Bio

Dr. Sepideh Alassi is a postdoctoral research associate and a lecturer at the Digital Humanities Lab (DHLab), University of Basel. Her background is in digital humanities, computer science, mathematics, and the history of science. She earned her PhD in 2020 in the field of digital humanities and is one of the main developers of Knora (recently renamed DSP-API), Switzerland's flagship RDF-based system for editing, storing, searching, and reusing humanities research data. Her main focus in the field of digital humanities is on applying linked open data (LOD) and semantic web technologies to humanities data creating a knowledge graph that can be efficiently analyzed and queried.

03.11.2022 – Volume Rendering in VR for Medicine

Speaker:  Prof. Dr. Philippe C. Cattin

Host: Prof. Dr. Renato Pajarola

Abstract

The amount of imaging data in the medical field (CT, MR, and others) is growing at a rapid pace. With each new generation of imaging device, the images get even higher spatial resolutions. However, more data does not automatically lead to better diagnoses. While the flood of data continues to grow, comparatively little research is being done on how to make this data more tangible. Philippe Cattin develops a virtual reality system to solve this task. In this talk, he will present this system and discuss the challenges when employing Volume Rendering to visualize patient data. These challenges are even more pronounced when showing volume-rendered images in a virtual reality environment.

Bio

Philippe Cattin was born in Switzerland in 1967. He received his B.Sc. degree from the University of Applied Science in Brugg/Windisch in 1991. In 1995 he received the M.Sc. degree in computer science and in 2003 the Ph.D. degree in robotics from ETH Zurich, Switzerland. From 2003 to 2007 he was a Postdoctoral Fellow with the Computer Vision Laboratory at ETH Zurich. In 2007 he became an Assistant Professor at the University of Basel and was promoted to Associate Professor in 2015 and to Full Professor in 2019. He is the founder of the Center for medical Image Analysis and Navigation (CIAN) at the Medical Faculty of the University of Basel. He is the founding head and still heading the Department of Biomedical Engineering at the University of Basel. Philippe Cattin was in 2017 a Research Fellow at the Brigham and Women's Hospital in Boston/MA.
His research interests include medical image analysis, image-guided therapy, robotics-guided laser osteotomy and virtual reality. As a Principal Investigator, he has finished many projects in these areas and published over 250 papers, patents and book chapters. He is also the founder of three spin-off companies and licensed his patents and software to medical device companies.

10.11.2022 – Interacting with AI

Speaker:  Prof. Dr. Michael Sedlmair

Host: Prof. Dr. Jürgen Bernard

Abstract

In recent years, there has been a strong focus on fully autonomous AI technologies. While full automatization is easy to communicate in the media, the contemporary rhetoric seems to forget that most problems will continue to necessitate meaningful interactions between humans and machines. Along the life cycle of  AI, there are many steps for which humans are needed in the loop: humans need to be able to understand the underlying data, explain AI models, or even cooperate with AI to excel at tasks such as decision making and music composition. Our work focuses exactly on these data, model, and AI interfaces. To that end, we develop and study techniques that combine approaches from human-computer interaction, data visualization, and mixed reality. In the talk, we will look at different examples of such human-data and human-AI interfaces, and think about when they are needed and how to properly build them.

Bio

Michael Sedlmair is a professor at the University of Stuttgart and leads the research group for Visualization and Virtual/Augmented Reality there. He received his Ph.D. degree in Computer Science from the University of Munich, Germany, in 2010. Further stops included the Jacobs University Bremen, University of Vienna, University of British Columbia in Vancouver, and the BMW Group Research and Technology, Munich. His research interests focus on visual and interactive machine learning, perceptual modeling for visualization, immersive analytics and situated visualization, novel interaction technologies, as well as the methodological and theoretical foundations underlying them.

17.11.2022 – AI and bureaucratic decision-making: a new layer of opacity

Speaker:  Prof. Dr. Antonio Cordella

Host: Prof. Dr. Gerhard Schwabe and Dr. Liudmila Zavolokina

Abstract

This talk offers an in-depth analysis and explanation of the reasons why AI cannot solve the problems of transparency and accountability of public administration bureaucracies. The talk offers an innovative theoretical framework for the analysis of AI: the theory of functional simplification and closure. Moreover, the talk contributes providing an innovative way to study AI in the context of public sector bureaucracies, shedding lights on the different impacts of AI on the transparency and accountability of public administration bureaucracies using Mintzberg’s taxonomy of machinery and professional bureaucracy (Mintzberg, 1983). To support the theoretical argument the tlak analyses the well-known public sector AI case of COMPAS, the algorithmic system used to assess offenders’ risk score in US Judiciary – to illustrate how and why AI makes opaquer public bureaucracies decision-making.

Bio

Dr. Antonio Cordella is an associate Professor at the London School of Economics and Political Science (LSE), where he is Academic Programme Director for the Master in Information systems and Digital Innovation, and a visiting professor at the Maastricht Graduate School of Governance, UNMERIT, The Netherland. He has published widely in Information Systems, e-government and public sector associated reforms. An Italian national, he holds a PhD in Information Systems from Gothenburg University, Sweden.

01.12.2022 – What can we learn from Squid Game, Game of Thrones, or Breaking Bad to Lower the Socioeconomic Inequalities in Health?

Speaker:  Prof. Dr. Tobias Kowatsch

Host: Prof. Dr. Gerhard Schwabe

Abstract

Non-communicable diseases (NCDs) impose enormous health burdens on individuals and lead to substantial economic challenges. Known risk factors relate primarily to a lifestyle characterized by tobacco and excessive alcohol consumption, physical inactivity, or an unbalanced diet. This lifestyle can lead to obesity, hypertension, and other cardiovascular and neurodegenerative diseases. Unfortunately, individuals with lower socioeconomic status (SES) are substantially more affected by NCDs. These individuals are also underrepresented in clinical and non-clinical trials. As a result, health interventions are potentially only effective for individuals with higher SES and do not address those most in need. Therefore, it is essential to understand how to reach and engage individuals with lower SES. In this talk, I will discuss what we can learn from the most successful TV shows to “hijack” the comfort zones of vulnerable individuals and design digital health interventions that may lower the socioeconomic inequalities in health.

Bio

Dr Tobias Kowatsch is Associate Professor for Digital Health Interventions at the Institute for Implementation Science in Health Care, University of Zurich (UZH). He is also Director at the School of Medicine, University of St.Gallen (HSG), and the Scientific Director of the Centre for Digital Health Interventions (www.c4dhi.org), a joint initiative of UZH, HSG, and ETH Zurich. Dr Kowatsch is also Advisor to Dartmouth’s Center for Technology and Behavioral Health (www.c4tbh.org). In close collaboration with his interdisciplinary team and research partners, Dr Kowatsch designs digital health interventions at the intersection of information systems research, computer science, and behavioral medicine. He helped initiate and participates in the ongoing development of MobileCoach (www.mobile-coach.eu), an open source platform for ecological momentary assessments, digital biomarker, and health intervention research. He also co-founded the ETH Zurich and University of St.Gallen spin-off company Pathmate Technologies which creates and delivers digital clinical pathways. Dr. Kowatsch holds a PhD in Management (HSG, 2016), a Master’s in Business Informatics (Saarland University, 2012), a Master’s in Media and Computer Science (Hochschule Furtwangen, 2007), and a Diploma (FH) in Computer Science (Hochschule Furtwangen, 2005). After his successful habilitation in 2021, he was also awarded the degree of a private lecturer with the “venia legendi” in Information Systems with a special focus on Digital Health (HSG, 2022). He published his research in the Proceedings of the National Academy of Sciences (PNAS), Annals of Behavioral Medicine, Journal of Consulting and Clinical Psychology (JCCP), American Journal of Preventive Medicine, Journal of Medical Internet Research (JMIR), Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Information Systems Journal (ISJ), and Computers in Human Behavior (CHB).