A paper based on controllable models for simplifying medical text, co-authored by our colleague Rosni Kottekulam Vasu and external collaborators, was accepted at the 37th AAAI Conference on Artificial Intelligence! The paper is titled “Med-EASi: Finely Annotated Dataset and Models for Controllable Simplification of Medical Texts” and was jointly conducted with Chandrayee Basu, Michihiro Yasunaga from Stanford University, and Qian Yang from Cornell University.

The paper’s vision is an interactive automatic medical text simplification system, which can enable medical practitioners and patients to simplify the contents of a text or conversation selectively and have controllability over the type of desired textual transformations.

Rosni presented the work at AAAI, orally and on a poster and was accepted to the 2023 AAAI student scholarship and volunteer program. Congratulations!

In his Bachelor Thesis, Viktor Lakic investigated the decay happening in datasets when the resources that Web-URLs point to become unavailable. This Link-Rot can cause problems for reproducibility, as datasets can shrink over time, potentially changing the outcome of experiments which use them. A paper based on the data that Viktor collected in his thesis, co-authored by Luca Rossetto and Abraham Bernstein, was recently presented at the 2023 International Conference on Multimedia Modeling in the Special Session on ‘Multimedia Datasets for Repeatable Experimentation’. The paper was awarded the ‘Best Special Session Paper Award’, honoring the best contribution across all special sessions of the conference. Congratulations!

For five days, scholars in computer science, political science, law, and communication sciences discussed current challenges and future opportunities of online participation, political communication, and online deliberation.

The paper, which looks into how the kind of expert giving the advice — i.e., a human or an AI advisor — influences trust, perceived responsibility, and reliance.

For more information about the paper, please check it out in our on-line library, over at the ACM Digital Library, and the video presentation prepared by Suzanne.

For your convenience you can also find the abstract right here:

While artificial intelligence (AI) is increasingly applied for decision-making processes, ethical decisions pose challenges for AI applications. Given that humans cannot always agree on the right thing to do, how would ethical decision-making by AI systems be perceived and how would responsibility be ascribed in human-AI collaboration? In this study, we investigate how the expert type (human vs. AI) and level of expert autonomy (adviser vs. decider) influence trust, perceived responsibility, and reliance. We find that participants consider humans to be more morally trustworthy but less capable than their AI equivalent. This shows in participants’ reliance on AI: AI recommendations and decisions are accepted more often than the human expert’s. However, AI team experts are perceived to be less responsible than humans, while programmers and sellers of AI systems are deemed partially responsible instead.

At the same conference, a group of DDIS members also presented a demo of a graph-based retrieval system for lifelogs. ‘LifeGraph’ was developed in the context of an international evaluation campaign which, due to some changes and delays caused by the pandemic, was held online only a week before ISWC. During the demo, conference attendees could get an impression of how such a graph exploration-based approach could be used to find particular events from the life of a lifelogger. The demo was nominated for ‘Best Demo’. More information on the inner workings of that approach can be found in the paper, authored by Luca Rossetto, Matthias Baumgartner, Narges Ashena, Florian Ruosch, Romana Pernisch, and Abraham Bernstein.

In the paper, Suzanne and team develop a taxonomy to categorize HRI failure types and their impact on trust. A risk score is introduced, as well as possible mitigation strategies to handle trust breaks of the user in a robotic system. The collaboration for this paper was a result of a workshop at Schloss Dagstuhl on ‘Ethics and Trust: Principles, Verification and Validation‘.

More information about this study is available in the article here and in the presentation that Daniele gave at the conference can be found by clicking the image below.

Finally, users interested in trying out SihlQL can find SihlMill, a SihlQL engine here.

This study is partially supported by the Swiss National Science Foundation under contract number #407550_167177 NFP 75‘s project Privacy-preserving, stream analytics for non-computer scientists.

Crowds vs Covid

Rosni was part of a team that tackled the challenge that the global research community is overwhelmed with the resources of over 47,000 scholarly articles related to COVID-19, SARS-CoV-2, and related coronavirus. The overloading for scientific and lay people about COVID-19 makes it very difficult to select the right information at the right time. In this context, they developed a pipeline, which can take high volumes of information (either scientific publications or social media), filter it by first feeding it through machine learning algorithms, and then use crowdsourcing to further refine the selection and tagging. This information can then be used to inform policy makers or subject experts in a timely manner.

You can find more information about the project at the following locations:

• Team Web-site: https://devpost.com/software/crowdvscovid
• Short video: https://www.youtube.com/watch?v=Zu8UV-1hixU
• Prototype System: https://lab.citizenscience.ch/en/
  

KurzarbeitGoesDigital

Florian helped developing a platform to digitalize, simplify, and accelerate the application process for short-time work (Kurzarbeit). Employers can digitally file the application according to official governmental and cantonal guidelines. The digitalized solution may be used swiss-wide and considers cantonal differences. Furthermore, it allows to make real-time analyses based on filed applications per canton or aggregated for the whole country and visualize the results. This project even made it into the set of highlights in the category “Economic Impact”.

You can find more information about the project at the following locations:

• Team Web-site: https://www.versusvirus.ch/blog/kurzarbeitgoesdigital?categoryId=150018
• Short video: https://www.youtube.com/watch?v=Zu8UV-1hixU
• Prototype System: http://kurzarbeitportal.mhc.li

Update

Our very own Florian was interviewed by CNN Money Switzerland. The piece aired on April 7 and can be found here: https://www.cnnmoney.ch/shows/big-picture/videos/highlights-versus-virus-hackathon

A few weeks ago, the 18^th International Semantic Web Conference took place in Auckland, New Zealand. A delegation of DDIS visited the conference and made some valuable contributions to the conference. A little overview of our work:

On Saturday the 26^th of October, Prof. Abraham Bernstein and Dr. Daniele Dell’Aglio ran a tutorial on Blockchain and Semantic web in collaboration with the University of Southampton and the Open University.

Romana Pernischová presented her work at the doctoral consortium on Sunday: ‘The Butterfly Effect in Knowledge Graphs: Predicting the Impact of Changes in the Evolving Web of Data’. At the same doctoral consortium, Daniele participated in a panel on ‘AI knocked to the Industry’s Door: Which is the Role of the PhD?’.

On Monday, Romana presented her poster ‘Toward Predicting Impact of Changes in Evolving Knowledge Graphs’ at the minute madness, and went on to present her poster at the welcome reception. This poster was declared the winner of best poster award.

Prof. Bernstein had a busy day on Tuesday: he was both track and session chair of the ‘Outrageous idea’ track, as well as chair on the panel ‘How to make Semantic Web Research /Outrageous/?’

On the final day of the conference, Daniele chaired the Linked Data analytics and dynamics session. Finally, Daniele was also recognized as a distinguished reviewer in the research track. Overall, it was a very productive and successful event and we look forward to next year’s edition.