- Dagstuhl Materials Page (Use personal credentials as created in DOOR to log in)
The real and digital worlds are increasingly more interconnected, leaving people to split their attention between tasks in the physical world in an increasing amount of ubiquitous systems and IoT services. We see an increase in accidents related to the usage of digital tools (such as interacting with a smartphone while driving). As governments and healthcare experts around the world call for changing lifestyles in response to the Covid-19 pandemic, the development, and usage of remote communication and touchless technologies are rapidly becoming an essential part of the "new normal". At the same time, the absence of touch and physical contact highlights their critical importance in human life, from school to hospital to care facilities. We need more intuitive, direct ways to interface with technology. Students and educators find it harder and harder to concentrate, and news outlets are already talking about the distraction economy. The seminar focused on people interacting with information from the digital domain, in a minimally disruptive way, creating novel sensory experiences using and extending human perception and ultimately cognition.
The overall objective of the seminar was to foster research, explore, and model new means for increasing human intake of information in order to lay the foundation for augmented cognition, especially through somatosensation: the ability to sense the environment through our body.
Machine Learning has often been used to mimic or surpass some cognitive functions of the human mind (visual object/face recognition, playing chess, etc.). Such efforts appear to put humans and computers in a competitive relationship, as emphasized in AI vs. Human competitions. Once a fear of AIs "replacing" human workers is now taken much more seriously and discussed in the public sphere. This Dagstuhl proposal suggests a different approach to the human-computer relationship by applying a cooperative and empowering framework. One important characteristic of the human mind is that it has significant fluctuations in productivity and capacity. Our mind has ebbs and flows, and is affected by various factors, some of which we do not even realize. These fluctuations manifest in patterns in human behavior and physiological signals (body temperature, eye movements, galvanic skin response, etc.). With this seminar, we aim to discuss technologies that can give us more insights into the ebb and flow of the human mind as a basis for cognitive augmentation.
The participants developed several frameworks and taxonomies for understanding and evaluating different types of cognitive augmentation, based on their goals, methods, and impacts. The frameworks focus on enhancement, compensation, offloading, and replacement, and consider factors such as safety, efficacy, and social impact. There are several publication plans and several participants already agreed to organize conference workshops together (for example at AugmentedHumans 2023 and UbiComp/ISWC 2023).
Overall, the Dagstuhl Seminar on Cognitive Augmentation advanced our research fields by creating a shared understanding of the concept and its implications, promoting interdisciplinary collaboration and communication, and identifying promising directions for future research and development. The outcomes of the seminar are to inform the design, implementation, and evaluation of cognitive augmentation technologies, and contribute to augmenting human cognition by applying ethical principles.
Smartphones and other wearable computers have become an integral part of most people's life. They support us in a wide variety of applications and use cases from simple navigation over health to work. Most of the time these devices just externalize knowledge, be it ours (over notes, pictures, calendar information, etc.) or that of others (e.g. access to Wikipedia, maps, Internet applications). Yet, even though we have all of this information at our fingertips, it is unclear how we should interface with it. How can we make information intake more "natural"? Can we extend our perception to understand complex digital data more intuitively? New findings in neuroscience, applied psychology, and physiology suggest it’s possible. This Dagstuhl Seminar brings together specialists of these fields, as well as researchers from wearable computing, human-computer interaction, machine perception, and pattern recognition to discuss the possibility of digitally enhancing our cognition/perception, augment our skills and create novel digital senses.
The concept to use information technology to augment the human intellect goes back to research from the 1960s (Douglas Engelbart et al.). The basic idea is to extend the computational (and other) capabilities of the human mind using technology. The ongoing technical progress in key areas (better insights how our mind works, advances in real-life tracking of physical, cognitive and emotional states) will enable fundamentally new approaches to amplify the human intelligence.
A major objective of the Dagstuhl Seminar is to foster research and explore and model new means for increasing human intake of information in order to lay the foundation for augmented cognition. One important characteristic of the human mind is that it has significant fluctuations in productivity and capacity. Our mind has ebb and flow, and is affected by various factors, some of which we do not even realize. These fluctuations manifest in patterns in human behavior and physiological signals. We aim to discuss technologies that can give us more insights into the ebb and flow of the human mind as a basis for cognitive augmentation. Beside just recognizing cognitive fluctuations, an elegant solution to extend people’s sensed information through technology would be to augment or "code" cognition.
This seminar focuses on how to interact with information from the digital domain in a minimally disruptive way, creating novel sensory experiences using and extending human perception and cognition.
- Michael Beigl (KIT - Karlsruher Institut für Technologie, DE) [dblp]
- Michael D. Bonfert (Universität Bremen, DE)
- Samantha W.T. Chan (MIT - Cambridge, US)
- Jiawen Han (Keio University - Yokohama, JP)
- Matthias Hoppe (LMU München, DE)
- Masahiko Inami (University of Tokyo, JP) [dblp]
- Shoya Ishimaru (TU Kaiserslautern, DE) [dblp]
- Shunichi Kasahara (Sony CSL - Tokyo, JP) [dblp]
- Marion Koelle (OFFIS - Oldenburg, DE) [dblp]
- Thomas Kosch (HU Berlin, DE) [dblp]
- Kai Kunze (Keio University - Yokohama, JP) [dblp]
- Yuichi Kurita (Hiroshima University, JP)
- Jie Li (EPAM Systems - Hoofddorp, NL)
- Stephan Lukosch (University of Canterbury - Christchurch, NZ) [dblp]
- Paul Lukowicz (DFKI - Kaiserslautern, DE) [dblp]
- Kouta Minamizawa (Keio University - Yokohama, JP)
- Qianqian Mu (Aarhus University, DK)
- Pat Pataranutaporn (MIT - Cambridge, US)
- Rakesh Patibanda (Monash University - Clayton, AU) [dblp]
- Roshan Lalintha Peiris (Rochester Institute of Technology, US)
- Enrico Rukzio (Universität Ulm, DE) [dblp]
- Albrecht Schmidt (LMU München, DE) [dblp]
- Valentin Schwind (Frankfurt University of Applied Sciences, DE)
- Paul Strohmeier (Max-Planck-Institut für Informatik Saarbrücken, DE) [dblp]
- Steeven Villa (LMU München, DE)
- Tobias Wagner (Universität Ulm, DE)
- Jamie A. Ward (University of London, GB) [dblp]
- Don Anusha Withanage (The University of Sydney, AU) [dblp]
- Katrin Wolf (Berliner Hochschule für Technik, DE) [dblp]
- Cindy Hsin-Liu Kao (Cornell University - Ithaca, US) [dblp]
- Zhuying Li (Southeast University - Nanjing, CN) [dblp]
- Pattie Maes (MIT - Cambridge, US) [dblp]
- Florian 'Floyd' Mueller (Monash University - Clayton, AU) [dblp]
- Suranga Nanayakkara (National University of Singapore, SG) [dblp]
- Evangelos Niforatos (TU Delft, NL) [dblp]
- Nathalie Overdevest (Monash University - Clayton, AU)
- Bektur Ryskeldiev (Mercari - Tokyo, JP)
- Aryan Saini (Monash University - Clayton, AU) [dblp]
- Stel Stelarc (Bentley, AU)
- Po-Yao (Cosmos) Wang (National Taiwan University - Taipei, TW)
- Artificial Intelligence
- Human-Computer Interaction
- Machine Learning
- Wearable Computing
- Augmented Humans
- Augmented Reality