BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//scienceofintelligence.de - ECPv6.16.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.scienceofintelligence.de
X-WR-CALDESC:Events for scienceofintelligence.de
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Berlin
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20210328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20211031T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20220327T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20221030T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230504T100000
DTEND;TZID=Europe/Berlin:20230504T110000
DTSTAMP:20260615T115635
CREATED:20230320T100436Z
LAST-MODIFIED:20250603T125924Z
UID:14992-1683194400-1683198000@www.scienceofintelligence.de
SUMMARY:Radoslaw Cichy\, “Deep Neural Networks As Scientific Models of Vision”
DESCRIPTION:Abstract: \nArtificial deep neural networks (DNNs) are used in many different ways to address scientific questions about how biological vision works. In spite of the wide usage of DNNs in this context\, their scientific value is periodically questioned. I will argue that DNNs are good in three ways for vision science: for prediction\, for explanation\, and for exploration. I will illustrate these claims by recently published or still ongoing projects in the lab. I will also propose future steps to accelerate progress. \nThis talk will take place in person at SCIoI. \nPhoto kindly provided by Radoslaw Cichy. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-radoslaw-cichy/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2023/03/x2_low_res.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230420T100000
DTEND;TZID=Europe/Berlin:20230420T110000
DTSTAMP:20260615T115635
CREATED:20230320T095113Z
LAST-MODIFIED:20250603T125937Z
UID:14987-1681984800-1681988400@www.scienceofintelligence.de
SUMMARY:Friedhelm Hamann (Science of Intelligence)\, “Applications of Event Cameras: Animal Behavior Quantification in the Wild”
DESCRIPTION:Abstract: \nEvent cameras are novel bio-inspired sensors that naturally respond to motion in the scene. They have promising advantages\, namely a high dynamic range\, little motion blur and low latency. But how can we leverage these advantages for vision tasks such as animal behavior quantification? In this talk I will  present two applications developed at the Robotic Interactive Perception lab\, where we used event cameras to address practical problems\, from low-level vision (background-oriented schlieren imaging\, a technique for visualizing air flow) to high-level vision (animal behavior quantification in the wild). \nThis talk will take place in person at SCIoI. \nPhoto by Steve Johnson on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scioi-project-36/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/03/steve-johnson-Nvmt7-mlR7g-unsplash-1536x1024-1-e1693384970338.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230413T100000
DTEND;TZID=Europe/Berlin:20230413T110000
DTSTAMP:20260615T115635
CREATED:20230320T094941Z
LAST-MODIFIED:20250603T125951Z
UID:14984-1681380000-1681383600@www.scienceofintelligence.de
SUMMARY:Nina Poth (Science of Intelligence)\, “Exploring the Prospects for a Prediction-Oriented View of Intelligence”
DESCRIPTION:Abstract: It has recently been proposed that a minimal condition of intelligence is the ability to form accurate predictions (Tjøstheim & Stephens 2021). In this talk\, I evaluate the promise of this view for integrating intelligence research across subdisciplines within the cognitive and life sciences. I argue that this view combines two desirable features: (1) it allows us to subsume key dimensions identifying intelligent behaviour\, such as goal-directedness\, adaptiveness\, generality\, and flexibility (Coelho Mollo 2021; Glock 2019)\, under a unifying conceptual framework; (2) it combines well with a non-symbolic approach to representation at various degrees of abstraction (Gärdenfors 2004). Thereby\, the predictive view provides opportunities for sharing concepts and transforming problems across research on artificial and biological intelligence. However\, an outstanding issue with this approach is its current lack of insight into the relevant mechanisms and functional interactions generating intelligent behavior. I respond to this challenge by discussing a set of available research heuristics for mechanism discovery (Poth 2022).\n\nReferences \nCoelho Mollo\, D. (2022). Intelligent Behaviour. Erkenntnis\, 1-17.\nGärdenfors\, P. (2004). Conceptual spaces as a framework for knowledge representation. Mind and Matter\, 2(2)\, 9-27.\nGlock\, H. J. (2019). Agency\, intelligence and reasons in animals. Philosophy\, 94(4)\, 645-671.\nPoth\, N. (2022). Schema-centred unity and process-centred pluralism of the predictive mind. Minds and Machines\, 32(3)\, 433-459.\nTjøstheim\, T. A.\, & Stephens\, A. (2021). Intelligence as Accurate Prediction. Review of Philosophy and Psychology\, 1-25. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-nina-poth/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/03/nina-poth.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230406T100000
DTEND;TZID=Europe/Berlin:20230406T110000
DTSTAMP:20260615T115635
CREATED:20221114T104605Z
LAST-MODIFIED:20240813T102441Z
UID:13325-1680775200-1680778800@www.scienceofintelligence.de
SUMMARY:Xing Li (Science of Intelligence)\, "Learning to Manipulate Articulated Objects From Human Demonstrations"
DESCRIPTION:Abstract: \nProgramming robots to manipulate articulated objects such as drawers\, doors\, or locks is a challenging task. One of the major reasons for this difficulty is that robots must physically interact with objects\, and even minor errors during manipulation can result in significant internal forces that may cause damage. \nWhile robots struggle with these manipulation tasks\, humans can effortlessly operate complex mechanisms with great reliability. Moreover\, humans can transfer their experience between objects of the same type\, resulting in remarkable generalization. This raises the question of how we can transfer these robust and general manipulation skills from humans to robots. \nIn this presentation\, we will introduce a viable solution to achieve this transfer in the context of manipulating articulated objects. Specifically\, we will demonstrate that a robot can acquire a manipulation policy that reliably manipulates various instances of the same type based on a single demonstration of a human opening an articulated object. \nFollowing the presentation\, we invite those who are interested to participate in an interactive session where we can discuss and share our experiences with controlling the robot with the soft hand in the robotics lab on the second floor. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-xing-li/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/11/20201020-SCIOI-Xing1-1024x1024-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230330T100000
DTEND;TZID=Europe/Berlin:20230330T110000
DTSTAMP:20260615T115635
CREATED:20230327T091603Z
LAST-MODIFIED:20240813T102500Z
UID:15096-1680170400-1680174000@www.scienceofintelligence.de
SUMMARY:Marah Halawa (Science of Intelligence)\, "Contrastive Learning Approaches for Computer Vision Applications"
DESCRIPTION:Abstract: \nThe recent success in Computer Vision has been mostly attributed to improved results using deep learning models trained on large labeled datasets. Many of these datasets have been labeled by humans. The labeling process\, however\, can be time-consuming\, and in many applications\, it may require expertise that could be costly to acquire. In order to address this requirement\, more research focus and effort have shifted toward unsupervised learning algorithms\, in order to utilize the ever-increasing quantities of unlabeled data. Self-supervised learning (SSL)\, in particular\, is a set of algorithms that specifically aim to learn rich data representations from unlabeled samples\, and it achieves comparable results to fully supervised methods on common benchmarks for image classification and segmentation. The idea behind SSL methods is to learn broad features from the signals that exist in unlabeled data. In other words\, to acquire more general information and knowledge\, and store them as neural network features that will be useful as prior knowledge for subsequent downstream supervised tasks (classification\, segmentation\, regression\, ..etc.). \nThere are two types of SSL methods. First\, self-prediction methods\, which predict some omitted parts (in purpose) of the data using the other existing part of the data\, such as jigsaw puzzle solving. Second\, contrastive learning methods\, which utilize similarities and dissimilarities\, or simply relations\, amongst data samples to form a classification problem\, such as SimCLR (simple contrastive learning of representations). Contrastive learning methods have proven effective as representation learners in applications of natural image classification. Nevertheless\, extending such algorithms to multiple application domains comes with challenges\, and we identify certain limitations in these approaches. Therefore\, in this talk\, we will focus on contrastive learning methods and how to apply them in several computer vision applications. We also discuss the challenges and limitations we identified and how to address them in project 29. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-marah-halawa-contrastive-learning-approaches-for-computer-vision-applications/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/03/20201020-SCIOI-Marah1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230323T100000
DTEND;TZID=Europe/Berlin:20230323T120000
DTSTAMP:20260615T115635
CREATED:20230222T135409Z
LAST-MODIFIED:20240813T102507Z
UID:14755-1679565600-1679572800@www.scienceofintelligence.de
SUMMARY:Dr. Arlena Jung\, "Time Management & Resilience"
DESCRIPTION:Abstract: \nIn this talk\, Dr. Jung will focus on the three key principles of good time management: defining priorities\, managing expectations and developing routines that work. Following the lecture\, the participants have the opportunity to discuss their time management challenges in an individual coaching session. \nDefining Priorities: Dealing with high performance expectations in wide array of areas ranging from research to writing\, presenting\, networking and teaching is a key challenge for early-stage researches. In order to deal effectively with the in part conflicting expectations PhD students and early stage researchers need both the mindset and the self-confidence to define priorities. This means developing short and middle term goals that are both compatible with one’s own long-term goals and the expectations one’s “relevant other’s”. Without clear goals defining priorities and quality criteria become impossible tasks. That participants learn to understand the use of time management tools using the power of the 4 Zs to define SMART goals\, and integrating a “definition of done” into work packages\, milestones and at times even individual tasks. We also address the emotional challenge of dealing with in part conflicting goals\, roles and expectations. Together we discuss how ambiguity tolerance and strategic thinking can be used as key strengths in dealing with the multifaceted challenges but also opportunities of this career phase.  \nManaging Expectations: Complex interdependencies are an inherent part of the qualification phase of early stage research. Without the ability to manage expectations. PhD students have a very limited ability to actually turn their priorities into actionable plans. In this section of the lecture the participants are acquainted with key stakeholder-management tools such as the stakeholder-matrix and the systemic portrait. We\, however\, also discuss key communication skills needed to manage expectations effectively such as “7 shades of no”\, turning “yes” into a deliberate decision and creating solution  oriented dialogues. \nDeveloping routines that work: In order to use the limited resources available as effectively as possible early stage researchers need to learn to develop routines that work. This means figuring out what time management tools fit nicely both with their individual needs and their operational and conceptual tasks. In the last section of the lecture we present time management tools that help PhD students structure their working days and weeks ranging from the pomodoro and the ivy lee method to stimulus-response regulation practices and self-monitoring and self-evaluation methods.\n \n  \nThis talk will take place in person at SCIoI. \nPhoto by freestocks on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dr-arlena-jung-time-management-resilience/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2023/02/Screenshot-2023-02-22-145102.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230309T100000
DTEND;TZID=Europe/Berlin:20230309T110000
DTSTAMP:20260615T115635
CREATED:20230207T103252Z
LAST-MODIFIED:20240813T102512Z
UID:14155-1678356000-1678359600@www.scienceofintelligence.de
SUMMARY:Judith L. Bronstein (University of Arizona)\, "Why Cooperate with Another Species? The Puzzles of Mutualism"
DESCRIPTION:Abstract:\nThe classic view of nature is one of a deathly struggle for existence. Yet\, throughout nature\, organisms cooperate with each other. Mutualisms – mutually beneficial interactions between species – are more than fascinating natural history stories: they are central to the diversity and the diversification of life on Earth. Charles Darwin\, well aware of mutualisms\, mused that if species could be shown to act exclusively for the good of others\, “it would annihilate my theory”. The very young field of mutualism research attempts in part to address Darwin’s challenge. I will first briefly discuss the relationship between within-species cooperation and mutualism. I will then introduce two underlying concepts that are helping to guide our growing understanding: mutualism not only confers benefits but also exacts costs on the participants; and the immediate interests of mutualists commonly conflict. Then\, I will review some of my group’s recent findings that help address two of the most vexing puzzles mutualism poses: if mutualisms are beneficial\, why isn’t the world covered with them; and if mutualisms are costly\, then why doesn’t everyone cheat their partners? Our understanding of mutualism has exploded in recent years\, but this new focus has come at the cost of exploring connections between and mutualism and other forms of interaction – a situation I am working to mend during my Wiko fellowship. I will conclude by highlighting the interfaces that excite me the most.\n\nThis talk will take place in person at SCIoI. \n  \nPhoto by Joseph Sharp on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-judith-l-bronstein-university-of-arizona-why-cooperate-with-another-species-the-puzzles-of-mutualism/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/02/joseph-sharp-sSt1ZE8gYmE-unsplas.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230223T100000
DTEND;TZID=Europe/Berlin:20230223T110000
DTSTAMP:20260615T115635
CREATED:20221114T105022Z
LAST-MODIFIED:20240813T101537Z
UID:13332-1677146400-1677150000@www.scienceofintelligence.de
SUMMARY:Ryan Burnell\, "A Cognitive Approach to the Evaluation of AI Systems"
DESCRIPTION:Abstract: \nThe capabilities of AI systems are improving rapidly\, and these systems are being deployed in increasingly complex and high-stakes contexts\, from self-driving cars to the detection of medical conditions. As the importance of AI grows\, so too does the need for robust evaluation. If we want to determine the extent to which systems are safe\, effective\, and unbiased\, it is vital that we understand the cognitive capabilities of those systems. In this endeavour\, psychological science has a lot to offer—scientists from cognitive\, developmental\, and comparative psychology have spent many decades developing theories and paradigms to understand the cognitive capabilities of adults\, children\, and animals. Drawing on these theories and paradigms\, we are working to build a framework for evaluating the cognitive capabilities of AI systems that we hope can be used to better track and regulate AI progress. I will present an initial version of the framework and discuss the open questions and challenges of applying cognitive science to AI evaluation. \nThis talk will take place in person at SCIoI. \nPhoto by Michael Dziedzic on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-ryan-burnell-a-cognitive-approach-to-the-evaluation-of-ai-systems/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/11/michael-dziedzic-aQYgUYwnCsM-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230216T100000
DTEND;TZID=Europe/Berlin:20230216T110000
DTSTAMP:20260615T115635
CREATED:20230207T104351Z
LAST-MODIFIED:20240813T101551Z
UID:14161-1676541600-1676545200@www.scienceofintelligence.de
SUMMARY:Julten Abdelhalim (Science of Intelligence)\, "Tips and Guidelines for your grant application in Germany"
DESCRIPTION:Abstract: \nThis talk will be targeting junior postdocs and phd at their final stages. It will be a short and brief introduction to the major options for grants (those aiming at the stars or smaller ones). Julten will offer some quick tips on the application process. She will also share her own experience in applying to the DFG Sachbeihilfe and ERC Starting Grant. The talk is not a detailed workshop in which we get into details about the proposal writing but rather a summary and a call out for how you should ideally plan your grant application journey. Those interested in detailed consultation are invited to book appointments later.\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-julten-abdelhalim-our-career-as-a-scientist-make-a-plan-for-successful-grant-applications/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2023/02/Screenshot-2023-02-07-at-11-43-19-People-–-Science-of-Intelligence.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230209T160000
DTEND;TZID=Europe/Berlin:20230209T173000
DTSTAMP:20260615T115635
CREATED:20230119T092829Z
LAST-MODIFIED:20240813T101605Z
UID:14065-1675958400-1675963800@www.scienceofintelligence.de
SUMMARY:Oliver Brock (Science of Intelligence)\, "About the Interplay of Embodiment and Learning in Intelligent Systems"
DESCRIPTION:Abstract:\nBiological intelligent systems manifest their intelligence in physical interactions with other agents and with their environment. Such interactions require embodiment. Intelligence\, both artificial and biological\, also requires some kind of learning. But what is the relationship between the two? How should the two interact? Do they even have to? What could be a common ground on which this relationship can be explored\, negotiated\, and ultimately designed? In this presentation\, I will attempt to provide my personal answers to these questions. I will argue that one of the reasons (deep) machine learning has not yet been able to replicate its smashing successes in the context of robotics lies in the widespread disregard for the important capabilities provided by the body. Instead of considering embodiment\, machine learning seems to be resorting to massive use of physical simulations. This seems to be unnecessarily complicated without being convincingly effective.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-oliver-brock-2/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/01/brock_800.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230209T100000
DTEND;TZID=Europe/Berlin:20230209T110000
DTSTAMP:20260615T115635
CREATED:20230116T111824Z
LAST-MODIFIED:20250603T130020Z
UID:14047-1675936800-1675940400@www.scienceofintelligence.de
SUMMARY:Andreagiovanni Reina (Université Libre De Bruxelles)\, “The Power of Inhibition for Collective Decision Making in Minimalistic Robot Swarms”
DESCRIPTION:Abstract:\nI investigate how large groups of simple robots can reach a consensus with decentralized minimalistic algorithms. Simple robots can be useful in nanorobotics and in scenarios with low-cost requirements. I show that through decentralized voting algorithms\, swarms of minimalistic robots can make best-of-n decisions. In my research\, I show that using a biologically-inspired voting model based on inhibitory signals\, the swarm can collectively perform better and be more resilient against a minority of misbehaving robots than in models without inhibition. Our best-of-n decision algorithm can also be used for collective environmental monitoring. I will show that investigating these models can be very interesting and yield surprising results. As Anderson said in 1972\, More is different. In our analysis\, we found that limiting the communication range or the speed of the robots can improve collective performance in a range of relevant conditions. We explain the mechanisms of some of these phenomena with a combination of mathematical models and large-scale robot experiments.\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-giovanni-rena/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/01/4.-April-LNDW-at-MAR-20220702_Sc.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230126T100000
DTEND;TZID=Europe/Berlin:20230126T110000
DTSTAMP:20260615T115635
CREATED:20221128T133841Z
LAST-MODIFIED:20240813T101630Z
UID:13403-1674727200-1674730800@www.scienceofintelligence.de
SUMMARY:Scott Robins (Bonn University)\, "What Machines Shouldn't Do"
DESCRIPTION:Abstract: \nFrom writing essays to evaluating potential hires\, machines are doing a lot these days. In all spheres of life\, it seems that machines are being delegated more and more decisions. Some of these machines are being delegated decisions that could have significant impact on human lives.Examples of such machines which have caused such impact are widespread and include machines evaluating loan applications\, machines evaluating criminals for sentencing\, autonomous weapon systems\, driverless cars\, digital assistants\, etc. Considering that machines cannot be held morally accountable for their actions (Bryson\, 2010; Johnson\, 2006; van Wynsberghe & Robbins\, 2018)\, the question that governments\, NGOs\, academics\, and the general public should be asking themselves is: how do we keep meaningful human control (MHC) over these machines? \n\nThe literature thus far details what features the machine or the context must have in order for MHC to be realized. Should humans be in the loop or on the loop? Should we force machines to be explainable? Lastly\, should we endow machines with moral reasoning capabilities? (Ekelhof\, 2019; Floridi et al.\, 2018; Robbins\, 2019a\, 2019b; Santoni de Sio & van den Hoven\, 2018; Wendall Wallach & Allen\, 2010; Wendell Wallach\, 2007). Rather than look to the machine itself or what part humans have to play in the context\, I argue here that we should shine the spotlight on the decisions that machines are being delegated. Meaningful human control\, then\, will be about controlling what decisions get made by machines. \n\nI argue that keeping meaningful human control over machines (especially AI which relies on opaque methods) means restricting machines to decisions that do not require a justifying explanation and can\, in principle\, be proven efficacious. Because contemporary methodologies in AI are opaque\, many machines cannot offer explanations for their outputs. In many cases\, decisions require justifying explanations\, and we should therefore not use machines for such cases. It won’t be surprising that machines should be efficacious if they are to be used – especially in contexts that will have impacts on human beings. Increasingly\, however\, machines are being delegated decisions for which we are unable\, in principle\, to evaluate their efficacy. This should not happen. \n\nThese arguments lead to the conclusion that machines should be restricted to descriptive outputs. It must always be a human being deciding how to employ evaluative terms as these terms not only refer to specific states of affairs but also say something about how the world ought to be. Machines which are able to make decisions based on opaque considerations should not be telling humans how the world ought to be. This is a breakdown of human control in the most severe way. Not only would we be losing control over specific decisions in specific contexts\, but we would be losing control over what descriptive content grounds evaluative classifications. \n\nIn this talk\, I will first discuss what it means to say that a machine is ‘doing’ something. I then briefly discuss different proposals for MHC and why they fall short. I then argue that machines should not be delegated evaluative decisions as they require justifying explanations which machines cannot give and cannot be evaluated for efficacy. While this talk is framed negatively\, it is my hope that this focuses research and development to design and build machines to help us realize our visions for how the world ought to be\, rather than machines that tell us hour the world ought to be. Only humans can decide that.\n \nThis talk will take place in person at SCIoI. \nPhoto by David Levêque on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scott-robins-bonn-university-what-machines-shouldnt-do/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/11/david-leveque-GpNOhig3LSU-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230119T100000
DTEND;TZID=Europe/Berlin:20230119T113000
DTSTAMP:20260615T115635
CREATED:20230116T101152Z
LAST-MODIFIED:20250603T130050Z
UID:14043-1674122400-1674127800@www.scienceofintelligence.de
SUMMARY:David Garzón Ramos (Université Libre De Bruxelles)\, “Automatic Design of Robot Swarms: Context and Experiments”
DESCRIPTION:Abstract:\n \nSwarm robotics is a promising approach to the coordination of large groups of robots. Traditionally\, the design of collective behaviors for robot swarms has been an iterative manual process: a human designer manually refines the control software of the individual robots until the desired collective behavior emerges.\n\nIn this talk\, I discuss automatic design as an alternative approach to manual design. In automatic methods\, the design process is cast into an optimization problem: given a task to be performed by the swarm\, an optimization process designs a collective behavior to perform the task and produces appropriate control software for the robots. I focus on experiments that highlight the various aspects of the automatic design of robot swarms: classes of collective behaviors\, control architectures\, and the optimization process. In particular\, I present a case study on the design of shepherding behaviors for groups of robots. The results presented in this talk are outcomes of the project DEMIURGE; an ERC funded project devoted to the study of the automatic design of robot swarms (PI Mauro Birattari).\nThis talk will take place in person at SCIoI. \nPhoto by Omar Flores on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-david-garzon-ramos-universite-libre-de-bruxelles-automatic-design-of-robot-swarms-context-and-experiments/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/01/omar-flores-lQT_bOWtysE-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230112T100000
DTEND;TZID=Europe/Berlin:20230112T110000
DTSTAMP:20260615T115635
CREATED:20221128T133344Z
LAST-MODIFIED:20250603T130102Z
UID:13400-1673517600-1673521200@www.scienceofintelligence.de
SUMMARY:Dustin Lehmann\, Fritz Francisco\, Jorg Raisch\, Pawel Romanczuk (Science of Intelligence)\, “Dynamical Adaptation and Learning: Knowledge Transfer and Cooperative Learning in Groups of Heterogeneous Agents”
DESCRIPTION:Abstract: \nIn groups of agents learning how to solve a common task\, interaction and knowledge transfer between agents is important and can vary depending on network topology. Heterogeneity is one of the key principles that influences the type and quality of interaction between learning agents. Different learning strategies and behaviors can be a driving factor for the learning success at the group and individual level\, whereas differences in dynamics (or capabilities\, behaviors\, internal states\, etc.) can impede the direct transferability of knowledge and may require dynamic adaption of the agents.\nIn this talk\, we show how to infer behavioral heterogeneity in learning groups of fish and how this affects future learning capabilities. Prior knowledge of social partners affects the outcome of learning processes and timing of information uptake. We further investigate behavioral heterogeneity from the perspective of synthetic dynamic systems and how to transfer knowledge between dissimilar agents to enable cooperative learning of how to solve a common task. First results show how to exploit heterogeneity for learning in synthetic agents and which information gradient is beneficial when dealing with novel tasks in a social context.\n \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dustin-lehmann-fritz-francisco-jorg-raisch-pawel-romanczuk-dynamical-adaptation-and-learning-knowledge-transfer-and-cooperative-learning-in-groups-of-heterogeneous-agents/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/11/project-52.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221215T100000
DTEND;TZID=Europe/Berlin:20221215T110000
DTSTAMP:20260615T115635
CREATED:20220914T121043Z
LAST-MODIFIED:20250603T130137Z
UID:13049-1671098400-1671102000@www.scienceofintelligence.de
SUMMARY:Robert Lange and Luis Gomez (Science of Intelligence)\, “Quantifying and Modelling Collective Behavior Across Ecological Contexts”
DESCRIPTION:Abstract: \nA central challenge in understanding the concept of swarm intelligence is the relation between the behavior of a swarm of agents and its ecological niche. In order to interpret such collective concept\, we have been using analytical and synthetic approaches to get more insights using mainly one particular biological system of Sulphur mollies as study system. We have combined analytical behavioral characterizations of schools of these fish with synthetic state-of-the-art machine learning methods to understand the  functionality of the behavior in real life. In this talk\, we will show our main findings related to the collective behavior. We will show i) that the highly synchronized diving behavior of the school is close to criticality\, ii) how this can be functionally related to effective communication about predator attacks\, and iii) how to study the heterogeneity in collectives by inferring the parameters of models using machine learning algorithms. \nThis talk will take place in person at SCIoI.
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-p12/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/Pawel-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221208T100000
DTEND;TZID=Europe/Berlin:20221208T110000
DTSTAMP:20260615T115635
CREATED:20221128T100636Z
LAST-MODIFIED:20250603T130147Z
UID:13385-1670493600-1670497200@www.scienceofintelligence.de
SUMMARY:Erik Rodner “Please Label Me: Challenges and Efficient Strategies for Data Annotation and Selection”
DESCRIPTION:Abstract: \nLack of data and annotations has been the showstopper for machine learning projects when I started my PhD and 15 years later it still is. In my talk\, I will give a brief overview of recent models we developed for weakly- and semi supervised as well as for active learning.\nIn addition\, we will analyze the relevance of these algorithms from an industrial perspective\, which often contradicts with the usual story line in traditional computer vision publications. \nThis talk will take place in person at SCIoI. \n  \nPhoto by vackground.com on Unsplash
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-erik-rodner-please-label-me-challenges-and-efficient-strategies-for-data-annotation-and-selection/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/11/vackground-com-agUC-v_D1iI-unsplash-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221201T100000
DTEND;TZID=Europe/Berlin:20221201T110000
DTSTAMP:20260615T115635
CREATED:20220914T121438Z
LAST-MODIFIED:20240813T101934Z
UID:13054-1669888800-1669892400@www.scienceofintelligence.de
SUMMARY:David Bierbach (Science of Intelligence)\, "Anticipation in social interactions among live and artificial agents"
DESCRIPTION:Abstract: \nThe aim of SCIoI’s P10 is to investigate how anticipation and prediction shapes social interactions among live and artificial agents using for example the Robofish system. We will outline our research showing the sophisticated anticipation abilities of live fish\, as well as how we integrated prediction and anticipation into Robofish’s social interaction behaviors. We will furthermore show how experiments with robotic animals can help to promote animal welfare and what is necessary to build biomimetic robots that will be accepted by live animals as conspecifics (see also these articles: https://www.frontiersin.org/articles/10.3389/fbioe.2020.00441/full\,  https://www.annualreviews.org/doi/10.1146/annurev-control-061920-103228\, https://link.springer.com/chapter/10.1007/978-3-030-64313-3_26 ). Finally we will dive into our public outreach activities that include the Robofish exhibition in the Humboldt Labor at Stadtschloss Berlin with more than 100\,000 visitors since 2021. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-p10-jens-krause-verena-hafner-2/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/Robotic-Fish-2-1536x1024-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221124T113000
DTEND;TZID=Europe/Berlin:20221124T130000
DTSTAMP:20260615T115635
CREATED:20221117T101332Z
LAST-MODIFIED:20240813T101103Z
UID:13344-1669289400-1669294800@www.scienceofintelligence.de
SUMMARY:Thursday morning talk: Nicolas Mandel\, "Kangaroos & Quadcopters"
DESCRIPTION:Abstract: \nThe contents of this presentation will be twofold. In the first part the Centre for Robotics of the Queensland University of Technology (QUT) and its research directions and facilities will be introduced. The research on semantics for the benefit of UAVs\, specifically quadcopters\, will be highlighted. The second part will contain the personal experiences of the presenter of undertaking a PhD in Australia\, highlighting differences\, challenges and lessons learnt along the way.Disclaimer: The views and opinions in this talk are the presenters and do not necessarily reflect the opinions of any of the employers or affiliates.\nThis talk will take place in person at SCIoI. \n  \nPhoto by Indy Bruhin on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-nicolas-mandel-kangaroos-quadcopters/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/11/indy-bruhin-mJ_oRYZqXdw-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221124T100000
DTEND;TZID=Europe/Berlin:20221124T110000
DTSTAMP:20260615T115635
CREATED:20220914T120810Z
LAST-MODIFIED:20240813T101121Z
UID:13046-1669284000-1669287600@www.scienceofintelligence.de
SUMMARY:What are futures made of? Collactive Materials\, a joint SCIoI/MoA project
DESCRIPTION:Abstract:\nThe BUA-funded experimental knowledge transfer project CollActive Materials\, a collaboration between the Clusters of Excellence Science of Intelligence and Matters of Activity\, encourages speculation on what the future has in store. \nWhich intelligent materials will pave our tomorrows? How can substances and materials change our world in an intelligent way? What will the world look like in the coming decades\, and how can we turn our speculations into something tangible?  Finally\, what kinds of relationships could we create with intelligent materials? \nIn this Thursday Morning Talk the audience will learn more about the CollActive Materials project and all the exciting interactions between the two clusters\, and most importantly\, they will get a chance to dive into the project themselves by taking part in a mini speculative design exercise. \nSPEAKERS:  \nLéa Perraudin is a media theorist and speculative material scholar and works as postdoctoral research associate at the Cluster of Excellence »Matters of Activity. Image Space Material«. Léa currently works on a habilitation project\, bringing forth a media theory of phase transitions by investigating the ties of material and metaphor in contemporary technocapitalist media environments through transience\, dispersal\, abundance and solidification.\nFurthermore\, Léa is the co-leader of the experimental laboratory »CollActive Materials«\, a joint project of the Clusters of Excellence »Matters of Activity« and »Science of Intelligence«\, that intends to gather multiple publics to jointly tackle possible material futures through the method of speculative design. \nMartin Müller researches at the intersection of cultural history and theory\, media studies\, history of knowledge and science\, and design theory. He is a postdoctoral research associate at the Cluster of Excellence »Matters of Activity. Image Space Material« – in the projects »Symbolic Material« and »Material Form Function«. Since 2015 he has been teaching at the Department of Cultural History and Theory at Humboldt-Universität zu Berlin. Martin is the co-leader of the experimental laboratory for knowledge exchange and speculative design »CollActive Materials«. Recently published: »The Will to Engineer. Synthetic Biology and the Escalation of Zoëpolitics«\, in: P. Ribault (Ed.): Design\, Gestaltung\, Formatività\, 2022 \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-matters-of-activity-moa/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/Screenshot-2022-09-20-at-08.21.13.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221117T100000
DTEND;TZID=Europe/Berlin:20221117T110000
DTSTAMP:20260615T115635
CREATED:20220914T120516Z
LAST-MODIFIED:20250603T130205Z
UID:13043-1668679200-1668682800@www.scienceofintelligence.de
SUMMARY:Heiner Spiess (Science of Intelligence)\, “Tools To Study the Generality of Deep Neural Network Representations”
DESCRIPTION:Abstract: \nAs many of us know by now\, Deep Learning has enabled tackling very challenging problems and applications that were previously almost impossible to solve with machine learning. However\, for most of the tasks we want to solve with Deep Learning\, we need large\, if not huge\, amounts of data and computing power. This is very limiting for many applications for which we do not have the necessary amounts of data or for practitioners who do not have access to enough computation power to train well-performing Deep Networks for their desired tasks.We hope to overcome these two limitations by leveraging the generality of already trained models through Transfer Learning or combining the information from multiple\, perhaps relatively small\, datasets with Multi-Task-Learning.In this project\, we are investigating the generality of representations learned by Deep Networks. Today I would like to introduce one of the families of tools we use in this effort: Representational Similarity Analysis (RSA).I will present the methodology behind these tools and provide some insights into Deep Networks gained through their use. However\, I would highlight some concerns to be aware of when using these tools and present some challenges that arise in practice. Considering these concerns\, I will present a variant of these tools that solves some of the existing problems.Furthermore\, I will shortly present a tool that we have developed to synthesize realistic image data\, allowing us to systematically analyse which properties of the data are represented in Deep Networks.Finally\, I want to mention our SCIoI cooperation with project 01 on “Scanpath Prediction in Dynamic Scenes using an end-to-end Deep Learning approach”. \nPhoto by Nina Ž. on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-heiner-spiess/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/nina-z-VKg1oXU-vzo-unsplash-1536x1024-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221110T100000
DTEND;TZID=Europe/Berlin:20221110T110000
DTSTAMP:20260615T115635
CREATED:20220926T105840Z
LAST-MODIFIED:20240813T101157Z
UID:13108-1668074400-1668078000@www.scienceofintelligence.de
SUMMARY:Jan De Bruyne (Leiden University)\, "Liability for Damage Involving AI – Some Regulatory Challenges and Priorities"
DESCRIPTION:More details to follow. \nPhoto by DeepMind on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-jan-de-bruyne/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/deepmind-lISkvdgfLEk-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221103T100000
DTEND;TZID=Europe/Berlin:20221103T110000
DTSTAMP:20260615T115635
CREATED:20220914T120203Z
LAST-MODIFIED:20240813T101210Z
UID:13040-1667469600-1667473200@www.scienceofintelligence.de
SUMMARY:POSTPONED: Scott Robbins\, "What Machine's Shouldn't Do"
DESCRIPTION:From writing essays to evaluating potential hires\, machines are doing a lot these days. In all spheres of life\, it seems that machines are being delegated more and more decisions. Some of these machines are being delegated decisions that could have significant impact on human lives. Examples of such machines which have caused such impact are widespread and include machines evaluating loan applications\, machines evaluating criminals for sentencing\, autonomous weapon systems\, driverless cars\, digital assistants\, etc. Considering that machines cannot be held morally accountable for their actions (Bryson\, 2010; Johnson\, 2006; van Wynsberghe & Robbins\, 2018)\, the question that governments\, NGOs\, academics\, and the general public should be asking themselves is: how do we keep meaningful human control (MHC) over these machines? \nThe literature thus far details what features the machine or the context must have in order for MHC to be realized. Should humans be in the loop or on the loop? Should we force machines to be explainable? Lastly\, should we endow machines with moral reasoning capabilities? (Ekelhof\, 2019; Floridi et al.\, 2018; Robbins\, 2019a\, 2019b; Santoni de Sio & van den Hoven\, 2018; Wendall Wallach & Allen\, 2010; Wendell Wallach\, 2007). Rather than look to the machine itself or what part humans have to play in the context\, I argue here that we should shine the spotlight on the decisions that machines are being delegated. Meaningful human control\, then\, will be about controlling what decisions get made by machines. \nI argue that keeping meaningful human control over machines (especially AI which relies on opaque methods) means restricting machines to decisions that do not require a justifying explanation and can\, in principle\, be proven efficacious. Because contemporary methodologies in AI are opaque\, many machines cannot offer explanations for their outputs. In many cases\, decisions require justifying explanations\, and we should therefore not use machines for such cases. It won’t be surprising that machines should be efficacious if they are to be used – especially in contexts that will have impacts on human beings. Increasingly\, however\, machines are being delegated decisions for which we are unable\, in principle\, to evaluate their efficacy. This should not happen. \nThese arguments lead to the conclusion that machines should be restricted to descriptive outputs. It must always be a human being deciding how to employ evaluative terms as these terms not only refer to specific states of affairs but also say something about how the world ought to be. Machines which are able to make decisions based on opaque considerations should not be telling humans how the world ought to be. This is a breakdown of human control in the most severe way. Not only would we be losing control over specific decisions in specific contexts\, but we would be losing control over what descriptive content grounds evaluative classifications. \n  \nPhoto by Alex Knight on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scott-robbins/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/alex-knight-2EJCSULRwC8-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221020T100000
DTEND;TZID=Europe/Berlin:20221020T110000
DTSTAMP:20260615T115635
CREATED:20220908T135026Z
LAST-MODIFIED:20250603T130235Z
UID:13017-1666260000-1666263600@www.scienceofintelligence.de
SUMMARY:David Bierbach (Science of Intelligence)\, “Anticipation in Fish-Robot Interactions”
DESCRIPTION:Abstract:\nI will present our current research involving the Robofish. I will put a special focus on our latest research paper that found live fish to be able to anticipate predictably behaving Robofish both in regard to final movement locations as well as movement dynamics.  \nThis talk will take place in person at SCIoI \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-project-11/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/Screenshot-2022-10-17-at-13-30-25-Konnen-Fische-antizipieren.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221013T100000
DTEND;TZID=Europe/Berlin:20221013T110000
DTSTAMP:20260615T115635
CREATED:20220908T134759Z
LAST-MODIFIED:20250603T130249Z
UID:13014-1665655200-1665658800@www.scienceofintelligence.de
SUMMARY:Alan Tump\, Dominik Deffner\, David Mezey (Science of Intelligence)\, “How Cognitive Computational Modeling Can Help Us Better Understand Principles Underlying Collective Intelligence”
DESCRIPTION:Abstract:\nCollective dynamics play a crucial role in everyday decision-making. Whether social influence promotes the spread of accurate information\, and ultimately results in collective intelligence\, or leads to false information cascades and maladaptive social contagion depends on the cognitive mechanisms underlying social interactions. \nIn our talk\, we will argue that cognitive modeling\, in tandem with experiments that allow collective dynamics to emerge\, can mechanistically link cognitive processes at the individual and collective levels and\, thus\, provides a fruitful path forward in identifying principles of collective intelligence. \nWe will show how such cognitive computational approaches are increasingly being used to better understand social and collective decision-making\, and will explore how we can extend this strategy to more unconstrained social decision spaces\, typical of real-world collective intelligence. \n  \nPhoto by Alina Grubnyak on Unsplash \n***Want to attend one of our events? Sign up here.\nTo get regular updates\, subscribe to our mailing list from this page.\nThe Zoom Link will be sent the day before the lecture.
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-alan-trump-domink-deffner-david-mezey-scioi-p26-p34/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/09/tmt1-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220714T100000
DTEND;TZID=Europe/Berlin:20220714T113000
DTSTAMP:20260615T115635
CREATED:20220711T104038Z
LAST-MODIFIED:20250603T130335Z
UID:12703-1657792800-1657798200@www.scienceofintelligence.de
SUMMARY:Katharina Scheiter (University of Potsdam)\, “Multimodal Learning: Underlying Processes and How To Support Them”
DESCRIPTION:Abstract:Theories of learning from multimodal sources (e.g.\, combinations of text and pictures\, aka multimedia) posit that in order to effectively learn from multimedia\, students need to select information from text and pictures\, organize the information in memory\, and most importantly\, integrate the information into one mental model. In the first part of my presentation\, I will focus on what is meant by text-picture integration by discussing results from empirical studies aimed at better understanding its underlying processes. In the second part of my presentation\, I will focus on ways to improve text-picture integration in educational settings through enhancing the design of the learning materials as well as nudging students into processing them more effectively. Eye tracking plays a major role in this research both as a research tool but also as an instructional tool to improve multimodal learning. \nPhoto by Element5 Digital on Unsplash \nThe Zoom Link will be sent the day before the lecture.
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-katharina-scheiter-university-of-potsdam-multimodal-learning-underlying-processes-and-how-to-support-them/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/07/ll-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220623T100000
DTEND;TZID=Europe/Berlin:20220623T113000
DTSTAMP:20260615T115635
CREATED:20220523T090343Z
LAST-MODIFIED:20240813T100735Z
UID:12107-1655978400-1655983800@www.scienceofintelligence.de
SUMMARY:Nicolas Roth\, Aravind Battaje\, Adrian Sieler and Vincent Wall (Science of Intelligence)\, "Integration Hackathons for Behavior 1"
DESCRIPTION:A cornerstone of SCIoI are the three example behaviors that provide the motivation\, as well as the demonstration platforms to showcase the amazing research happening within the cluster. In order to get the ball rolling towards interesting example behaviors\, we have recently started regular “integration hackathon” meetings. They bring together people from different projects\, who identify achievable first integration steps\, and just start putting things together. \nIn this talk\, Nico from P1\, Aravind from P2\, and Adrian and Vincent from P17 will present this process. We will show the Behavior 1 escape room component that we selected for our first integration attempts\, explain which different research components come together to create the combined behavior\, and share some insights and observations we made along the way. In the end\, we hope to encourage everybody in SCIoI to think about integration steps and motivate people to get involved in the exciting\, rewarding (and necessary!) integration efforts for the example behaviors. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-thursday-morning-talk-adrian-sieler-nicolas-roth-aravind-battaje-vincent-wall/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2022/05/Screenshot-2022-06-03-at-12.24.34.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220616T100000
DTEND;TZID=Europe/Berlin:20220616T110000
DTSTAMP:20260615T115635
CREATED:20220428T100808Z
LAST-MODIFIED:20240404T101644Z
UID:12001-1655373600-1655377200@www.scienceofintelligence.de
SUMMARY:Thursday Morning Talk with Andrea Iannelli (ETHZ)\, "Learning and Controlling: Robustness\, Informativity and Adaptation"
DESCRIPTION:Abstract: \nThe abundance of available data on the one hand\, and the increase in systems complexity caused by the need to cope with new challenging tasks on the other\, have put research on so-called learning and data-driven methods in the agenda of virtually every engineering field. Control theory is no exception. In fact\, some of its traditional fields have close connections with open problems in data science\, such as system identification (with regression and classification) and adaptive and stochastic optimal control (with reinforcement learning). The first part of the talk will give an overview of our ongoing work on basic research problems at the intersection between control theory and learning. This will be followed by a more detailed discussion on two projects that investigate the problem of controlling unknown dynamical systems from different perspectives. One blends behavioral system theory\, which sees dynamical systems as sets of trajectories\, and system identification\, concerned with identifying models from data using statistical and information theoretic tools. The other frames it as an optimal control problem and proposes a robust adaptive model predictive control with active learning components to address the tension between exploration and exploitation. A discussion on the current limitations\, future extensions\, and foreseeable challenges will conclude the talk. \n  \nPhoto by Markus Spiske on Unsplash
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-andrea-iannelli-ethz-learning-and-controlling-robustness-informativity-and-adaptation/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/04/data.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220609T100000
DTEND;TZID=Europe/Berlin:20220609T110000
DTSTAMP:20260615T115635
CREATED:20220428T093121Z
LAST-MODIFIED:20250604T092203Z
UID:11997-1654768800-1654772400@www.scienceofintelligence.de
SUMMARY:Dafna Burema; Mattis Jacobs (Science of Intelligence)\, “Workshop: Discussing Ethically Problematic “Incidents” of AI Systems”
DESCRIPTION:(In-person talk at Science of Intelligence) \nWorkshop: Discussing ethically problematic “incidents” of AI systems \nIn the Thursday morning talk\, we discuss ethically problematic incidents of AI that we selected from the AIAAIC Repository. In total\, we discuss four cases. \nIn a first step\, we present a brief overview what occurred in the respective cases\, based on media coverage. The audience is then invited to give a briefly assess the case: what went wrong? Which ethical values or principles were involved? How could the incident have been prevented? Who is responsible for what has happened and who could have prevented it? \nIn a second step\, we present how the respective case was assessed in the ethics-related academic literature and compare the assessment of the participants with the expert’s assessment. We conclude by inviting the participants to reflect on their own projects and potential problematic outcomes of their research. \n\nPhoto by Ehud Neuhaus on Unsplah
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-dafna-burema-matthis-jacobs/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/04/books.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220602T100000
DTEND;TZID=Europe/Berlin:20220602T110000
DTSTAMP:20260615T115635
CREATED:20220523T092237Z
LAST-MODIFIED:20240813T100915Z
UID:12113-1654164000-1654167600@www.scienceofintelligence.de
SUMMARY:Florian Blume\, Martin Maier\, Doris Pischedda\, Olga Wudarczyk-Markett and Murat Kirtay (Science of Intelligence)
DESCRIPTION:Abstract:\nSocial interaction and communication are supported by the integration of multimodal signals. One crucial social cue when interacting with other humans are facial expressions. In Project 8\, we study how people not only read information from faces\, but how they read meaning into faces based on context and prior knowledge. Incorporating sources of information in addition to what is actually visible (top-down processing) supports efficient\, robust\, context-adaptive visual perception. Neural networks designed to recognize facial expressions largely ignore such contextual information and are therefore inherently misaligned with human social perception. Closing this gap promises to make synthetic face processing at the same time more intelligent\, useful for human-machine interaction\, and ethically responsible. \nSuccessful social interaction relies on additional social factors and cognitive processes including partner co-representation (i.e.\, the representation of the partner’s actions alongside one’s own actions)\, emotion processing\, theory of mind (i.e.\, the ability to consider mental states – such as beliefs\, desires\, intentions – to predict people’s behaviour) and trust. In project 9\, we study processes underlying social communication in humans and assess potential changes in these processes when the interaction partner is an artificial agent. We use this knowledge to implement similar mechanisms in our robots and assess how this affects their performance along other dimensions\, such as trust or scaffolding. Our ultimate goal is to create robots with higher social intelligence that can interact smoothly with humans and other agents. \n  \n  \nPhoto by Yuyeung Lau on Unsplash
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-florian-blume-martin-maier-doris-pischedda-olga-wudarczyk-markett-and-murat-kirtay-2/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/05/zak-7wBFsHWQDlk-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220519T100000
DTEND;TZID=Europe/Berlin:20220519T110000
DTSTAMP:20260615T115635
CREATED:20220512T081828Z
LAST-MODIFIED:20240917T063052Z
UID:12054-1652954400-1652958000@www.scienceofintelligence.de
SUMMARY:Tilman Geishauer\, "Virtual Reality - From Research to Market"
DESCRIPTION:Abstract: Tilman Geishauser is currently working at Somareality to create a virtual reality focused product out of a cognitive load algorithm based on pupillometry that has been in development for 8 years at Research Studios Austria. In the past he invented one of Germanys most promising VR tools: Halocline Layout. He lead his team at what is now Halocline up until product launch. In his presentations he will talk about making products for virtual reality and about making products in cooperation with research institutions and universities.
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-tilman-geishauer-virtual-reality-from-research-to-market/
LOCATION:SCIoI\, MAR Building\, Marchstr. 23\, Berlin
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2022/05/Unknown.jpeg
END:VEVENT
END:VCALENDAR