Open Projects

J.UCS - the Journal of Universal Computer Science - is an electronic journal that is the prototype for electronic publishing in the future. Using Hyper-G for distribution it provides all search and navigation mechanisms of large scale hypermedia systems and therefore makes it easy to locate interesting articles. Readers can perform variable scope searches to find papers, then they can browse them on screen either in hypertext mode or in high quality PostScript mode, or they can get high quality PostScript documents for printing. Even PostScript documents provide full hyperlink support when reading them on screen. Articles in J.UCS can be accessed very fast using a wide net of servers distributed all over the world. J.UCS also supports annotations to existing articles informing the readers of new research results or errors. Writing articles for J.UCS is very easy using PostScript as the main submission format, even standard hyperlinks such as literature references are generated automatically.

The development of innovative products from lignin, which comes as black liquor in a million-ton scale from pulp and paper production, has a huge potential to open new business areas. Despite significant efforts on national and international level, the vast majority of lignin is still subjected to incineration. Another societal challenge is a safe and sustainable supply with energy. While sustainable energy production has been addressed in the past years, sustainable energy storage still is an issue. Nowadays, most of the chemical storage technologies rely on depletable sources (e.g. metals), which need to be mined and transported to Europe, thereby causing a wide range of problems (e.g., disposal, sustainability, flammability etc.) In this project, a new value chain based on lignin (more precisely black liquor) is explored to generate sustainable, non‒inflammable redox flow battery electrolytes including aspects on recycling after end-of-life. For this purpose, processes will be designed to efficiently separate and pretreat the black liquor.

Digitalization efforts have led to massive sensor infrastructures embedded in the structure of objects, processes and spaces. The growing volume of data increasingly requires access to data anytime and anywhere. A wealth of data needs to be processed for this, often by drawing on collective expertise before a decision is made.

The learning process in clinical placements involves several actors such as tutors, supervisors, teachers, and students and during this complex process, tasks and mentorships must be done in a way that is synchronized with educational and clinical processes and embedded in the respective contexts. Only a structure that synchronizes processes and respective communication can prevent (some central problems) and ensure meaningful learning for students and appropriate care in the placement organizations. The project ‘4D (Determinants, Design, Digitalization, Dissemination) in the Digitalization of Learning in Practice Placement’ (4D Project) aims at addressing this gap by introducing mobile technology in practice placements, creating a bridge between the different actors involved to foster the best experience in practice-based learning in healthcare settings. The 4D project aims to address this goal by implementing the four main objectives: (i) to Determine the key factors (practice-based learning models) and the key elements (diffusion of innovation theories) to introduce mobile technology in practice placements, (ii) to co-Design a mobile learning application (app) for successful adoption of mobile technology in practice-based learning reflecting users’ core values and needs, (iii) to introduce Digitalization and to train the participating institutions through workshops and providing tutorials, (iv) to pilot and assess the use of mobile learning in practice placements in healthcare higher education in three different countries in Europe and (iv) to Disseminate the project findings as a inclusive approach to exchange and support the practice placement digitalization around universities EU Countries.

The goal of the project is to build upon a sensor instrumented fibre production line, by textile producer, and provide predictive quality information in a trustful way to operators an decision makers throughout the production pipeline so that humans can change the process immediately and avoid inferior quality outcomes. Through this optimisation energy loss and waste are avoided, as no costly upcycling needs to be performed on inferior goods. To achieve this AI based instrumentation of the production line, we want to close (i) causality gaps and (ii) measurement data gaps by using historic information. In a second step we want to build (iii) trustworthy embedded energy-efficient explainable AI tools into the process and (iv) provide counterfactual-based explanations for what-if analysis of the overall process. Finally, this should showcase, to others, how sustainability goals and traditional cooperate goals are not mutually exclusive and can be enabled by using advanced AI methods.

The project Pedestrian Strategy Styria aims to develop a strategy and a funding guideline for the design of pedestrian-friendly public spaces and to increase the share of walking in the municipalities of Styria. Increase the share of walking in the municipalities of the province of Styria. In particular, the (re)design of traffic areas is in focus.

Web search has become an essential technology and commodity, driving not only future innovations but forming a backbone for our digital economy. Regrettably, currently few non-European gatekeepers control Web search, which creates a biased, one-sided information access centred around economic success rather than the needs of citizens or European values and jurisdiction. This onesided ecosystem puts pressure on many small Web contributors from science, economy, art, culture, media and society requiring them to optimize their content for a few gatekeepers. A system greatly benefiting the gatekeepers thereby creates a vicious cycle, which leads to locked-in effects and a closed search engine market. To promote an open human-centred search engine market and provide a true choice to users when selecting search engines based on their own preferences, OpenWebSearch.EU proposes to develop and pilot the core of a European Open Web Index (OWI) and the foundation for an open and extensible European open Web Search and Analysis Infrastructure (OWSAI). Our approach is based on four objectives, namely (1) to develop a core suite of search, discovery and analytics services to create, maintain and utilize the OWI; (2) to develop relevant search engine verticals and new search paradigms demonstrating the impact; (3) to establish a network of European HPC-infrastructure, research and business organizations to pilot the OWSAI based on Europe’s values, principles, legislation, ethics and standards; (4) to stimulate an ecosystem around the OWI. The envisioned infrastructure will not only contribute to Europe’s sovereignty for navigating and searching the web, it will also empower Europe’s researchers, innovators and business to systematically tap into the Web as business and innovation resource, without paying huge upfront costs. This will be particularly crucial for future AI innovations and relevant for other European infrastructure like e.g. the European Open Science Cloud, GAIA-X.

In the light of the growing pressure to decarbonise our economies, hydrogen is attracting strongly increasing attention from researchers, industry, policy makers and the wider public. Although hydrogen has been described as a promising substitute for fossil fuels already in the 1970s, current enthusiasm about the energy carrier is unprecedented. A rising number of countries are implementing national hydrogen strategies, policies, and policy targets, and large corporations such as Toyota, Bosch, or Siemens present the hydrogen economy as the growth market of the coming decades. In addition, the recent war in the Ukraine strengthens hopes about hydrogen even further. While expectation and attention levels associated with hydrogen are rising, important inconsistencies exist in terms of how the production of hydrogen is envisioned. Casting a glance at already specified national hydrogen strategies shows that nations have very different expectations about the roles that fossil fuels will play in this production process. Germany and the UK are good examples in this regard. Whereas Germany focuses on hydrogen produced from renewable electricity (‘green’ hydrogen), the UK strategy places an additional emphasis on the production of hydrogen from natural gas that is combined with technological approaches that capture and store the resulting CO2 emissions (so-called ‘blue’ hydrogen). In the HydroFRAME project, the examples of Germany and the UK are used to better understand the processes by which nations develop desirable visions of sociotechnical futures. Conceptualizing the future images associated with the German and British hydrogen strategies as politically legitimized ‘imaginaries’, the following questions will be addressed: - What expectations and visions are associated with the emerging hydrogen imaginaries in Germany and the UK, and which framing processes in the policy arena have driven the formation of these imaginaries? - Which alternative or competing hydrogen visions exist in these countries, and what are the country-specific differences? - Which narratives are associated with the countries’ ‘incumbent’ natural gas imaginaries, and how do these narratives relate to the emerging hydrogen imaginaries? - How did the public framing of hydrogen futures in Germany and the UK evolve over time, and what has been the role of these framing processes in shaping the emerging hydrogen imaginaries? By shedding light on how the emerging future images associated with the German and British hydrogen strategies relate to discursive processes, the project gains important insight into the interplay between two different types of expectations: institutionally stabilised, and politically legitimized, expectations on the one hand, and expectations that are shared rhetorically through ‘language in use’ on the other. Furthermore, the project provides a decision basis for countries and regions that currently think about their own hydrogen futures.

The project result is a Virtual Reality Digital Twin environment of the test sites "My Smart City Graz" and "TU Graz - Innovation District Inffeld". The user can interactively operate and visualise energy-technical building simulations and Internet of Things monioring data of the districts. This will support all stakeholders in making our cities more climate-neutral, resilient, efficient and liveable.

Austria is heavily depending on natural gas and oil. Large urban DH networks in Vienna, Graz, Linz, and Salzburg are mainly based on combined heat and power plants (CHP) using natural gas. Other cities, such as Klagenfurt, are still relying on natural gas for covering peak loads. Since the use of renewable fuels and CHP will be very limited in the future, and the connection of more customers to the DH networks can be expected, significant amounts alternative heat sources such as heat pumps, waste heat, solar- and geothermal energy will be required to secure and decarbonize the DH supply. However, this is resulting in various challenges, especially related to the optimization of the building stock in terms of return temperatures and flexibilities, network hydraulics, bi-directional operation, the integration of seasonal storages, as well as consumer involvement and business models – there is very limited experience for existing urban DH networks. Also, the connected investment costs are very high and uncertainties regarding energy prices, availability of alternative heat sources and seasonal storages as well as implementation of retrofitting and optimization activities, leading to high risks. DeRiskDH will develop and demonstrate key enabling solutions on a technological and a strategic level as well as innovative business models towards building owners and end users for handling the technical challenges and minimizing the investment risk in alternative heat sources. Those solutions will be demonstrated and tested: Vienna: innovative control algorithms will be developed and demonstrated in an innovative secondary DH network, including a local waste heat source and bi-directional operation. In Graz, the aim is to reduce the DH network temperatures in order to increase the performance of the heat pump in a new district, with a focus domestic hot water preparation. In Linz, a quick assessment tool for assessing the potential of optimizing the building installations should be developed. Salzburg will perform an assessment of the DH network hydraulics, including cascading for a complete decarbonization strategy. For Klagenfurt the focus is on activating building flexibility measures, P2H and heat pump integration for peak load reduction.

Against the background of the necessity to create a sustainable mobility system, different mobility paths for the next decades will be developed and evaluated in this project. For this purpose, an interdisciplinary supported, multidimensional view on the future development of mobility in Styria will be taken, which considers both passenger and freight transport as well as implications for Styria as a production location. The future projections should be flexible enough to integrate recent materializing developments, to strengthen appropriate trends and to change course according to the principle of avoid-shift-improve. The projection period covers the next 20 years in line with the 2040 climate neutrality target at the federal level. The analysis will seek to answer the following specific questions, among others: - What new governance structures and tax needs are derived for spatial, urban, and transportation planning? - What are the requirements for the distribution patterns of housing, workplaces and infrastructure? - How do the different projections affect social inclusion and socio-spatial inequalities? - What is the significance of new social practices, such as the use of "Mobility as a Service" (MaaS) offerings, for the Styrian industry? The project approaches this issue through a broad-based, transdisciplinary backcasting process. With the participation of stakeholders, the neuralgic points of possible development paths are identified and quantitative projection calculations are validated. In addition, this project combines backcasting and scenario analysis in a contrasting and synthesizing way (a methodological approach that is quite innovative in international comparison).

The project COOL-KIT develops demonstrates and structures system solutions for the cooling of buildings, with a focus on the founders' period (Gründerzeit). Buildings from this period (approx. built 1850 to 1910) characterise the centres of many European cities and contain high-quality public and private functions. Climate change, densification and sealing are increasingly causing extreme summer situations in these central urban locations and are rapidly enhancing the need for overheating protection and active building cooling. Due to the lack of overarching approaches to cool this important group of buildings, the increasing use of inefficient individual cooling systems (mostly single split units) becomes an energy-related, acoustic and architectural burden. The cooling systems developed in the project are based on different cooling sources (ground, air, microgrids) and various active cooling techniques and components (activated intermediate ceilings, fan coils, radiators). Passive approaches such as shading or night ventilation are investigated as complementary measures. Predictive control technology ensures optimal control and the use of PV electricity a sustainable operation. Cooling system and operation designs are developed, taking into account the accessible synergies with the heating operation. Cooling ceilings are used to reduce heating system temperatures to increase the year-round efficiency and reduce district heating requirements. Selected system configurations are implemented in several buildings of the participating universities. Testing of different predictive control approaches will be performed on the test buildings using a digital twin, based on an IoT platform, followed by comprehensive energy and comfort related, economic, ecological and operational evaluations. The experience gained simulation studies, as well as market and stakeholder analyses lead to a modularly structured bundle of interdisciplinarily evaluated system solutions, the COOL-KIT. BIM models of the system concepts also enable subsequent projects to be configured in a technically and economically targeted manner with little processing effort.

Autism Spectrum Disorder (ASD) is a growing problem (1-in-44 children; 4:1 boys:girls) that causes debilitating cognitive issues. "Social blindness," an inability to recognize emotions in others, is a common problem that requires costly and limited 1:1/small-group therapy. This shortage of therapy is particularly concerning given the increasing number of ASD diagnoses, particularly in boys. To address this, there is a need to increase access to emotional recognition training/therapy for those with ASD, and at a lower cost. Our proposed solution is to virtualize emotional recognition training/therapy by combining three novel key elements (KE1-3): hyper-realistic and responsive avatars, computer vision, and programmed therapeutic methods. This creates a fully virtualized, two-way adaptive, and individualized therapy that can be extended, gamified, and used for further research. Our hypothesis is that this technology solution can be ≥80% as effective as one-to-one therapy with ASD therapists, increasing access to basic care and augmenting/reinforcing current therapy. The outcome is a highly extensible software-based platform technology solution that dramatically increases access and scalability, lowers costs, and creates new insights/pathways in ASD research.

Although there seems to be broad support for a transformation to a hydrogen-based economy, there are different expectations regarding the implementation and design of such an economy. For instance, hydrogen is often seen as an environmentally friendly substitute for fossil fuels, allowing us to maintain our current (globalized) consumption and production patterns in the future. However, hydrogen is also often associated with energy independence from nation states and individual regions. Finally, there are visions that associate a future hydrogen economy with a democratization of the energy system as well as with an establishment of decentralized post-growth societies. There are also different expectations with regard to the production of hydrogen. For example, while some countries focus exclusively on green hydrogen in their hydrogen strategies (i.e. hydrogen produced by electrolysis and renewable electricity), other countries push the production of hydrogen from fossil fuels in combination with carbon (dioxide) capture (blue or turquoise hydrogen). Against this background, this project explores the opportunities available to the Styrian region in terms of increased hydrogen use (and associated R&D&I activities). As in basically all processes of socio-technical change, different logics - and thus different visions of the future - come together in the use of hydrogen. The aim of this project is to map them systematically and to confront them critically with considerations of feasibility. The central result is therefore the description and evaluation of potential future paths for the Styrian region as well as the comparison of these with current R&D&I activities and with developments in the larger context (Austria, EU, global). The results of this research project can subsequently be used as a basis for the continuous design of a Styrian future strategy in the field of hydrogen. Specifically, the following questions will be addressed: - Which different hydrogen visions are discussed in the Styrian context and how are these visions evaluated by experts and stakeholders? - What are the opportunities and risks for those private-sector actors who are to drive this transformation forward? - What socioeconomic effects can be expected? - Which synergies between potential future paths in the field of hydrogen and other Styrian R&D&I activities (in related topics) can be identified? To answer these questions, possible hydrogen future paths for Styria are formulated based on (i) focus groups with stakeholders, (ii) a systematic literature loyalty analysis, and (iii) an analysis of public discourses. Afterwards, these future paths will be critically discussed and evaluated in an exchange with experts and stakeholders. For this purpose, multi-criteria analyses will be performed and causal loop diagrams will be developed. The multi-criteria analyses are based on the Multicriteria Mapping (MCM) approach, which makes it possible to include a variety of relevant perspectives and to systematically illuminate competing views. The causal loop diagrams are based on systems mapping approaches and allow to embed the respective development paths into economic questions.

The Grand Challenge ahead is to shift fossil-dominated centralized energy systems towards regenerative integrated multi-vector grids. This requires also sustainable electrical energy storage, including the related raw material supply, processes and systems. A real impact on economy, society and ecology is only created if materials, processes and products can be potentially transferred to large scale. This represents a particular challenge for mid to long term, systems-integrated energy storage, also because the EU strongly depends on critical raw materials from politically instable regions. In VanillaFlow, we develop radically new approaches for integrated energy storage which combine artificial intelligence (AI) and machine learning (ML) with flow battery technology to replace currently employed, non-sustainable, and critical raw materials (i.e. redox-active molecules, membranes) in flow batteries by readily-available renewable materials based on starch and lignocellulosics. VanillaFlow will use AI and ML techniques such as physics-informed modeling, causal discovery, and representation learning, and makes use of deep learning and symbolic regression. These approaches are used in designing redox active quinones, and to optimize their interplay with the other components of a battery on single and multi-cell level. The whole research will be guided by toxicology investigations to ensure that sustainable and inherently safe materials will be obtained in the project. Today, the innovation capacity of European scientists and industry in the area of renewable materials makes them already the leading global players in the field. VanillaFlow will further support the European technological leadership in the area by cross-fertilization of different fields (artificial intelligence, battery technology, pulp and paper, biotechnology, polymer technology, toxicity) while addressing needs of sustainable materials in mid to long term energy storage.

The automotive industry has long been at the forefront of advances in automation. Modern assembly lines and supply chains are almost completely automated. Recent advances in data science and digitization have led to intelligent systems where data across the heterogeneous system landscape is becoming a major source of innovation. The complex data-driven discipline of vehicle development is supported by complex cyber-physical systems of systems (CPSoS) manifested by vehicle testbeds. However, novel propulsion systems are forcing the automotive industry to act faster than ever before. Development efficiency is the key and includes not only rapid development, but also the economical use of resources. HybridAIR aims to significantly increase the efficiency of CPSoS operation by introducing intelligent systems in the form of self-adaptive explainable recommender systems for different stakeholders applied on testbeds. Problem to solve: How can we cope with a constantly increasing volume of data and ever-growing data exchange within a multi-stakeholder and heterogeneous IT landscape (H2H, H2M, M2M)? How can we profitably turn around the associated challenges to create a source of knowledge from the many (informal) data sources, which not only mitigates the increasing complexity but even further increases efficiency? More concrete, how can we provide explainable, stakeholder-specific, high-quality, and context-aware decision support for testbed developers and testbed operators (DevOps), based on existing, shared data sources enriched with contextual information in their respective fields? How to build a generic, reusable infrastructure portable to reach a broad user group, whose respective knowledge is profitably reinforced?

This project aims to present development options and potentials for carbon management in Styria, to locate the most important stakeholders along the value chain and to derive future paths and recommendations for action for the Styrian research and development community and for industrial applications.

With population growing rapidly and within the context of agro-climatic changes, there is an increased demand to sustainably produce nutritious food. In Europe, many nutrient-dense foods are not widely grown and consumed, despite their suitability to European climates and environments, and viability for sustainable production with lower inputs. Underutilised crops that are stress resilient such as rye and legumes, have the potential to supply key nutrients and improve diets and risk of diet-related diseases. Such crops have a long history of cultivation across the continent and are part of the national historic food identity of different European countries yet are underutilised due to several complex reasons. DIVERSICROP addresses these challenges using an innovative, cross-sectoral and multidisciplinary approach by analysing the deep history of underutilised crops in Europe, understanding the genetic diversity and adaptation to climate change of crop germplasm, analysing current regional trends in the consumption of food products and by involving national and EU policymakers and key stakeholders to revive diverse crop production and maximise the impact of Europes agricultural sustainability. DIVERSICROP aims to harmonise fragmented data and develop strategies for the sustainable cultivation of target crops, striking a balance between agricultural sustainability and human nutritional value. DIVERSICROP brings together a skilled and interdisciplinary network to identify climate-resilient crop lines, and potential nutritional and health benefits of their consumption to rethink our food systems. DIVERSICROP will strengthen the Farm to Fork and the Biodiversity strategies under the European Green Deal to contribute to achieving the UN Sustainable Development Goals.

Prototypical development of collaborative web tools.

Climate change adaptation measures such as green infrastructure (GI) are becoming increasingly important in urban water management and urban planning. GI have a microclimatic cooling effect, which reduces heat islands and improves the quality of life in urban areas. However, this natural cooling effect can only be achieved if sufficient water is available for the plants used. This project investigates the water demand of green infrastructures, which is required to maximize their multifunctionality (e.g. cooling effect and increase of biodiversity). The identification of alternative water resources, the quantitative availability, the qualitative requirements and a cost-benefit analysis of the use of alternative resources for the irrigation of GI will also be carried out. Urban development scenarios for climate change-adapted greening are derived for representative case studies in Austria. These scenarios support the restoration of the local water balance and form the basis for irrigation demand forecasting models based on machine learning methods. These models are used to forecast irrigation requirements taking climate change into account. The simulations are intended to show the effects of the medium and long-term irrigation requirements of GI in urban areas on the drinking water supply. In addition, the potential of using alternative water resources to save drinking water in the long term will be determined and thus contribute to a more efficient use of drinking water and to the long-term security of water supply in Austria.

ECOCredGT aims to build capacities in Vocational Education and Training (VET) Institutions towards the creation of an ecosystem of Digital Credentials. This ecosystem of Digital Credentials is expected to have a positive impact on the promotion of employability. The capacity building generated thanks to ECOCredGT will strengthen the basis for exploring the future issuance of Digital Credentials for undergraduate and graduate degrees in a validated ecosystem with international recognition and interoperability. ECOCredGT is implemented mainly in Guatemala with the support of European partners from Spain and Austria. As such ECOCredGT will establish a National Model of Digital Credentials thanks to the cooperation between Guatemalan and European partners. The action seeks to promote digital transformation in the region by establishing a national center in Guatemala for issuing Digital Credentials. The project seeks to be a benchmark and establish a replicable model in other countries in the region. The specific objectives of ECOCredGT are: - To contribute to capacity building in VET Institutions towards a digital transformation. - To build a digital credential issuing center model replicable to other VET institutions. - To conduct pilot projects for vocational and professional micro-courses that promote employability. - To generate a link between VET and society, through a process of raising awareness of the importance of digital credentials and updating training plans for professionals to meet the challenges of the 4th industrial revolution. - To create an observatory of digital credential issuing centers to generate a community to share best practices, success stories and training in the region. In the short term, the project seeks to promote employability in the countries of the region by raising awareness on the proper use of Digital Credentials. It also seeks to identify the perception of recruiting agencies and human resources specialists on Digital Credentials.

The provision of scientific knowledge is of great importance for social decision-making processes. The challenge here is to make data and facts on pressing social issues available to citizens and politicians. A technology assessment will examine new ways of evaluating and analyzing personal information using artificial intelligence while fully respecting the right to privacy can be carried out in a socially acceptable manner

The Styria 2030+ walking strategy forms the foundation for the expansion of active mobility in Styria. The province of Styria is thus laying the foundation for the design of pedestrian-friendly public spaces in order to increase the number of journeys made on foot. In a one-year pilot phase, the Styrian municipalities are called upon to to plan and ultimately implement concrete measures based on the strategy. The pilot phase for planning and implementing initial measures in the Styrian municipalities is being scientifically supported by the STS Unit at TU Graz. Transcripts, recordings and other materials from the planned "pedestrian traffic tables" as well as interviews with the participating municipalities will be used for a qualitative study. A final report will summarize the findings from the pilot phase and recommendations for action for the province of Styria will be derived. The aim of the project is to accompany the implementation process of the Styria 2030+ walking strategy in the Styrian municipalities, to document and analyze it. The results from the report facilitate the further process of implementing the Styrian walking strategy in the municipalities.

This project aims to leverage scalable, digital ways of learning as the means to move forward the green transition through increased awareness of and knowledge on green entrepreneurship. The main outcome of this project will be that green entrepreneurs - i.e., people who are interested in or already engaged in developing new business models and processes with a focus environmental sustainability - can improve their competences in an innovative, easy-to-access online learning environment. This project targets the European working population, as well as the European population in preparation for (re-)entering the workforce, such as higher education students or learners in vocational training. Participants will develop their ability to analyse existing business models and processes for environmental impact and to develop further ideas on how to improve environmental sustainability. Co-creatively, the consortium will develop a multilingual AI-enriched online learning course. In this course, learners will progress from reading the teaching materials, to answering quiz questions, to discussing open-ended questions with the tutorial agent about cases, to being invited to chat with like-minded peers. This approach is innovative: It connects the strength of the i) current standard in online courses (multimedia content, interactive quizzes) with the strength of ii) existing teaching standards, (case-based teaching), with iii) new developments in AI for education, i.e., conversational agents as interactive tutors. Finally, iv) it serves as a social platform where distributed learners can connect for content-related discussions. The project directly supports the green transition through green entrepreneurship training. It supports the digital transformation of vocational and professional learning through an innovative and highly- scalable approach to teaching and learning green entrepreneurship.

The aim of the proposed study on the technology assessment of artificial intelligence (TA study) is to assess the socio-economic potential of AI-based recommender systems. In particular, opportunities for regional value creation and sustainable development are to be discussed. The results of the TA study provide a basis for software developers and political decision-makers alike. Recommender systems support economic decisions by providing information on selected products and services. This mediation service is all the more useful the more confusing the offer is and the better the selection provided can be tailored to the individual needs and preferences of the information seeker. At the same time, the use of AI-supported recommender systems raises important questions of fairness. What criteria are used to evaluate the actors and offers involved and does the provision of recommendations lead to unintentional discrimination against individual interest groups? As Snoboli et al. (2022) argue, the definition of fairness itself is a multi-stakeholder problem that must be negotiated between the groups involved. The proposed TA study takes up this problem and explains it on the basis of a concrete AI development. The results of the proposed study will be incorporated into the development of recommendations for AI-based recommender systems. These recommendations will be communicated to software developers in the form of design guidelines and made available to policy makers in the form of policy briefs.

Bilateral AI provides the means to develop the foundations of “broad AI”, a new level of AI with considerably enhanced and broader capabilities for skill acquisition and problem solving, by combining sub-symbolic AI (machine learning, ML) with symbolic AI (knowledge representation and reasoning, KRR). Bilateral AI will leverage the synergy from combining these AI fields.