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<div xmlns="http://www.tei-c.org/ns/1.0"><head n="1.">Introduction</head><p>Artificial Intelligence (AI) is increasingly shaping the way we work, live, and interact, leading to significant developments across various sectors of industry, including media, finance, business services, retail and education. In recent years, numerous high-level principles and guidelines for 'responsible' or 'ethical' AI have been formulated. However, these theoretical efforts often fall short when it comes to addressing the practical challenges of implementing AI in real-world contexts: Responsible Applied AI.</p><p>The one-day workshop on Responsible Applied Artificial InTelligence (RAAIT) at HHAI 2024: Hybrid Human AI Systems for the Social Good in Malmö, Sweden, brought together researchers studying various dimensions of Responsible AI in practice.</p><p>This was the second RAAIT workshop, following the first edition at the 2023 European Conference on Artificial Intelligence (ECAI) in Krakow, Poland <ref type="bibr" target="#b0">[1]</ref>.</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="2.">Keynote speakers</head><p>The keynote speakers at the workshop were:</p><p>• Giovanni Leoni (Global Head of AI Governance Advisory at Credo AI) -Industry keynote: "Operationalizing AI Governance -a hands-on approach to Responsible AI"</p><p>• Olya Kudina (Assistant Professor at Delft University of Technology) -Academic keynote: "Ethics in AI: from assessment checklists to proactive practices"</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="3.">Accepted papers</head><p>Collectively, the RAAIT workshop received 8 submissions, 6 of which were accepted through a reviewing process. </p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="4.">Closing Remarks</head><p>Throughout the day, there was room for interactive sessions in which the participants reflected together how to bring the presented results, insights and methodologies effectively into practice. The day ended with a discussion on the major challenges for the field of Responsible Applied AI. To structure this discussion, we used a model that was created as part of the RAAIT methodology. The vision behind this model is that in order to put responsible AI in practice, we need to deal with the complex interactions between Technology, Organization(s) and People.</p><p>The organizers would like to express their gratitude to the keynote speakers, all the authors who submitted and/or presented their work, the RAAIT Program Committee members for their assistance in reviewing submissions, and the local organizing team and all the chairs of HHAI 2024.</p></div><figure xmlns="http://www.tei-c.org/ns/1.0" type="table" xml:id="tab_0"><head></head><label></label><figDesc>Contributions address instruments and tools for Responsible AI in practice, such as gamification and question matrices, technological approaches, including novel ways to track disinformation spread and training models on multiple labels, and case studies of Responsible AI in practice, including design workshops for a Public Service Media recommender system, and interviews around Explainable AI the financial sector. Here, we proudly present the papers accepted to the second edition of the annual workshop on Responsible Applied AI:</figDesc><table><row><cell>Rogue Algorithms: Using AI to track the spread of disinformation</cell></row><row><cell>• Benedetta Muscato (Scuola Normale Superiore and University of Pisa), Praveen</cell></row><row><cell>Bushipaka (Scuola Superiore Sant'Anna and University of Pisa), Gizem Gezici</cell></row><row><cell>(Scuola Normale Superiore), Lucia Passaro (University of Pisa) and Fosca</cell></row><row><cell>Giannotti (Scuola Normale Superiore): Multi-Perspective Stance Detection</cell></row><row><cell>• Maaike Harbers (Rotterdam University of Applied Sciences), Oumaima Hajri</cell></row><row><cell>(Autoriteit Persoonsgegevens) and Nathalie Stembert (Rotterdam University of</cell></row><row><cell>Applied Sciences): Responsible AI in Practice: A Case Study on Designing a PSM</cell></row><row><cell>Recommender</cell></row><row><cell>• Jenia Kim (University of Applied Sciences Utrecht), Henry Maathuis (University of</cell></row><row><cell>Applied Sciences Utrecht), Kees van Montfort (Amsterdam University of Applied</cell></row><row><cell>Sciences) and Danielle Sent (Jheronimus Academy of Data Science): Identifying</cell></row><row><cell>XAI User Needs: Gaps between Literature and Use Cases in the Financial Sector</cell></row></table><note>• Maria Inês Ribeiro (TU Eindhoven), Laura Genga (TU Eindhoven), Monique Simons (Wageningen University) and Pieter van Gorp (TU Eindhoven): Promoting Responsible and Trustworthy AI in mHealth: a Gamified Approach to Value-Sensitive Design • Sietske Tacoma (University of Applied Sciences Utrecht), Jimmy Mulder (University of Applied Sciences Utrecht), Matthieu Laneuville (SURF) and Stefan Leijnen (University of Applied Sciences Utrecht): A thought-provoking question matrix to guide the development of foundation-model-based applications • Jimmy Mulder (University of Applied Sciences Utrecht), Librecht Kuijvenhoven (University of Applied Sciences Utrecht), Stan Meyberg (University of Applied Sciences Utrecht) and Stefan Leijen (University of Applied Sciences Utrecht):</note></figure>
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<div xmlns="http://www.tei-c.org/ns/1.0"><head>Acknowledgements</head><p>The authors would like to acknowledge the SPRONG RAAIT project funded by SIA (for more information, please visit https://raait.nl).</p></div>
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