@techreport{BeanKearnsRomanouetal., type = {Working Paper}, author = {Bean, Andrew M. and Kearns, Ryan Othniel and Romanou, Angelika and Hafner, Franziska Sofia and Mayne, Harry and Batzner, Jan and Foroutan, Negar and Schmitz, Chris and Korgul, Karolina and Batra, Hunar and Deb, Oishi and Beharry, Emma and Emde, Cornelius and Foster, Thomas and Gausen, Anna and Grandury, Mar{\´i}a and Han, Simeng and Hofmann, Valentin and Ibrahim, Lujain and Kim, Hazel and Kirk, Hannah Rose and Lin, Fangru and Liu, Gabrielle Kaili-May and Luettgau, Lennart and Magomere, Jabez and Rystr{\o}m, Jonathan and Sotnikova, Anna and Yang, Yushi and Zhao, Yilun and Bibi, Adel and Bosselut, Antoine and Clark, Ronald and Cohan, Arman and Foerster, Jakob and Gal, Yarin and Hale, Scott A. and Raji, Inioluwa Deborah and Summerfield, Christopher and Torr, Philip H. S. and Ududec, Cozmin and Rocher, Luc and Mahdi, Adam}, title = {Measuring what Matters: Construct Validity in Large Language Model Benchmarks}, publisher = {arXiv}, doi = {10.48550/arXiv.2511.04703}, pages = {29}, abstract = {Evaluating large language models (LLMs) is crucial for both assessing their capabilities and identifying safety or robustness issues prior to deployment. Reliably measuring abstract and complex phenomena such as 'safety' and 'robustness' requires strong construct validity, that is, having measures that represent what matters to the phenomenon. With a team of 29 expert reviewers, we conduct a systematic review of 445 LLM benchmarks from leading conferences in natural language processing and machine learning. Across the reviewed articles, we find patterns related to the measured phenomena, tasks, and scoring metrics which undermine the validity of the resulting claims. To address these shortcomings, we provide eight key recommendations and detailed actionable guidance to researchers and practitioners in developing LLM benchmarks.}, language = {en} } @article{BonGibsonDariusetal., author = {Bon, Esmeralda and Gibson, Rachel and Darius, Philipp and Greffet, Fabienne and R{\"o}mmele, Andrea}, title = {What drives data-driven campaigning (DDC)? A comparative analysis of the institutional and organisational factors shaping the adoption of DDC in the French and German party systems}, series = {Swiss Political Science Review}, volume = {31}, journal = {Swiss Political Science Review}, publisher = {Wiley}, issn = {1424-7755}, doi = {10.1111/spsr.12652}, pages = {79 -- 101}, abstract = {This paper analyses the adoption of data-driven campaigning (DDC) by German and French parties in recent national elections using data from an original post-election survey of 27 parties (12 German, 15 French) and a new purpose-built DDC campaign index. Specifically, we investigate two main research questions: (1) Do countries and parties vary in the extent to which DDC is practised? (2) If so, what explains those differences? We find that while in both countries DDC adoption is limited in comparison to other campaign modes, differences exist across countries and parties based on a range of macro (systemic) and meso (organisation-level) factors. Most notably, contrary to normalisation theory, we find that minor parties with a 'netroots' base and newcomers who are digital 'natives' engage more in DDC than the 'legacy' major parties.}, language = {en} } @techreport{BreaughHammerschmidRackwitzetal., type = {Working Paper}, author = {Breaugh, Jessica and Hammerschmid, Gerhard and Rackwitz, Maike and Palaric, Enora}, title = {Research Report on Collaborative Management for ICT Enabled Public Sector Innovation}, pages = {103}, abstract = {The process of digitalising government is rapidly gaining speed, resulting in a pressing need for increased inter-governmental integration and challenging the traditional silo structures of government. This has sparked the adoption of inter-governmental collaborative working arrangements and efforts to develop joint standards and solutions; yet little is known about how exactly this manifests itself in the context of ambitious digitalisation projects. This report provides new empirical evidence on the challenges and dynamics of collaboration within and between public organisations in order to drive digital transformation. The report begins with a literature review on collaborative management with a particular focus on collaboration in the context of government digitalisation. This literature serves as a basis for developing a set of five propositions regarding how intergovernmental collaborative digitalisation projects can be best designed and managed. Following the conceptual framework of the TROPICO project deliverable 6.3 developed by Rackwitz et al. (2020), the report investigates the interplay between system context, collaboration challenges and dynamics (i.e. complexity, risk and power imbalances), public management interventions (i.e. institutional design and leadership) as well as outcomes. Emphasis is placed upon the role of institutional design and leadership in order to cope with the challenges inherent to collaborative governance approaches. The framework and related propositions are then verified through the use of empirical findings from ten comparative case studies from five European countries (Belgium, Denmark, Estonia, Germany, and the United Kingdom). The case studies, presented in detail in TROPICO deliverable 6.3, examine the development of national government-wide online portals, as well as the implementation of municipal Smart City initiatives. The cases show that the system dynamics and challenges of digitalisation projects, such as size and scope, tend to generate resource-intensive and demanding working conditions. Creating hybrid structures that incorporate both network and hierarchical approaches has been a common approach to handling these conditions and balancing the demands of inter-departmental collaboration with the inherent accountabilities and existing working cultures of public organisations. At the steering level, a central coordinator with collaborative leadership skills was found to be key to driving the projects forward and achieving outcomes. Participatory, network-style approaches at the working group level were successful in balancing the demands of all collaborative partners and encouraging wide-scale engagement. In addition, opting for wide-scale inclusion, setting ground rules and clear processes as well as a focus on trust and social capital development proved essential. While most leadership approaches still maintain elements of transactional leadership in managing projects, collaborative leadership approaches such as bringing stakeholders together, mediating problems, and guiding and steering the process were used in many instances to handle the complexities inherent in the project objectives. In the conclusion of the report, contributions are discussed, followed by an outline for future research avenues.}, language = {en} } @article{BreaughRackwitzHammerschmidetal., author = {Breaugh, Jessica and Rackwitz, Maike and Hammerschmid, Gerhard and N{\~o}mmik, Steven and Bello, Benedetta and Boon, Jan and Van Doninck, Dries and Downe, James and Randma-Liiv, Tiina}, title = {Deconstructing complexity: A comparative study of government collaboration in national digital platforms and smart city networks in Europe}, series = {Public Policy and Administration}, journal = {Public Policy and Administration}, doi = {10.1177/09520767231169401}, abstract = {This research deconstructs complexity as a key challenge of intergovernmental digitalisation projects. While much of the literature acknowledges that the fundamental restructuring coupled with technical capacity that these joint projects require leads to increased complexity, little is known about how different types of complexity interact within the collaborative process. Using established concepts of substantive, strategic, and institutional complexity, we apply complexity theory in collaborative digital environments. To do so, eight digital projects are analysed that differ by state structure and government level. Using a cross-case design with 50 semi-structured expert interviews, we find that each digitalisation project exhibits all types of complexity and that these complexities overlap. However, clear differences emerge between national and local level projects, suggesting that complexity in digitalisation processes presents different challenges for collaborative digitalisation projects across contexts.}, language = {en} } @incollection{Bryson, author = {Bryson, Joanna}, title = {The Artificial Intelligence of the Ethics of Artificial Intelligence: An Introductory Overview for Law and Regulation}, series = {The Oxford Handbook of Ethics of AI}, booktitle = {The Oxford Handbook of Ethics of AI}, editor = {Dubber, Markus and Pasquale, Frank and Das, Sunit}, publisher = {Oxford University Press}, isbn = {9780190067397}, doi = {10.1093/oxfordhb/9780190067397.013.1}, publisher = {Hertie School}, pages = {1000}, abstract = {Artificial intelligence (AI) is a technical term often referring to artifacts used to detect contexts for human actions, or sometimes also for machines able to effect actions in response to detected contexts. Our capacity to build such artifacts has been increasing, and with it the impact they have on our society. This does not alter the fundamental roots or motivations of law, regulation, or diplomacy, which rest on persuading humans to behave in a way that provides sustainable security for humans. It does however alter nearly every other aspect of human social behaviour, including making accountability and responsibility potentially easier to trace. This chapter reviews the nature and implications of AI with particular attention to how they impinge on possible applications to and of law.}, language = {en} } @incollection{Bryson, author = {Bryson, Joanna}, title = {The Past Decade and Future of AI's Impact on Society}, series = {Towards a New Enlightenment? A Transcendent Decade}, volume = {11}, booktitle = {Towards a New Enlightenment? A Transcendent Decade}, publisher = {BBVA}, isbn = {9788417141219}, publisher = {Hertie School}, abstract = {Artificial intelligence (AI) is a technical term referring to artifacts used to detect contexts or to effect actions in response to detected contexts. Our capacity to build such artifacts has been increasing, and with it the impact they have on our society. This article first documents the social and economic changes brought about by our use of AI, particularly but not exclusively focusing on the decade since the 2007 advent of smartphones, which contribute substantially to "big data" and therefore the efficacy of machine learning. It then projects from this political, economic, and personal challenges confronting humanity in the near future, including policy recommendations. Overall, AI is not as unusual a technology as expected, but this very lack of expected form may have exposed us to a significantly increased urgency concerning familiar challenges. In particular, the identity and autonomy of both individuals and nations is challenged by the increased accessibility of knowledge.}, language = {en} } @article{Bryson, author = {Bryson, Joanna}, title = {Europe Is in Danger of Using the Wrong Definition of AI}, series = {Wired}, journal = {Wired}, abstract = {Some intelligent systems are at risk of being excluded from oversight in the EU's proposed legislation. This is bad for both businesses and citizens.}, language = {en} } @article{Bryson, author = {Bryson, Joanna}, title = {Robot, all too human}, series = {XRDS: Crossroads, The ACM Magazine for Students}, volume = {25}, journal = {XRDS: Crossroads, The ACM Magazine for Students}, number = {3}, doi = {10.1145/3313131}, pages = {56 -- 59}, abstract = {Advanced robotics and artificial intelligence systems present a new challenge to human identity.}, language = {en} } @incollection{BrysonBogani, author = {Bryson, Joanna and Bogani, Ronny}, title = {Robot Nannies Will Not Love}, series = {The Love Makers}, booktitle = {The Love Makers}, editor = {Campbell, Aifric}, publisher = {Goldsmiths Press}, address = {London}, isbn = {97819126858442}, publisher = {Hertie School}, pages = {249 -- 258}, abstract = {How artificial intelligence and robotics are transforming the future of love and desire: a philosophical thriller and essays.A chance encounter between two women and a road trip into the future: It's Christmas Eve, and Scarlett, banker-turned-technologist, is leaving a secret underground lab to catch the last flight that will get her home in time to open presents with her three-year-old son. She offers a lift to a young woman in distress, who shares her intimate life story as they drive to the airport. These revelations will have devastating consequences for both of them. The Love Makers is a philosophical thriller about female friendship, class, motherhood, women, and work--and how artificial intelligence and robotics are transforming the future of love and desire. Aifric Campbell combines her novel with essays from leading scientists and commentators who examine what's at stake in our human-machine relationships. What is our future as friends, parents, lovers? Will advances in intelligent machines reverse decades of progress for women? From robot nannies to generative art and our ancient dreams of intelligent machines, The Love Makers blends storytelling with science communication to investigate the challenges and opportunities of emergent technologies and how we want to live. ContributorsRonny Bogani, Joanna J. Bryson, Julie Carpenter, Stephen Cave, Anita Chandran, Peter R. N. Childs, Kate Devlin, Kanta Dihal, Mary Flanagan, Margaret Rhee, Amanda Sharkey, Roberto Trotta, E. R. Truitt, and Richard Watson}, language = {en} } @incollection{BrysonEisenlauer, author = {Bryson, Joanna and Eisenlauer, Martin}, title = {Artificial Intelligence and ethics}, series = {Faster than the Future}, booktitle = {Faster than the Future}, publisher = {Digital Future Society}, address = {Barcelona}, publisher = {Hertie School}, pages = {57 -- 73}, language = {en} }