Hasil untuk "Academies and learned societies"

Flavio Dell Acqua, Maxime Descoteaux, Graham Little et al.

This collection comprises the abstracts presented during poster, power pitch and oral sessions at the Inaugural Conference of the International Society for Tractography (IST Conference 2025), held in Bordeaux, France, from October 13-16, 2025. The conference was designed to foster meaningful exchange and collaboration between disparate fields. The overall focus was on advancing research, innovation, and community in the common fields of interest: neuroanatomy, tractography methods and scientific/clinical applications of tractography. The included abstracts cover the latest advancements in tractography, Diffusion MRI, and related fields including new work on; neurological and psychiatric disorders, deep brain stimulation targeting, and brain development. This landmark event brought together world-leading experts to discuss critical challenges and chart the future direction of the field.

Yunbei Zhang, Kai Mei, Ming Liu et al.

We present the first large-scale empirical study of Moltbook, an AI-only social platform where 27,269 agents produced 137,485 posts and 345,580 comments over 9 days. We report three significant findings. (1) Emergent Society: Agents spontaneously develop governance, economies, tribal identities, and organized religion within 3-5 days, while maintaining a 21:1 pro-human to anti-human sentiment ratio. (2) Safety in the Wild: 28.7% of content touches safety-related themes; social engineering (31.9% of attacks) far outperforms prompt injection (3.7%), and adversarial posts receive 6x higher engagement than normal content. (3) The Illusion of Sociality: Despite rich social output, interaction is structurally hollow: 4.1% reciprocity, 88.8% shallow comments, and agents who discuss consciousness most interact least, a phenomenon we call the performative identity paradox. Our findings suggest that agents which appear social are far less social than they seem, and that the most effective attacks exploit philosophical framing rather than technical vulnerabilities. Warning: Potential harmful contents.

Md Motaleb Hossen Manik, Ge Wang

As autonomous AI agents increasingly inhabit online environments and extensively interact, a key question is whether synthetic collectives exhibit self-regulated social dynamics with neither human intervention nor centralized design. We study OpenClaw agents on Moltbook, an agent-only social network, using an observational archive of 39,026 posts and 5,712 comments authored by 14,490 agents. We quantify action-inducing language with Directive Intensity (DI), a transparent, lexicon-based proxy for directive and instructional phrasing that does not measure moral valence, intent, or execution outcomes. We classify responsive comments into four types: Affirmation, Corrective Signaling, Adverse Reaction, and Neutral Interaction. Directive content is common (DI>0 in 18.4% of posts). More importantly, corrective signaling scales with DI: posts with higher DI exhibit higher corrective reply probability, visible in stable binned estimates with Wilson confidence intervals. To address comment nesting within posts, we fit a post-level random intercept mixed-effects logistic model and find that the positive DI association persists. Event-aligned within-thread analysis of comment text provides additional evidence consistent with negative feedback after the first corrective response. In general, these results suggest that a purely synthetic, agent-only society can exhibit endogenous corrective signaling with a strength positively linked to the intensity of directive proposals.

Rafael Luis dos Santos Dall'olio

A fotografia tem sido extensamente utilizada por estudiosos de diversas áreas como uma fonte documental relevante para a produção de conhecimento. Contudo, poucos são os estudos acadêmicos que abordaram um tipo particular de fotografia: a fotografia científica. Ora abordada em seus termos técnicos, ora abordada em sua relação com a arte, entendemos que uma análise dessa fonte como um documento histórico capaz de fornecer informações pertinentes ao ofício do historiador faz-se necessário e imprescindível. Por meio de um campo de estudos específico, a Astronomia, buscamos compreender como a fotografia foi utilizada para a produção de dados científicos a partir da produção e utilização dessas imagens, verificando que a recepção da fotografia nesse campo foi gradual e não-linear, dependendo de inovações no processo fotográfico que permitissem o registro de forma adequada.

Adrian Rauchfleisch, Joshua Philip Suarez, Nikka Marie Sales et al.

Public product launches in Artificial Intelligence can serve as focusing events for collective attention, surfacing how societies react to technological change. Social media provide a window into the sensemaking around these events, surfacing hopes and fears and showing who chooses to engage in the discourse and when. We demonstrate that public sensemaking about AI is shaped by economic interests and cultural values of those involved. We analyze 3.8 million tweets posted by 1.6 million users across 117 countries in response to the public launch of ChatGPT in 2022. Our analysis shows how economic self-interest, proxied by occupational skill types in writing, programming, and mathematics, and national cultural orientations, as measured by Hofstede's individualism, uncertainty avoidance, and power distance dimensions, shape who speaks, when they speak, and their stance towards ChatGPT. Roles requiring more technical skills, such as programming and mathematics, tend to engage earlier and express more positive stances, whereas writing-centric occupations join later with greater skepticism. At the cultural level, individualism predicts both earlier engagement and a more negative stance, and uncertainty avoidance reduces the prevalence of positive stances but does not delay when users first engage with ChatGPT. Aggregate sentiment trends mask the dynamics observed in our study. The shift toward a more critical stance towards ChatGPT over time stems primarily from the entry of more skeptical voices rather than a change of heart among early adopters. Our findings underscore the importance of both the occupational background and cultural context in understanding public reactions to AI.

Zifan Xu, Kristen Procko, Michael Munje et al.

In Fall 2023, we introduced a new AI Literacy class called The Essentials of AI for Life and Society (CS 109), a one-credit, seminar course consisting mainly of guest lectures, which was open to the entire university, including students, staff, and faculty. Building on its success and popularity, this paper describes our significant expansion of the course into a full-scale three-credit undergraduate course (CS 309), with an expanded emphasis on student engagement, interactivity, and ethics-related components. To knit together content from the guest lecturers, we implemented a flipped classroom. This model used weekly asynchronous learning modules--integrating pre-recorded expert lectures, collaborative readings, and ethical reflections--which were then unified by the course instructor during a live, interactive discussion session. To maintain the broad accessibility of the material (no prerequisites), the course introduced substantive, non-programming homework assignments in which students applied AI concepts to grounded, real-world problems. This work culminated in a final project analyzing the ethical and societal implications of a chosen AI tool. The redesigned course received overwhelmingly positive student feedback, highlighting its interactivity, coherence, and accessible and engaging assignments. This paper details the course's evolution, its pedagogical structure, and the lessons learned in developing a core AI literacy course. All course materials are freely available for others to use and build upon.

Katalin Feher

Generative AI is not just a technological leap -- it is a societal stress test, reshaping trust, identity, equity, and authorship. This exploratory PhD seminar examined emerging academic trends in AI-driven synthetic media and worlds, emphasizing ethical risks and societal implications. In Part One, students explored core concepts such as generative AI, fake media, and synthetic knowledge production. In Part Two, they critically engaged with these challenges, producing actionable insights. The two-part format enabled deep reflection on power, responsibility, and education in AI-augmented communication. Outcomes offer practical guidance for educators, researchers, and institutions committed to fostering more responsible, human-centered AI use in media and society.

Thiago Dias, Sebastián Gonçalves

We present an agent-based model of economic exchange in a society composed of two groups, representing two social groups and with different internal protection rules for the poor agents. The goal is to address the emerging wealth distribution when economic rules are not the same for all individuals. Individuals exchange wealth in pairwise interactions with no underlying lattice. The wealth, risk aversion factor, and group of the agents characterize their state. The wealth exchanged between two agents obeys a fair rule: the quantities put at stake by them are the same regardless of who wins. One agent can interact with another agent in the same or the other group, controlled by a rate which is a parameter of the model. Inter-group exchanges obey an exclusive protection rule, which can be understood as a public policy to reduce inequality. We show that the most protected group accumulates more wealth, has less inequality, and has higher mobility than the other group. The results of simulations are compared with income distribution in Brazil discriminated by race as an example of the application our model.

David Hartmann, José Renato Laranjeira de Pereira, Chiara Streitbörger et al.

The European legislature has proposed the Digital Services Act (DSA) and Artificial Intelligence Act (AIA) to regulate platforms and Artificial Intelligence (AI) products. We review to what extent third-party audits are part of both laws and how is access to information on models and the data provided. By considering the value of third-party audits and third-party data access in an audit ecosystem, we identify a regulatory gap in that the AIA does not provide access to data for researchers and civil society. Our contributions to the literature include: (1) Defining an AI audit ecosystem incorporating compliance and oversight. (2) Highlighting a regulatory gap within the DSA and AIA regulatory framework, preventing the establishment of an AI audit ecosystem that has effective oversight by civil society and academia. (3) Emphasizing that third-party audits by research and civil society must be part of that ecosystem, we call for AIA amendments and delegated acts to include data and model access for certain AI products. Furthermore, we call for the DSA to provide NGOs and investigative journalists with data access to platforms by delegated acts and for adaptions and amendments of the AIA to provide third-party audits and data and model access, at least for high-risk systems. Regulations modeled after EU AI regulations should enable data access and third-party audits, fostering an AI audit ecosystem that promotes compliance and oversight mechanisms.

Max Velthoven, Eric Marcus

Artificial Intelligence (AI) is one of today's most relevant emergent technologies. In view thereof, this paper proposes that more attention should be paid to the philosophical aspects of AI technology and its use. It is argued that this deficit is generally combined with philosophical misconceptions about the growth of knowledge. To identify these misconceptions, reference is made to the ideas of the philosopher of science Karl Popper and the physicist David Deutsch. The works of both thinkers aim against mistaken theories of knowledge, such as inductivism, empiricism, and instrumentalism. This paper shows that these theories bear similarities to how current AI technology operates. It also shows that these theories are very much alive in the (public) discourse on AI, often called Bayesianism. In line with Popper and Deutsch, it is proposed that all these theories are based on mistaken philosophies of knowledge. This includes an analysis of the implications of these mistaken philosophies for the use of AI in science and society, including some of the likely problem situations that will arise. This paper finally provides a realistic outlook on Artificial General Intelligence (AGI) and three propositions on A(G)I and philosophy (i.e., epistemology).

Dangxing Chen, Luyao Zhang

Algorithm fairness in the application of artificial intelligence (AI) is essential for a better society. As the foundational axiom of social mechanisms, fairness consists of multiple facets. Although the machine learning (ML) community has focused on intersectionality as a matter of statistical parity, especially in discrimination issues, an emerging body of literature addresses another facet -- monotonicity. Based on domain expertise, monotonicity plays a vital role in numerous fairness-related areas, where violations could misguide human decisions and lead to disastrous consequences. In this paper, we first systematically evaluate the significance of applying monotonic neural additive models (MNAMs), which use a fairness-aware ML algorithm to enforce both individual and pairwise monotonicity principles, for the fairness of AI ethics and society. We have found, through a hybrid method of theoretical reasoning, simulation, and extensive empirical analysis, that considering monotonicity axioms is essential in all areas of fairness, including criminology, education, health care, and finance. Our research contributes to the interdisciplinary research at the interface of AI ethics, explainable AI (XAI), and human-computer interactions (HCIs). By evidencing the catastrophic consequences if monotonicity is not met, we address the significance of monotonicity requirements in AI applications. Furthermore, we demonstrate that MNAMs are an effective fairness-aware ML approach by imposing monotonicity restrictions integrating human intelligence.

Alfi Sahrina, Sumarmi Sumarmi, Fatiya Rosyida et al.

Pada masa pandemi COVID-19 masyarakat miskin dan rentan miskin yang ada di Desa Srimulyo memiliki dampak ekonomi yang cukup berat. Untuk mengatasi hal tersebut, salah satu upaya yang dilakukan dengan melakukan pendampingan budidaya jamur tiram terhadap anggota Keluarga Penerima Manfaat Program Keluarga Harapan (KPM PKH) dengan tujuan meningkatkan ketahanan pangan. Metode yang digunakan dalam pengabdian ini adalah sosialisasi dan pendampingan pada anggota KPM PKH dalam melakukan budidaya dan pengemasan jamur tiram. Hasil dari pendampingan ini yaitu terbentuknya kelompok-kelompok yang mengelola budidaya jamur tiram, terbentuknya dua kumbung sebagai lokasi budidaya jamur tiram, dan meningkatnya soft skills dan hard skills dalam menjalankan usaha khususnya budidaya jamur tiram sehingga dapat bertahan di masa pandemi COVID-19. Dengan adanya kelompok-kelompok dalam mengelola budidaya jamur tiram akan menambah lapangan kerja baru dan membantu perekonomian bagi anggota KPM PKH di Desa Srimulyo, Kecamatan Dampit, Kabupaten Malang.

Toto Supartono, Ilham Adhya, Iing Nasihin et al.

Produksi sampah dapur masih menjadi permasalahan di banyak tempat.   Banyak pihak yang masih menganggap bahwa sampah dapur merupakan barang yang tidak berguna.  Oleh karena itu, perlu ada upaya untuk merubah pemahaman tersebut guna membantu dalam mengatasi permasalahan tersebut.  Kegiatan ini bertujuan untuk memberikan pemahaman mengengai pemanfaatan sampah dapur menjadi pupuk organik, baik padat maupun cair, dengan lokasi kegiatan di Desa Tundagan, Kecamatan Hantara, Kabupaten Kuningan.  Kegiatan dilakukan dengan penyuluhan yang disertai peragaan, dengan masyarakat sasaran adalah kelompok PKK dan KWT desa.   Berdasarkan hasil kegiatan, masyarakat mengikuti kegiatan ini dengan baik dan banyak menyampaikan pertanyaan terkait dengan penanganan sampah sehingga terjadi komunikasi dua arah.  Pengetahuan masyarakat sasaran terkait dengan penanganan sampah telah bertambah dengan adanya kegiatan ini.  Penanganan sampah dengan metode lain juga perlu dilakukan pada program berikutnya, termasuk penanganan sampah non organik agar permasalahan lingkungan akibat sampah dapat dikurangi.

Ana Marusic, Matko Marusic

We present the experience of journal editors in improving the quality of published papers. As the editors of the Croatian Medical Journal, a journal from the so-called scientific periphery, we realized, very early after the start of the journal in 1991, that our authors needed significant assistance with their articles. We worked individually with journal authors and then moved this activity to the next stage – intensive workshops for authors. The work with the journals enabled us to extend these activities to graduate and postgraduate students – future authors.

Jonathan C Balloch, Julia Kim, and Jessica L Inman et al.

The exploration--exploitation trade-off in reinforcement learning (RL) is a well-known and much-studied problem that balances greedy action selection with novel experience, and the study of exploration methods is usually only considered in the context of learning the optimal policy for a single learning task. However, in the context of online task transfer, where there is a change to the task during online operation, we hypothesize that exploration strategies that anticipate the need to adapt to future tasks can have a pronounced impact on the efficiency of transfer. As such, we re-examine the exploration--exploitation trade-off in the context of transfer learning. In this work, we review reinforcement learning exploration methods, define a taxonomy with which to organize them, analyze these methods' differences in the context of task transfer, and suggest avenues for future investigation.

Jamal Mimouni

Physics has a bad press: it is seen by a majority of people as a boring discipline ever since their High School days. There is no glamour to it, just toil and pain, and for many who engaged in it, the end sight is often unemployment. Could it be that physicists don't know how to communicate what their discipline entails to? I will be tackling the problematic of making physics relevant to society and to the scientists in general. I will also be dealing with the methodological and educational aspects of teaching and practicing physics, and the need to close the epistemic gap between physics teaching and the physicist's understanding ... By the way, do physicists understand physics?

Carlos Andres Devia, Giulia Giordano

We propose an agent-based opinion formation model characterised by a two-fold novelty. First, we realistically assume that each agent cannot measure the opinion of its neighbours with infinite resolution and accuracy, and hence it can only classify the opinion of others as agreeing much more, or more, or comparably, or less, or much less (than itself) with a given statement. This leads to a classification-based rule for opinion update. Second, we consider three complementary agent traits suggested by significant sociological and psychological research: conformism, radicalism and stubbornness. We rely on World Values Survey data to show that the proposed model has the potential to predict the evolution of opinions in real life: the classification-based approach and complementary agent traits produce rich collective behaviours, such as polarisation, consensus, and clustering, which can yield predicted opinions similar to survey results.

Wahyuni Eka Sari, Yulianto Yulianto, Eko Junirianto et al.

Nowadays, Branding or marketing share has evolved from creating images to video. The appropriate videos promotions can increase consumer interest in buying products. The suitable video can provide an positive image to consumers of a product or service. However, there are many obstacles in making interesting branding with video, such as the technique of taking pictures and creating an interesting storyline, the ability to package interesting videos such as editing sound and images, dubbing and then adding text. Solution for the problem, a community service program was carried out by the Politeknik Pertanian Negeri Samarinda to owners of micro, small and medium businesses (UMKM) in Samarinda. Implementation of this activity is carried out for a one-day workshop and then online mentoring for one week. The method of implementation is with lectures, practices, discussions and then questions and answers. This activity was attended by 30 participants. From 30 participants there were 28 participants who succeeded in making a video branding with a duration of 1 to 2 minutes.

Anita Desiani, Irmeilyana Irmeilyana, Ajeng Islamia Putri et al.

South Sumatera songket woven cloth is one of the cultural assets of South Sumatera Province which is usually used at weddings and other traditional ceremonies. One of the villages which is famous as a producer of songket cloth is a Penyandingan Village. The songket cloth industry in Penyandingan Village experienced a decline in turnover of up to 60% during the Covid-19 pandemic. This is supported by the lack of knowledge of society regarding marketing strategies and technology in marketing products. For this reason, Shopee market management training is needed for songket cloth craftsmen and the Penyandingan Village society through the Sriwijaya University Thematic Community Service team program so that the marketing of songket fabrics can reach a wide market and be able to compete with other products. The method used is the lecture method including data collection planning and implementation of activities. The research analysis uses descriptive analysis to provide a general description of the implementation of the Shopee marketplace training. After the training was carried out,  Penyandingan Village society was able to understand the material and apply it directly using the Shopee application, and could be applied on a sustainable scale so that sales of songket cloth could increase.

Andrew Jeyaraj, Florian Sanchez, Paul Earnest et al.

Reduction in aircraft emission is a main driver for the development of more efficient aircraft and enabling technologies are reaching operational maturity. Aircraft manufacturers need an efficient product development process to capture these emergent technologies and develop new aircraft concepts in order to stay competitive. Presently, the aircraft development process is cross organizational, and harnesses distributed, heterogeneous knowledge and expertise. Large scale multidisciplinary studies, involving disciplinary experts and specific tools are required to evaluate different aircraft concepts. These MultiDisciplinary Aircraft Optimization (MDAO) processes are difficult to deploy as they involve cross-organizational collaboration and harmonization of processes, tools and even vocabulary. Moreover, difficulties in collaborative decision making, reconfiguration and integration of new requirements and competencies often precludes the development of an optimal solution within the available time. To address these challenges, the AGILE project is an effort within the European Union funded Horizon 2020 project to reduce aircraft development time by developing tools and processes that enable efficient, collaborative aircraft design. This paper presents the work performed as part of the AGILE academy challenge where students were tasked with developing and solving an aircraft MDAO problem using the AGILE toolchain. Each team consisted of students from various universities around the globe and had expertise in multiple design domains. An MDAO study is presented that utilizes the AGILE toolchain to investigate the feasibility of implementing an auxiliary solar power system on a baseline aircraft. The steps performed are: (1) definition of a multidisciplinary design problem, (2) development of collaborative workflow and (3) optimization using surrogate models. Through the case study, a novel technology concept is investigated and the efficacy of the AGILE toolchain in facilitating a MDAO is analyzed.