Institutt for ledelse og organisasjon

Personality and Social Psychology Review Doi: https://doi.org/10.1177/10888683261430089

Academic Abstract Advances in AI require a revision of the psychological and socio-technical dynamics by which individuals are radicalized to embrace violent extremism. This review synthesizes process models of radicalization with research on social and personality risk factors, AI, and psychological mechanisms to propose a four-stage framework mapping the AI architecture of radicalization: (1) Exposure , where recommender systems and virality features create initial attraction to extreme content; (2) Reinforcement , where filter bubbles and group recommendations leverage biases to strengthen extremist beliefs and create echo chambers; (3) Group Integration , where ideologically homogenous clusters, AI bot swarms and companions foster group belonging and readiness for action; cumulatively resulting in (4) Violent Extremist Action . We examine how established social, cognitive, personality, and contextual vulnerability factors heighten psychological risk in the AI-driven radicalization process, as well as the emerging role of generative AI. We conclude by outlining a stage-based framework for governance and future research. Public Abstract AI-driven algorithms designed to maximize engagement on social media, compounded by generative AI, can unintentionally set the stage for radicalization. It begins with Exposure , where algorithms push users toward extreme content because it captures attention. Next, during Reinforcement , algorithms feed users personalized content while AI swarms can create a synthetic consensus that reinforces emerging biases, normalizes extremity, and insulates users from alternative views. Third, during Group Integration , individuals are absorbed into extremist networks, reinforced by human peers, AI companions, and bot swarms that validate radical beliefs and deepen identity ties. By exploiting psychological needs for belonging and certainty, this stage becomes particularly pernicious, potentially opening the door for violence. We propose policy measures that can reduce radicalization at each stage.

Magma forskning og viten 29(1) s. 79-87 Doi: https://magmaforskning.econa.no/index.php/magma/article/view/1524

Denne artikkelen presenterer og diskuterer konseptuelle rammeverk som ledere kan anvende for å vurdere når kunstig intelligens (KI) i form av språkmodeller kan bidra til bedre beslutninger. Utgangspunktet vårt er at teknologien bak KI i hovedsak bygger på prediksjonsmodeller, og at nytteverdien av disse vil være avhengig av hvilke typer beslutninger den anvendes på. Vi vil problematisere en utbredt antakelse om at språklig formulert informasjon kan likestilles med kunnskap i organisasjoner, og viser hvordan denne antakelsen kan føre til feil bruk av KI i ledelse. Vår diskusjon bygger spesielt på det såkalte Cynefin-rammeverket (uttales ku-nev-in) for å dele inn beslutningsoppgaver etter grad av forutsigbarhet, usikkerhet og årsakssammenhenger. Deretter knytter vi diskusjonen opp mot skillet mellom beregnelige problemer, estimerbare hemmeligheter og åpne mysterier. Til sammen utgjør disse begrepene et beslutningsheuristisk rammeverk for bruken av KI som støtte til analyse og prediksjon. Rammeverket åpner for å vise hvor menneskelig dømmekraft, fortolkning og koordinasjon må være viktigere enn teknologi. Artikkelens bidrag er tredelt. For det første argumenterer vi for at språkbasert KI er en teknologi som er avhengig av den epistemiske struktur i beslutninger. For det andre beskriver vi hvordan Cynefin-rammeverket kan fungere som et praktisk verktøy for avgrenset bruk av KI i organisasjoner. For det tredje illustrerer vi rammeverkets analytiske nytteverdi gjennom konkrete eksempler fra markedsføringsledelse, knyttet til medieallokering og etterspørselsplanlegging. Artikkelen viser at effektiv innføring av KI krever mer enn teknologisk kompetanse. Ledere må forstå forholdet mellom kunnskapsformer, prediksjon, forklaring og sosial samhandling. En sentral implikasjon er at ledere ikke bør starte med spørsmålet «hvordan kan vi bruke KI?», men med «hvilken type beslutningsproblem står vi overfor?».

Quality of Life Research 35(76) Doi: https://doi.org/10.1007/s11136-025-04103-w

Purpose Patient-centered care (PCC) improves quality of life, symptom management and healthcare outcomes in oncology. However, integration into routine cancer care remains limited. Digital solutions using patient-reported outcome measures (PROMs) offer a potential mechanism to operationalize PCC. This study explored healthcare professionals’ (HCPs) pre-implementation perspectives on using digital PROMs to support PCC in Norwegian oncology outpatient clinics, informing the design and implementation strategies of the European MyPath digital solution. Methods Semi-structured interviews (n = 29) and three focus groups (n = 16) were conducted with varied HCPs across four Norwegian hospitals. Interviews explored perceptions of PCC, experiences with PROMs, and requirements for digital implementation. Data were analyzed using thematic analysis, combining inductive and deductive coding guided by the TPOM framework. Results Four themes emerged: (1) balancing PCC with disease-centered practices, (2) integrating PCC into daily routines, (3) customization and patient acceptance of digital tools, and (4) combining patient-reported data with clinical autonomy. HCPs viewed digital PROMs as promising for facilitating PCC but emphasized that successful implementation requires workflow alignment, adaptable digital solutions, and strong stakeholder engagement. Concerns included patient digital literacy, workload implications, and overreliance on PROMs at the expense of direct patient interaction. Conclusion Our findings highlight a tension between HCPs’ needs for technical functionality and workflow alignment, and the support required to adapt their practice to fully realize PCC through digital tools. Integrating PCC successfully requires organizational, cultural, and workflow adaptations, alongside active HCP engagement in design and implementation. These changes are essential to reposition PCC as an integral rather than competing component of high-quality cancer care.

Italian Political Science 20(2) s. 113-138 Doi: https://doi.org/10.69101/IPS.2025.20.2.1

Recent shifts in migration governance – especially the externalization of border control and the strategic use of migration cooperation – demand systematic analyses of how states manage migration beyond their borders. Italy has emerged as a key actor in this domain, yet its external migration policies remain understudied. The DEPMI project addresses this gap by mapping and analysing Italy’s bilateral migration engagement with 28 countries across North Africa, Sub-Saharan Africa, the Balkans, the Middle East, and Asia between 2000 and 2024. It sheds light on the objectives, tools, and evolution of Italy’s external migration governance through two original datasets of over 140 bilateral instruments and 1,800 migration-related development cooperation pro- jects. Complemented by 28 country profiles and an interactive map, DEPMI provides a robust framework for comparative analysis and policy reflection. This article outlines the project’s aims and methodology, while pre- senting key research findings from the Sub-Saharan African context. It shows how the region, once peripheral, has become central to Italy’s migration diplomacy, with a strong emphasis on containment, returns, and the stra- tegic use of legal migration as diplomatic leverage.

Anthem Press