Violence risk assessment is an internationally recognised methodology, aimed to manage different forms of violence. Most risk assessment tools, as is the case of the reviewed one, are designed to protect victims in the context of pressure, little time, or little information. This paper presents a reply to Valdivia et al. (AI & Society, July 2024) criticism of the algorithm for intimate partner violence risk assessment—EPV—used in the Basque Country. They concluded that more than 50% of high-risk victims are in danger, using results from a pilot version of the instrument, not the reviewed one published in 2010, nor the system in use since May 2013. In addition, qualitative information from a single professional generates global criticisms of the tool. Neither the current cut-off points nor the real weighting of the items nor the real risk management procedure are considered, and the personal opinion of a judge is assumed to be better than the use of tools when the accumulated research shows the opposite. When EPV risk assessment reports are used in courts, they may only temporarily affect some perpetrator rights, imposing restraining orders or, in the worst case, pretrial prison waiting for sentence. However, risk management can save the life of the victim. Cautions and suggestions related to the judicial context, such as improving risk reports or training judicial professionals, are shared. However, Valdivia et al.’s paper leads to misconceptions that extend to different sectors when echoing the wrong conclusions of their paper.

This article explores how the emergence of creative AI technologies transforms creative workers’ self-apprehension in the context of critical theory and labor studies. The distinguishing contribution of this study resides in its focus on how CI laborers’ creativity perception and reception are affected by AI technologies’ intrusion into the creative domain. Creative AI technologies are expected to present new expressive capacities to creative workers and cost-cutting advantages for CIs’ production that put a lot of creative jobs at risk. Findings show that creatives perceive the adaptation of AI technologies as both an opportunity for their creative process and a requirement of their active presence in the market survival as a matter of technocratic rule. We critically analyze creative labor’s novel mods engaged with updated technology and present reflections on the favorable co-creation conditions to flourish an understanding of socially intelligible technology and thereby a creative livelihood against technocracy.

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Artificial intelligence (AI) systems will increasingly be used to cause harm as they grow more capable. In fact, AI systems are already starting to help automate fraudulent activities, violate human rights, create harmful fake images, and identify dangerous toxins. To prevent some misuses of AI, we argue that targeted interventions on certain capabilities will be warranted. These restrictions may include controlling who can access certain types of AI models, what they can be used for, whether outputs are filtered or can be traced back to their user, and the resources needed to develop them. We also contend that new restrictions on non-AI capabilities needed to cause harm will be required. For example, concerns about AI-enabled bioweapon acquisition have motivated efforts to introduce DNA synthesis screening. Though capability restrictions risk reducing use more than misuse (resulting in an unfavorable Misuse–Use Tradeoff), we argue that interventions on capabilities are warranted in some circumstances when other interventions are insufficient, the potential harm from misuse is high, and there are targeted interventions. We provide a taxonomy of interventions that can reduce AI misuse, focusing on the specific steps required for a misuse to cause harm (the Misuse Chain), and a framework to determine if an intervention is warranted. We exemplify our framework to three examples: predicting novel toxins, creating harmful images, and automating spear phishing campaigns.

Generative AI has captured the public imagination as a tool that promises access to expertise beyond the technical jargon and expense that traditionally characterize such infospheres as those of medicine and law. Largely absent from the current literature, however, are interrogations of generative AI’s abilities to deal in culturally responsive communication, or the expertise interwoven with culturally aware, socially responsible, and personally sensitive communication best practices. To interrogate the possibilities of cultural responsiveness in generative AI, we examine the patterns of response that characterize ChatGPT-3.5’s advice for coming out. Specifically, we submitted 100 prompts soliciting coming out advice to GPT-3.5, variegating each of those prompts slightly to account for intersectional identities. From the analysis, we find that, while the responses are largely in-line with best practices, there are also instances that might represent problematics concerning the interpellation of the user or the persons to whom one is coming out.

This article assesses the exploration of the utopian paradigm within the context of technological advancement and its implications for human labor. It engages in this reflection, beginning with John Danaher’s reading of utopian perspectives related to the evolution of the labor domain, and then focusing on the significance of the social element and its dynamics in redefining labor and productive structures. It focuses on utopia as a regulatory ideal, valuing the conjectural contributions from theories throughout the history of utopian thought. The analysis aims to understand how utopian theories arise in contexts of social dissatisfaction, prompting internal reflection on the structure. The article is organized into three sections: the first introduces the concept of utopia, tracing its historical and philosophical roots, with a focus on influential figures such as Henri de Saint-Simon and Charles Fourier. Through the study of nineteenth-century social theories, the article explores their radical proposals for societal restructuring in response to the socio-economic upheavals of their time. The second section examines utopia as a form of social critique, emphasizing its critical function in assessing and guiding societal development, by engaging with Norbert Elias’s definitions of utopia. The third section evaluates the relevance of utopia in contemporary discourse on social change, emphasizing the critical examination of utopian visions in relation to the concept of the end of work and aiming to articulate clear parameters defining a utopian model as a social regulatory ideal.

The current debate on artificial intelligence (AI) tends to associate AI imaginaries with the vision of a future technology capable of emulating or surpassing human intelligence. This article advocates for a more nuanced analysis of AI imaginaries, distinguishing “strong AI narratives,” i.e., narratives that envision futurable AI technologies that are virtually indistinguishable from humans, from "weak" AI narratives, i.e., narratives that discuss and make sense of the functioning and implications of existing AI technologies. Drawing on the academic literature on AI narratives and imaginaries and examining examples drawn from the debate on Large Language Models and public policy, we underscore the critical role and interplay of weak and strong AI across public/private and fictional/non-fictional discourses. The resulting analytical framework aims to empower approaches that are more sensitive to the heterogeneity of AI narratives while also advocating normalising AI narratives, i.e., positioning weak AI narratives more firmly at the center stage of public debates about emerging technologies.

In developing nations, the implementation of Foundational Identity Systems (FIDS) has optimised service delivery and inclusive economic growth. Cross-border e-government will gain traction as developing countries increasingly look to identity federation and trustworthy interoperability through FIDS for the identification and authentication of identity holders. Despite this potential, the interoperability of FIDS in the African identity ecosystem has not been well-studied. Among the difficulties in this situation are the intricate internal political dynamics that have led to weak institutions, suggesting that FIDS could be used for political purposes; additionally, citizens’ or identity holders’ habitual low trust in the government raises concerns about data security and privacy protection. Similarly, vendor lock-in, cross-system compatibility, and ambiguous legislative rules for data exchange are other concerns. Interoperability is fundamentally necessary as a precondition for e-government services and serves as the foundation for the best possible service delivery in the areas of social security, education, and finance, as well as gender equality as demonstrated by the European Union (EU). Moreover, the integration of cross-border FIDS and an ecosystem of effective data governance will be created by unified data sharing via an interoperable identity system. Thus, in this study, we point to the challenges, opportunities, and requirements for cross-border interoperability in an African setting. Furthermore, we investigated current interoperability solutions such as the EU’s eIDAS and Estonian X-Road and proposed an approach for scoping requirements to achieve a fully functional interoperable identity ecosystem in the African setting. Our findings show that interoperability in the African identity ecosystem is essential for expanding the scope of e-government throughout the continent and for bolstering the smooth authentication and verification of identity holders for inclusive economic growth.

Artificial General Intelligence (AGI) is said to pose many risks, be they catastrophic, existential and otherwise. This paper discusses whether the notion of risk can apply to AGI, both descriptively and in the current regulatory framework. The paper argues that current definitions of risk are ill-suited to capture supposed AGI existential risks, and that the risk-based framework of the EU AI Act is inadequate to deal with truly general, agential systems.