SAT: a methodology to assess the social acceptance of innovative AI-based technologies

Purpose The purpose of this paper is to present the conceptual model of an innovative methodology (SAT) to assess the social acceptance of technology, especially focusing on artificial intelligence (AI)-based technology. Design/methodology/approach After a review of the literature, this paper presents the main lines by which SAT stands out from current methods, namely, a four-bubble approach and a mix of qualitative and quantitative techniques that offer assessments that look at technology as a socio-technical system. Each bubble determines the social variability of a cluster of values: User-Experience Acceptance, Social Disruptiveness, Value Impact and Trust. Findings The methodology is still in development, requiring further developments, specifications and validation. Accordingly, the findings of this paper refer to the realm of the research discussion, that is, highlighting the importance of preventively assessing and forecasting the acceptance of technology and building the best design strategies to boost sustainable and ethical technology adoption. Social implications Once SAT method will be validated, it could constitute a useful tool, with societal implications, for helping users, markets and institutions to appraise and determine the co-implications of technology and socio-cultural contexts. Originality/value New AI applications flood today’s users and markets, often without a clear understanding of risks and impacts. In the European context, regulations (EU AI Act) and rules (EU Ethics Guidelines for Trustworthy) try to fill this normative gap. The SAT method seeks to integrate the risk-based assessment of AI with an assessment of the perceptive-psychological and socio-behavioural aspects of its social acceptability

<i>E</i>-3-aril-2-(1<i>H</i>-benzotriazol-1-il)acrilonitrili: una nuova classe di inibitori della tubulina ad attività antitumorale

Da lungo tempo ci occupiamo di derivati dei E-3-aril-2-(1-H-benzotriazol-1-il)acrilonitrili [3, 4, 5], che hanno dimostrato una interessante attività antiproliferativa nei confronti dei tumori umani solidi e liquidi, in alcuni casi superiore a quella dei farmaci di riferimento 6-mercaptopurina ed etoposide. Si è voluto quindi verificare se l’attività antiproliferativa dimostrata da questa classe di sostanze fosse dovuta ad una inibizione della funzionalità della tubulina. I risultati ottenuti hanno evidenziato che questo tipo di struttura si lega all’interno “del sito della colchicina” della β-tubulina con un energia libera di legame ΔGbind favorevole all’interazione. L’obiettivo della ricerca è stato quello di individuare all’interno della classe il lead compound sul quale apportare le modifiche che consentano la massima efficacia nell’interazione al sito della tubulina con conseguente miglioramento dell’attività antiproliferativa

Preserving authenticity evidence to assess provenance and integrity of digital resources

During their lifecycle, digital resources, notably digital representation of artistic work, may often go through changes of custody, format migrations and other changes of their representation. This may pose a threat to the integrity of their intellectual content and makes it difficult to trace their provenance. The paper addresses the crucial problem of gathering and preserving the evidence that would allow, at a later time, to properly assess the authenticity, the provenance and the integrity of these resources. The solution that we propose is based on the definition of special XML structures to preserve the authenticity evidence, which are compliant with PREMIS Data Dictionary, a widely acknowledged standard in the digital preservation community, and hence guarantees a sound basis for the interoperability among different repositories. © 2013 Springer-Verlag

Modelling Data Value in Digital Preservation: Paper - iPres 2013 - Lisbon

For decades, the Earth Science (ES) community has launched missions to monitor vital phenomena of our planet and, through measurements, obtain data for improving their models. Indeed the proper characterisation of phenomena, such as desertification, Arctic sea ice melting, volcanic activities or earthquakes effects, requires the analysis of data acquired in a long period and the validation of correctness of scientific models. This means that digital data, especially in the ES domain, represents an important asset to be preserved over time. Despite each single ES mission’s cost being quantified and supported by well documented evidence, ES organisations are not able to assess the value of data generated by those missions over time. This paper describes the rationale for and an approach to modelling the value of data/information to be preserved over long term in digital archive. This is the result of experience in the SCIDIP-ES project [16] which has considered the: i) definition of models for describing the value of digital data and related information; ii) characterisation of data/information value model through core set of key parameters and iii) identification of long term digital preservation activities that may potentially impact on key parameters and consequently on the value of digital assets. This model is being assessed in ES scenarios with data curators and archive managers