Potere Computazionale

Deleghiamo decisioni e compiti ad agenti artificiali, meccanismi d’apprendimento automatico, procedure algoritmiche, in breve, a sistemi computazionali. Tutto ciò non vuole portarci sulla Luna, rimpiazzare gli esseri umani con legioni di androidi, creare scenari fantascientifici à la Matrix o programmare la Macchina di Person of Interest. Si tratta di una rivoluzione del quotidiano: tanto più profonda, inosservata e diffusa quanto più investe la trama delle nostre abitudini e forme di vita. Come tutte le grandi rivoluzioni si radica nelle pratiche correnti. È a tale livello che i suoi effetti devono essere studiati e valutati secondo una precisa linea d’indagine: il potere computazionale, che l’alimenta, si esercita adattando il mondo e la sua rappresentazione al modo di funzionamento delle tecnologie digitali dell’informazione e della comunicazione. Così facendo, aspira a governare la società con la produzione di specifiche e nuove forme del sapere.

We delegate more and more decisions and tasks to artificial agents, machine-learning mechanisms, and algorithmic procedures or, in other words, to computational systems. Not that we are driven by powerful ambitions of colonizing the Moon, replacing humans with legions of androids, creating sci-fi scenarios à la Matrix or masterminding some sort of Person of Interest-like Machine. No, the current digital revolution based on computational power is chiefly an everyday revolution. It is therefore that much more profound, unnoticed and widespread, for it affects our customary habits and routines and alters the very texture of our day-to-day lives. This opens a precise line of inquiry, which constitutes the basic thesis of the present text: our computational power is exercised by trying to adapt not just the world but also our representation of reality to how computationally based ICTs work. The impact of this technology is such that it does not leave things as they are: it changes the nature of agents, habits, objects and institutions and hence it subverts the existing order, without necessarily generating a new one. I argue that this power is often not distributed in an egalitarian manner but, on the contrary, is likely to result in concentrations of wealth, in dominant positions or in unjust competitive advantages. This opens up a struggle, with respect to which the task of reaffirming the fundamental values, the guiding principles, the priorities and the rules of the game, which can transform, or attempt to transform, a fierce confrontation between enemies in a fair competition between opponents rests on us.

Lo psicologo contemporaneo deve fare i conti con sfide sempre maggiori e opportunità di studio e di ricerca usando nuove tecnologie fino a pochi anni fa impensabili. Elementi di Psicometria Computazionale, rappresenta un prezioso strumento per formare gli psicologi di domani, attenti al passato, orientati al futuro e con una corposa conoscenza del presente. In modo pratico e semplice il volume accompagna il lettore all'uso degli strumenti della misura in psicologia, alla luce delle più recenti tecnologie. Un percorso che parte dall'acquisizione dei dati con questionari elettronici, biosensori, social networks, realtà virtuale e altro, per proseguire con la gestione avanzata dei dati e chiudere con una prima introduzione ai modelli computazionali. Caratteristica importante del volume è il totale orientamento al mondo open source e la costante disponibilità di software gratuito per tutti gli strumenti utilizzati.

This book identifies the principles that should be applied when processing Big Data in the context of food safety risk assessments. Food safety is a critical goal in the protection of individuals’ right to health and the flourishing of the food and feed market. Big Data is fostering new applications capable of enhancing the accuracy of food safety risk assessments. An extraordinary amount of information is analysed to detect the existence or predict the likelihood of future risks, also by means of machine learning algorithms. Big Data and novel analysis techniques are topics of growing interest for food safety agencies, including the European Food Safety Authority (EFSA). This wealth of information brings with it both opportunities and risks concerning the extraction of meaningful inferences from data. However, conflicting interests and tensions among the parties involved are hindering efforts to find shared methods for steering the processing of Big Data in a sound, transparent and trustworthy way. While consumers call for more transparency, food business operators tend to be reluctant to share informational assets. This has resulted in a considerable lack of trust in the EU food safety system. A recent legislative reform, supported by new legal cases, aims to restore confidence in the risk analysis system by reshaping the meaning of data ownership in this domain. While this regulatory approach is being established, breakthrough analytics techniques are encouraging thinking about the next steps in managing food safety data in the age of machine learning. The book focuses on two core topics – data ownership and data governance – by evaluating how the regulatory framework addresses the challenges raised by Big Data and its analysis in an applied, significant, and overlooked domain. To do so, it adopts an interdisciplinary approach that considers both the technological advances and the policy tools adopted in the European Union, while also assuming an ethical perspective when exploring potential solutions. The conclusion puts forward a proposal: an ethical blueprint for identifying the principles – Security, Accountability, Fairness, Explainability, Transparency and Privacy – to be observed when processing Big Data for food safety purposes, including by means of machine learning. Possible implementations are then discussed, also in connection with two recent legislative proposals, namely the Data Governance Act and the Artificial Intelligence Act.

The COVID-19 pandemic has made the fragility of the human body painfully perceptible. Through essays and contributions of international artists and activists, this anthology poses the question of how and by whom a body is defined as healthy or sick. At the intersection of ecology, economics and technology, Kingdom of the Ill investigates a shift in the relationship between health and illness, contamination and purity, care and neglect. How are climate change and pollution affecting our well-being? Given the collective state of exhaustion, looming economic hardships, public healthcare cuts, and the dissolution of the boundaries between online and offline, how can one actually stay healthy and well? Following Techno Globalization Pandemic, Kingdom of the Ill – curated by Sara Cluggish and Pavel S. Pyś – is the second chapter in the long-term research program TECHNO HUMANITIES launched in 2021 by Museion Bozen's Director Bart van der Heide.

The Routledge Social Science Handbook of AI is a landmark volume providing students and teachers with a comprehensive and accessible guide to the major topics and trends of research in the social sciences of artificial intelligence (AI), as well as surveying how the digital revolution – from supercomputers and social media to advanced automation and robotics – is transforming society, culture, politics and economy. The Handbook provides representative coverage of the full range of social science engagements with the AI revolution, from employment and jobs to education and new digital skills to automated technologies of military warfare and the future of ethics. The reference work is introduced by editor Anthony Elliott, who addresses the question of relationship of social sciences to artificial intelligence, and who surveys various convergences and divergences between contemporary social theory and the digital revolution. The Handbook is exceptionally wide-ranging in span, covering topics all the way from AI technologies in everyday life to single-purpose robots throughout home and work life, and from the mainstreaming of human-machine interfaces to the latest advances in AI, such as the ability to mimic (and improve on) many aspects of human brain function. A unique integration of social science on the one hand and new technologies of artificial intelligence on the other, this Handbook offers readers new ways of understanding the rise of AI and its associated global transformations. Written in a clear and direct style, the Handbook will appeal to a wide undergraduate audience.

This book discusses issues relating to the application of AI and computational modelling in criminal proceedings from a European perspective. Part one provides a definition of the topics. Rather than focusing on policing or prevention of crime – largely tackled by recent literature – it explores ways in which AI can affect the investigation and adjudication of crime. There are two main areas of application: the first is evidence gathering, which is addressed in Part two. This section examines how traditional evidentiary law is affected by both new ways of investigation – based on automated processes (often using machine learning) – and new kinds of evidence, automatically generated by AI instruments. Drawing on the comprehensive case law of the European Court of Human Rights, it also presents reflections on the reliability and, ultimately, the admissibility of such evidence. Part three investigates the second application area: judicial decision-making, providing an unbiased review of the meaning, benefits, and possible long-term effects of ‘predictive justice’ in the criminal field. It highlights the prediction of both violent behaviour, or recidivism, and future court decisions, based on precedents. Touching on the foundations of common law and civil law traditions, the book offers insights into the usefulness of ‘prediction’ in criminal proceedings.