Artificiale troppo Umano. Dall'equità alla correttezza algoritmica come presupposto di una nuova forma di Machine Learning

This study analyzes Artificial Intelligence (AI) as a socio-technical infrastructure shaping organizational systems and Human Resource Management. Focusing on Machine Learning, it highlights both the opportunities of AI in improving efficiency and the risks related to algorithmic bias and gender inequality. The research concludes that responsible AI adoption requires the integration of technological innovation, ethical governance, and organizational accountability.

Il monitoraggio degli assetti organizzativi, amministrativi e contabili per la tempestiva emersione dello stato di crisi aziendale

Sanzioni penali e premialità nella gestione efficiente della crisi d’impresa

A Digital Surrogate Framework for End-to-End Optimization of IM/DD Optical Communication Systems

1. Context and motivation High-capacity connectivity is a cornerstone of the ongoing digital transformation of industry and society. Data-center interconnects, campus networks, metro aggregation, and increasingly distributed industrial infrastructures must deliver rising throughput under strict constraints on cost, energy consumption, and operational complexity. In this landscape, intensity modulation and direct detection (IM-DD) remains highly relevant because it enables high data rates with...

Crisi aziendale e resilienza: strategie di gestione e continuità organizzativa

La relazione tra la dimensione ESG e la performance patrimoniale e finanziaria aziendale: analisi della letteratura ed evidenze empiriche dalle società non finanziarie quotate alla Borsa italiana (2021-2024).

This research examines the role of ESG metrics as sustainability KPIs in the context of corporate financial distress, with a focus on their potential contribution to early crisis detection and the preservation of business continuity. ESG factors are not treated merely as reputational or compliance tools, but as strategic variables with broader social implications, particularly regarding employment and economic well-being. The main objective is to investigate whether non-financial performance...

AI-generated Deepfakes: Detection and Bias Analysis

DeepFakes, synthetic manipulations of faces produced with generative artificial intelligence, threaten the authenticity of content and expose detectors to the tough task of dealing with a multiplicity of content and great variability, compression levels and deepfake generation pipelines. Against this backdrop, this doctoral thesis investigates how misclassifications in DeepFake detection relate to high-level facial attributes, and how this knowledge can guide more robust and interpretable det...

Measuring and Modelling the Spatial Patterns of Firms: Integrating Spatial Statistics and Machine Learning for Firm-Level Analysis

This thesis is developed as a collection of three independent chapters/papers and studies how productivity differences emerge and persist across firms and places, with a focus on industrial clustering and agglomeration. The first paper devel- ops an empirical framework based on bipartite network representations of firms to characterize local productive structures of innovative startups in Lombardy. The second paper develops a deep clustering pipeline to perform bootstrap analysis of high-tech...

AI-Driven Learning Assistants for Reflective, Adaptive, and Inclusive Education

This thesis presents the AI-Driven Reflective Learning Framework (AI-DRLF), a framework for the design of educational assistants based on Large Language Models (LLMs). The framework is intended to support reflective, adaptive, and inclusive learning through the integration of generative AI technologies and pedagogical principles. In particular, it combines reflective scaffolding, adaptive content delivery, accessibility-aware interaction, and AI-supported feedback within a unified educational...