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.
Artificiale troppo Umano. Dall'equità alla correttezza algoritmica come presupposto di una nuova forma di Machine Learning
Cosmo, Nunzia
2026
Abstract
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.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Tesi Dottorato Cosmo DT00200005.pdf
accesso aperto
Licenza:
Tutti i diritti riservati
Dimensione
3.04 MB
Formato
Adobe PDF
|
3.04 MB | Adobe PDF | Visualizza/Apri |
I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.14242/367346
Il codice NBN di questa tesi è
URN:NBN:IT:UNIMERCATORUM-367346