| Line 64: | Line 64: | ||
<br /><br /><br /> | <br /><br /><br /> | ||
'''3 May 2022 / Week 4'''<br /> | '''3 May 2022 / Week 4'''<br /> | ||
From Machine Learning to Machine Intelligence<br /> | |||
Algorithmic, Computational & Generative Forms<br /> | |||
<br /> | <br /> | ||
Assignment: TBA<br /> | Assignment: TBA<br /> | ||
<br /><br /><br /> | <br /><br /><br /> | ||
'''10 May 2022 / Week 5'''<br /> | '''10 May 2022 / Week 5'''<br /> | ||
Guest Lecture with [https://www.unibg.it/ugov/person/1979 Prof. Mario Verdicchio], University of Bergamo (IT)<br /> | |||
''We have always lived in a post-truth era.''<br /> | |||
<br /> | |||
Deepfakes are videos created by means of machine learning techniques that allow for audiovisuals that depict people in a very realistic, almost impossible to detect yet fake way, while they say and do things that they did not say or do in reality. This has a plethora of potentially dangerous epistemological and ethical consequences. Since deepfakes are a novelty, these issues may appear to stem from the latest technologies, but this seeming attack against the truth has always been there, ever since humans started recording facts. | |||
This lecture analyses the technological aspects of deepfakes to show that they are simply the most recent embodiment of a gap between facts and descriptions that is as old as humanity.<br /> | |||
<br /> | <br /> | ||
Assignment: TBA<br /> | Assignment: TBA<br /> | ||