A proposal that we think about digital technologies such as machine learning not in terms of artificial intelligence but as artificial communication. Algorithms that work with deep learning and big data are getting so much better at doing so many things that it makes us uncomfortable. How can a device know what our favorite songs are, or what we should write in an email? Have machines become too smart? In Artificial Communication, Elena Esposito argues that drawing this sort of analogy between algorithms and human intelligence is misleading. If machines contribute to social intelligence, it will not be because they have learned how to think like us but because we have learned how to communicate with them. Esposito proposes that we think of “smart” machines not in terms of artificial intelligence but in terms of artificial communication. To do this, we need a concept of communication that can take into account the possibility that a communication partner may be not a human being but an algorithm—which is not random and is completely controlled, although not by the processes of the human mind. Esposito investigates this by examining the use of algorithms in different areas of social life. She explores the proliferation of lists (and lists of lists) online, explaining that the web works on the basis of lists to produce further lists; the use of visualization; digital profiling and algorithmic individualization, which personalize a mass medium with playlists and recommendations; and the implications of the “right to be forgotten.” Finally, she considers how photographs today seem to be used to escape the present rather than to preserve a memory.
Author(s): Elena Esposito
Series: Strong Ideas
Publisher: The MIT Press
Year: 2022
Language: English
Commentary: TruePDF | Full TOC
Pages: 199
City: Cambridge
Tags: Telecommunication: Social Aspects; Artificial Intelligence: Social Aspects; Online Identities; Social Intelligence
Cover
Half title
Series title
Title
Copyright
Dedication
Contents
Introduction
1 | Artificial Communication? Algorithms as Interaction Partners
Communication With Algorithms
Artificial Communication
Can We Communicate With Partners That Do Not Think?
Virtual Contingency
Googlization
What Algorithms Learn
Learning To Learn From Machines
Conclusion
2 | Organizing without Understanding: Lists in Ancient and Digital Cultures
A Web Of Lists
Listing, Rating, Ranking
Writing, Context, And Abstraction
Listing Machines
Conclusion
3 | Reading Images: Visualization and Interpretation in Digital Text Analysis
Nonlinguistic Literary Analysis
Exploring Images
Visual Provocations`
Reading, Non-Reading, Distant Reading
Algorithmic Reading Is Not Algorithms Reading
Conclusion
4 | Getting Personal with Algorithms
Anonymous Personalization
The Web Of Individuals
Personalization And Standardization
Profiling: Contextual Or Behavioral?
Forms Of Digital Communication
Conclusion
5 | Algorithmic Memory and the Right to Be Forgotten
Remebering To Forget
Data-Driven Agency
The Memory Of A Web-Based Society
Forgetting Without Remembering
Data-Driven Memory
Conclusion
6 | Forgetting Pictures
Photographic Experience
Images To Remember
The Risk Of The Present
Time-Specific Experience
Conclusion
7 | The Future of Prediction: From Statistical Uncertainty to Algorithmic Forecasts
The Uncertainty Of The Open Future
Divinatory Aspects Of Algorithmic Prediction
Managing Future Uncertainty
Averages Versus Individual Prediction
Manufacturing The Predicted Future
When Correct Predictions Are Wrong
Blindness And Overfitting
Memory And Fantasy
Conclusion
Conclusion
Acknowledgments
Notes
Introduction
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Conclusion
Bibliography
Index
