| id |
cdrf2022_244 |
| authors |
Miric Ljubica |
| year |
2022 |
| title |
Collective Intelligence and Effects of Anticipation |
| doi |
https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_21
|
| source |
Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022) |
| summary |
Based on the extrapolation of contemporary theories that mind is a prediction machine, this paper points out the repetitive nature of the prediction parameters of collective intelligence anticipation scenarios and questions the hybridity of fears and desires regarding the evolution of artificial intelligence. Through the analysis of mnemonic principles of remembrance it combines the ancient technique of the art of memory with the contemporary views on the dynamics of perceptions in order to establish a link between the spatial constructs and their rapid expansion through the presence of the digital medium while in parallel suggesting an approach to the integration of the necessity for a more sophisticated systems of artificial intelligence into the collective intelligence. The main question of this paper is whether the anticipation of the future results in the creation of such a future, can a prediction-based interaction between man and machine govern its outcome? In order to attempt to develop potential new methods of integrating an idea of a different, more neutral outcome, the focus will be on the characteristics of perception that surpass the influenced, emotional response, and the observation of the general, innate human mechanisms of alignment. Through the study of the principles of memory the aim of this paper is to ask whether the individual comprehension of space and time as disengaged in given examples can in fact produce a system of ideas compatible in its nature to that of the machine itself. What are the main aspects of both human and machine that would stem their hybridity, and how should the collective intelligence adapt to enable the interlink? |
| series |
cdrf |
| email |
|
| full text |
 file.pdf (185,244 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/05/29 14:02 |
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