Attention economy

HYPER-REALITY, by Keiichi Matsuda

We are all agents acting with limited and local information. What sort of behaviour can we expect from a multiscale system composed of such actors? Especially, consider the problem of what we can expect if all the actors in such a system have no only finite computational resources and times to spend of calculating the risk an return for each problem facing them, but also finite resources to spend even on working out which problems to allocate their other finite resources to.

Center for Humane Technology TED-izes this.


Evans, David S. 2017. β€œThe Economics of Attention Markets.” SSRN Scholarly Paper ID 3044858. Rochester, NY: Social Science Research Network.
Hoiles, William, Vikram Krishnamurthy, and Kunal Pattanayak. 2020. β€œRationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior.” Journal of Machine Learning Research 21 (170): 1–39.
Huang, Linan, and Quanyan Zhu. 2021. β€œCombating Informational Denial-of-Service (IDoS) Attacks: Modeling and Mitigation of Attentional Human Vulnerability.” arXiv:2108.08255 [Cs] 13061: 314–33.
Rizoiu, Marian-Andrei, and Lexing Xie. 2017. β€œOnline Popularity Under Promotion: Viral Potential, Forecasting, and the Economics of Time.” arXiv:1703.01012 [Cs], March.
Wu, Siqi, Marian-Andrei Rizoiu, and Lexing Xie. 2019. β€œEstimating Attention Flow in Online Video Networks.” Proceedings of the ACM on Human-Computer Interaction 3 (CSCW): 1–25.

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