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--- z-modul:kunst_kuenstliche_intelligenz [2023/02/14 08:23] – fstalder@zhdk.ch
+++ z-modul:kunst_kuenstliche_intelligenz [2023/02/14 08:56] (current) – fstalder@zhdk.ch
@@ Line 9: / Line 9: @@
   * self-driving cars, [[https://www.nytimes.com/2015/03/20/business/elon-musk-says-self-driving-tesla-cars-will-be-in-the-us-by-summer.html|2015]]
-  * Blockchain, 2019
+  * Blockchain, [[https://www.pwc.com/gx/en/industries/technology/publications/blockchain-report-transform-business-economy.html|2019]]
   * AI Sentience, 2023
 **Main Sources:**
-  * Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜.” In [[https://doi.org/10.1145/3442188.3445922|Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency]], 610–23. Virtual Event Canada: ACM.
+  * Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜.” In [[https://doi.org/10.1145/3442188.3445922|Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency]], 610–23. Virtual Event Canada: ACM. \\ “we understand the term language model (LM) to refer to systems which are trained on string prediction tasks: that is, predicting the likelihood of a token (character, word or string) given either its preceding context or (in bidirectional and masked LMs) its surrounding context.” (Bender et al., 2021, p. 611) \\ resource use \\ bias (gender, class, language, geography) \\ false narrative (coherence is not sentience) \\ "LMs are not performing natural language understanding (NLU), and only have success in tasks that can be approached by manipulating linguistic form” (Bender et al., 2021, p. 610)
   * Bender, Emily. 2022. [[https://www.youtube.com/watch?v=wuU-5rGPbyg|Resisting dehumanization in the age of AI.]] Talk at CogSci: Interdisciplinary Study of the Mind (07.29), 62 Min
-  * “we understand the term language model (LM) to refer to systems which are trained on string prediction tasks: that is, predicting the likelihood of a token (character, word or string) given either its preceding context or (in bidirectional and masked LMs) its surrounding context.” ([Bender et al., 2021, p. 611]
   * Mozilla Internet Health Report. 2022. [[https://2022.internethealthreport.org/facts/|Who Has Power Over AI?]]
   * [[https://wiki.zhdk.ch/fs/lib/exe/detail.php?id=what_kind_of_ai_do_we_want&media=biases.png|Avoidable and Unavoidable Bias in the AI Pipeline]] by Felix Stalder, 2022