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On the Opportunities and Risks of Foundation Models 167 Andrew Brock, Jeff Donahue, and Karen Simonyan. 2018. Large Scale GAN Training for High Fidelity Natural Image Synthesis. In International Conference on Learning Representations. Matt Brockman. 2020. Math - GPT_Prompts. http://gptprompts.wikidot.com/logic:math#toc5 Urie Bronfenbrenner. 1977. Toward an Experimental Ecology of Human Development. American Psychologist 32 (1977), 513–531. R. Brooks. 2002. Flesh and Machines: How Robots Will Change Us. Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, and Florian Tramèr. 2022. What Does it Mean for a Language Model to Preserve Privacy? arXiv preprint arXiv:2202.05520 (2022). Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165 (2020). Miles Brundage, Shahar Avin, Jack Clark, Helen Toner, Peter Eckersley, Ben Garfinkel, Allan Dafoe, Paul Scharre, Thomas Zeitzoff, Bobby Filar, Hyrum Anderson, Heather Roff, Gregory C. Allen, Jacob Steinhardt, Carrick Flynn, Seán Ó hÉigeartaigh, Simon Beard, Haydn Belfield, Sebastian Farquhar, Clare Lyle, Rebecca Crootof, Owain Evans, Michael Page, Joanna Bryson, Roman Yampolskiy, and Dario Amodei. 2018. The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. arXiv:1802.07228 [cs.AI] Erik Brynjolfsson. 2022. The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence. Daedalus, Forthcoming (2022). Erik Brynjolfsson and Avinash Collis. 2019. How should we measure the digital economy? Focus on the value created, not just the prices paid. Harvard business review 97, 6 (2019), 140–. Erik Brynjolfsson, Xiang Hui, and Meng Liu. 2019. Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform. Management Science 65, 12 (dec 2019), 5449–5460. https://doi.org/10.1287/mnsc.2019.3388 Erik Brynjolfsson and Andrew McAfee. 2011. Race against the Machine. Erik Brynjolfsson and Tom Mitchell. 2017. What can machine learning do? Workforce implications. Science 358, 6370 (2017), 1530–1534. Sébastien Bubeck and Mark Sellke. 2021. A Universal Law of Robustness via Isoperimetry. arXiv preprint arXiv:2105.12806 (2021). Ben Buchanan, Andrew Lohn, Micah Musser, and Katerina Sedova. 2021. Truth, Lies, and Automation: How Language Models Could Change Disinformation. Center for Security and Emerging Technology. https://doi.org/10.51593/2021CA003 Joy Buolamwini and Timnit Gebru. 2018. Gender shades: Intersectional accuracy disparities in commercial gender classifica- tion. In Conference on Fairness, Accountability and Transparency. 77–91. Christopher Burr, Nello Cristianini, and James Ladyman. 2018. An analysis of the interaction between intelligent software agents and human users. Minds and machines 28, 4 (2018), 735–774. Jenna Burrell. 2016. How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society 3, 1 (Jan. 2016), 205395171562251. https://doi.org/10.1177/2053951715622512 Daniel Buschek, Martin Zur
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