44 Association of Research Libraries Research Library Issues 299 — 2019 18. Joelle Pineau, “ICLR Reproducibility Challenge: Second Edition, 2019,” Pineau’s website, accessed August 30, 2019, https://www.cs.mcgill. ca/~jpineau/ICLR2019-ReproducibilityChallenge.html. 19. Lee Rainie and Janna Anderson, Code-Dependent: Pros and Cons of the Algorithm Age (Washington, DC: Pew Research Center, February 2017), http://www.pewinternet.org/wp-content/uploads/sites/9/2017/02/ PI_2017.02.08_Algorithms_FINAL.pdf. 20. R. David Lankes, “Decoding AI and Libraries,” Lankes’s website, July 3, 2019, https://davidlankes.org/decoding-ai-and-libraries/. 21. Catherine Nicole Coleman, “Artificial Intelligence and the Library of the Future, Revisited,” Digital Library Blog, Stanford Libraries, November 3, 2017, http://library.stanford.edu/blogs/digital-library-blog/2017/11/ artificial-intelligence-and-library-future-revisited. 22. “Artificial Intelligence and Machine Learning in Libraries,” ed. Jason Griffey, Library Technology Reports 55, no. 1 (2019), https://doi. org/10.5860/ltr.55n1. 23. Chris Bourg, “What Happens to Libraries and Librarians When Machines Can Read All the Books?,” Feral Librarian, March 16, 2017, https://chrisbourg.wordpress.com/2017/03/16/what-happens-to- libraries-and-librarians-when-machines-can-read-all-the-books/. 24. Vahe Tshitoyan et al., “Unsupervised Word Embeddings Capture Latent Knowledge from Materials Science Literature,” Nature 571, no. 7763 (2019): 95–98, https://doi.org/10.1038/s41586-019-1335-8. 25. Don R. Swanson, “Medical Literature as a Potential Source of New Knowledge,” Bulletin of the Medical Library Association 78, no. 1 (January 1990): 29–37, https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC225324/. 26. Jacobo Elosua, Anita Schjøll Brede, Maria Ritola, and Victor Botev, “Iris.ai’s Project Aiur: An Open, Community-Governed AI Engine for Knowledge Validation,” Iris.ai, May 2018, https://iris.ai/wp-content/ uploads/2018/05/ProjectAiur_whitepaper.pdf.