"a public beta of our project, Collective Cognition to share ChatGPT chats"

@teknium1 via Twitter on Sep 22, 2023

Today @SM00719002 and I are launching a public beta of our project, Collective Cognition to share ChatGPT chats - allowing for browsing, searching, up and down voting of chats, as well as creating a crowdsourced multiturn dataset!
https://collectivecognition.ai

As of this post: ‘🚀 Beta Launch: 218 total chats shared so far!’

Including an example shared chat by me (https://collectivecognition.ai/share/925e8ee0-d7f1-4728-87b3-7f167b8359bc) prompted with a leading question about the value of sharing interactions with these systems, quoting from Zamfirescu-Pereira et al. (2023) (re: “a searchable repository of examples”) and Mollick (2023) (re: “large-scale public libraries of prompts”) and some language—first drafted re #llm_system_screenshots_and_social_share_cards—at SearchRights.org > category: Sharing Searching:

Research demonstrates significant value in users communicating about their experiences with tools. Better support for sharing interactions with these systems may improve users collective ability to effectively question/complain, teach, & organize about/around/against these tools (i.e. “working around platform errors and limitations” & “virtual assembly work” (Burrell et al., 2019), “repairing searching” (Griffin, 2022), search quality complaints (Griffin & Lurie, 2022), and end-user audits (Lam et al., 2022, Metaxa et al., 2021)) and improve our “practical knowledge” of the systems (Cotter, 2022).

Shared also on Twitter

References

Burrell, J., Kahn, Z., Jonas, A., & Griffin, D. (2019). When users control the algorithms: Values expressed in practices on Twitter. Proc. ACM Hum.-Comput. Interact., 3(CSCW). https://doi.org/10.1145/3359240 [burrell2019control]

Cotter, K. (2022). Practical knowledge of algorithms: The case of BreadTube. New Media & Society, 1–20. https://doi.org/10.1177/14614448221081802 [cotter2022practical]

Griffin, D. (2022). Situating web searching in data engineering: Admissions, extensions, repairs, and ownership [PhD thesis, University of California, Berkeley]. https://danielsgriffin.com/assets/griffin2022situating.pdf [griffin2022situating]

Griffin, D., & Lurie, E. (2022). Search quality complaints and imaginary repair: Control in articulations of Google Search. New Media & Society, 0(0), 14614448221136505. https://doi.org/10.1177/14614448221136505 [griffin2022search]

Lam, M. S., Gordon, M. L., Metaxa, D., Hancock, J. T., Landay, J. A., & Bernstein, M. S. (2022). End-user audits: A system empowering communities to lead large-scale investigations of harmful algorithmic behavior. Proc. ACM Hum.-Comput. Interact., 6(CSCW2). https://doi.org/10.1145/3555625 [lam2022end]

Metaxa, D., Park, J. S., Robertson, R. E., Karahalios, K., Wilson, C., Hancock, J., & Sandvig, C. (2021). Auditing algorithms: Understanding algorithmic systems from the outside in. Foundations and Trends® in Human–Computer Interaction, 14(4), 272–344. https://doi.org/10.1561/1100000083 [metaxa2021auditing]

Mollick, E. (2023). One useful thing. Now Is the Time for Grimoires. https://www.oneusefulthing.org/p/now-is-the-time-for-grimoires [mollick2023useful]

Zamfirescu-Pereira, J. D., Wong, R. Y., Hartmann, B., & Yang, Q. (2023). Why johnny can’t prompt: How non-ai experts try (and fail) to design llm prompts. Proceedings of the 2023 Chi Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3544548.3581388 [zamfirescu-pereira2023johnny]