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   https://doi.org/10.1145/3461702.3462599  

   Kshirsagar, Meghana; Robinson, Caleb; Yang, Siyu; Gholami, Shahrzad; Klyuzhin, Ivan; Mukherjee, Sumit; Nasir, Md; Ortiz, Anthony; Oviedo, Felipe; Tanner, Darren; et al (July 2021, Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES ’21), May 19–21, 2021,)

   null (Ed.)

   AI for good (AI4G) projects involve developing and applying ar- tificial intelligence (AI) based solutions to further goals in areas such as sustainability, health, humanitarian aid, and social justice. Developing and deploying such solutions must be done in collab- oration with partners who are experts in the domain in question and who already have experience in making progress towards such goals. Based on our experiences, we detail the different aspects of this type of collaboration broken down into four high-level cat- egories: communication, data, modeling, and impact, and distill eleven takeaways to guide such projects in the future. We briefly describe two case studies to illustrate how some of these takeaways were applied in practice during our past collaborations. 

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2. Good-enough language production

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   Goldberg, Adele E.; Ferreira, Fernanda (April 2022, Trends in Cognitive Sciences)
3. Sys: A Static/Symbolic Tool for Finding Good Bugs in Good (Browser) Code

   Brown, Fraser; Stefan, Deian; Engler, Dawson (August 2020, 29th USENIX Security Symposium)

   We describe and evaluate an extensible bug-finding tool, Sys, designed to automatically find security bugs in huge codebases, even when easy-to-find bugs have been already picked clean by years of aggressive automatic checking. Sys uses a two-step approach to find such tricky errors. First, it breaks down large---tens of millions of lines---systems into small pieces using user-extensible static checkers to quickly find and mark potential errorsites. Second, it uses user-extensible symbolic execution to deeply examine these potential errorsites for actual bugs. Both the checkers and the system itself are small (6KLOC total). Sys is flexible, because users must be able to exploit domain- or system-specific knowledge in order to detect errors and suppress false positives in real codebases. Sys finds many security bugs (51 bugs, 43 confirmed) in well-checked code---the Chrome and Firefox web browsers---and code that some symbolic tools struggle with---the FreeBSD operating system. Sys's most interesting results include: an exploitable, cash bountied CVE in Chrome that was fixed in seven hours (and whose patch was backported in two days); a trio of bountied bugs with a CVE in Firefox; and a bountied bug in Chrome's audio support. 

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4. Good times for wireless research

   https://doi.org/10.1016/j.comnet.2021.107870  

   Doost-Mohammady, Rahman; Bejarano, Oscar; Sabharwal, Ashutosh (April 2021, Computer Networks)
5. Good Times For Wireless Research

   https://doi.org/10.1145/3411276.3414557  

   Doost-Mohammady, Rahman; Bejarano, Oscar; Sabharwal, Ashutosh (September 2020, ACM WiNTECH 2020)