00:37:59 Peter Mawhorter: Good points! 00:38:58 Shadan Sadeghian: @Diana: how much of those jobs (in which people use their cars) will exist in the future? 00:41:06 Meghna Gupta: ... 00:43:09 Andrew Kun: Questions for the panelists? Please type in the chat window. 00:47:29 Peter Mawhorter: Do panelists feel that there are enough connections between the technical disciplines that we’re in and disciplines in the humanities who study social injustice like gender studies or Africana studies? What role might cross-disciplinary connections play in building a more inclusive future of technology, and what might those connections look like? 00:49:59 Peter Mawhorter: (Sorry to ask such a hard question :) 00:50:43 Ayesha Bhimdiwala: 100000% true 00:50:46 Andrew Kun: https://www.nsf.gov/od/oia/convergence/index.jsp 00:51:14 Peter Mawhorter: Thanks for the link Andrew! 00:52:31 Andrii Matviienko: To Diana’s point about misclassification and dangers of facial recognition, there is a nice recent episode by John Oliver on that topic: https://www.youtube.com/watch?v=jZjmlJPJgug 00:52:37 Preeti Vyas: (Re: designing question) I also feel that while connecting with diverse user groups we need to have patience and empathy. As researchers we often tend to assume certain levels of familiarity while designing technology. Our interactions and user studies might be overwhelming for some group, we need to take this into consideration. 01:01:53 Shadan Sadeghian: How can we define axes of diversity without biases? E.g., How can we include vulnerable/less privileged societies without thinking war is a “normal” state in middle east, or it is normal that less people from far east are fluent in English, i.e., how can we avoid these “normals”? 01:03:53 Andrew Kun: https://dl.acm.org/doi/pdf/10.1145/3334480.3381808 01:05:53 Preeti Vyas: I think we cannot have a general definition of "normal" but if we acknowledge these differences and take these conditions into account, that makes more sense. 01:08:30 Anupriya Tuli: I agree, we should focus and seek for “similarity” that runs common among diverse voices and look for common grounds while acknowledging the differences! 01:09:36 Shivani: I think you made a great point, Aditya. You're asking a challenging question here, but do you have any thoughts on how do you deal with this? 01:12:35 Shivani: (to rephrase) As researchers, how do we move from where we are today to a place where people have equitable access to these tools? How and where do we start? 01:13:58 Ayesha Bhimdiwala: @Shivani, one way to do so is related to what Aditya said earlier, having diverse stakeholders as part of these projects to understand user needs and accessibility 01:15:53 Preeti Vyas: great point! @Diana 01:17:22 aditya vishwanath: Very sorry but I have to leave at the end of the hour, but this was a really wonderful session. Thanks Neha and Andrew for organizing this. And thank you for the opportunity to learn from and share with all of you! 01:17:27 Preeti Vyas: Got to leave, but thank you everyone. Really insightful discussion. 01:17:38 Diana Tosca: Thank you Aditya!!! 01:17:45 Diana Tosca: thank you all :) 01:20:34 Shivani: Thanks, Ayesha! 01:25:25 Peter Mawhorter: @Shadan: But with the direction things are going now, aren’t these intelligent systems likely to be more biased based on training on biased data? (Same thing that Shivani just said) 01:27:31 Shivani: The saviour complex! 01:27:31 Diana Tosca: everyone’s a part of this conversation regardless of panelist status! 👀😁 01:31:22 Peter Mawhorter: I feel like disciplinary boundaries and institutional structures are one big thing that prevents collaboration across disciplines. 01:31:35 Peter Mawhorter: Concerns about whether cross-disciplinary research will count towards tenure for example 01:32:45 Shadan Sadeghian: I need to leave now. Thanks for the interesting panel and discussion :) hope to see you soon! 01:37:41 Peter Mawhorter: Thanks so much for moderating!