CHI 2021 conference papers

Two papers at the CHI con­fer­ence this year.

Sara Heitlinger, Lara Hous­ton, Alex Tay­lor, Ruth Cat­low (2021) Algo­rith­mic Food Jus­tice: Co-Design­ing More-than-Human Blockchain Futures for the Food Com­mons, Pro­ceed­ings of the 2021 CHI Con­fer­ence on Human Fac­tors in Com­put­ing Sys­tems, New York, NY, USA: Asso­ci­a­tion for Com­put­ing Machin­ery, pdf, doi:10.1145/3411764.3445655

The rela­tion­ships that con­sti­tute the glob­al indus­tri­al food sys­tem tend towards two dom­i­nant val­ues that are cre­at­ing unsus­tain­able social and envi­ron­men­tal inequal­i­ties. The first is a human-cen­tered per­spec­tive on food that priv­i­leges humans over all oth­er species. The sec­ond is a view of food as a com­mod­i­ty to be trad­ed for max­i­mum eco­nom­ic val­ue, reward­ing a small num­ber of share­hold­ers. We present work that explores the unique algo­rith­mic affor­dances of blockchain to cre­ate new types of val­ue exchange and gov­er­nance in the food sys­tem. We describe a project that used role­play with urban agri­cul­tur­al com­mu­ni­ties to co-design blockchain-based food futures and explore the con­di­tions for cre­at­ing a thriv­ing mul­ti­species food com­mons. We dis­cuss how the project helped rethink algo­rith­mic food jus­tice by recon­fig­ur­ing more-than-human val­ues and recon­fig­ur­ing food as more-than-human com­mons. We also dis­cuss some of the chal­lenges and ten­sions aris­ing from these explorations. 

Ceci­ly Mor­ri­son, Edward Cutrell, Mar­tin Grayson, Anja Thieme, Alex Tay­lor, Geert Roumen, Camil­la Long­den, Sebas­t­ian Tschi­atschek, Rita Faia Mar­ques, Abi­gail Sell­en (2021) Social Sense­mak­ing with AI: Design­ing an Open-End­ed AI Expe­ri­ence with a Blind Child, Pro­ceed­ings of the 2021 CHI Con­fer­ence on Human Fac­tors in Com­put­ing Sys­tems, New York, NY, USA: Asso­ci­a­tion for Com­put­ing Machin­ery, pdf, doi:10.1145/3411764.3445290

AI tech­nolo­gies are often used to aid peo­ple in per­form­ing dis­crete tasks with well-defined goals (e.g., recog­nis­ing faces in images). Emerg­ing tech­nolo­gies that pro­vide con­tin­u­ous, real-time infor­ma­tion enable more open-end­ed AI expe­ri­ences. In part­ner­ship with a blind child, we explore the chal­lenges and oppor­tu­ni­ties of design­ing human-AI inter­ac­tion for a sys­tem intend­ed to sup­port social sense­mak­ing. Adopt­ing a research-through-design per­spec­tive, we reflect upon work­ing with the uncer­tain capa­bil­i­ties of AI sys­tems in the design of this expe­ri­ence. We con­tribute: (i) a con­crete exam­ple of an open-end­ed AI sys­tem that enabled a blind child to extend his own capa­bil­i­ties; (ii) an illus­tra­tion of the delta between imag­ined and actu­al use, high­light­ing how capa­bil­i­ties derive from the human-AI inter­ac­tion and not the AI sys­tem alone; and (iii) a dis­cus­sion of design choic­es to craft an ongo­ing human-AI inter­ac­tion that address­es the chal­lenge of uncer­tain out­puts of AI systems. 

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