Welcome to the third issue of this year's AI Matters Newsletter. In this issue, we will summarize the achievement of SIGAI in the past year (July 1, 2022 --- August 30, 2023). This annual report will highlight some of the many activities we have completed as a SIG, hoping to provide inspiration for members who wish to get more involved. This issue will also highlight the "AI Policy Matters" column by Dr. Larry Medsker at George Washington University. In this column, Dr. Medsker summarized an update on the ACM US Technology Policy Committee (USTPC) and introduced the TechBrief series at ACM. We welcome blog comments from everyone! Finally, we will end the issue with a conference report by Dr. Louise A. Dennis.
{"title":"Welcome to AI Matters 9(3)","authors":"Ziyu Yao, Anuj Karpatne","doi":"10.1145/3626487.3626488","DOIUrl":"https://doi.org/10.1145/3626487.3626488","url":null,"abstract":"Welcome to the third issue of this year's AI Matters Newsletter. In this issue, we will summarize the achievement of SIGAI in the past year (July 1, 2022 --- August 30, 2023). This annual report will highlight some of the many activities we have completed as a SIG, hoping to provide inspiration for members who wish to get more involved. This issue will also highlight the \"AI Policy Matters\" column by Dr. Larry Medsker at George Washington University. In this column, Dr. Medsker summarized an update on the ACM US Technology Policy Committee (USTPC) and introduced the TechBrief series at ACM. We welcome blog comments from everyone! Finally, we will end the issue with a conference report by Dr. Louise A. Dennis.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135735269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AI Policy Matters is a regular column in AI Matters featuring summaries and commentary based on postings that appear in the AI Matters blog (https://sigai.acm.org/aimatters/blog/). We welcome everyone to make blog comments so we can develop a rich knowledge base of information and ideas representing the SIGAI members.
AI Policy Matters是AI Matters的定期专栏，主要内容是根据AI Matters博客(https://sigai.acm.org/aimatters/blog/)上的帖子进行总结和评论。我们欢迎每个人在博客上发表评论，这样我们就可以建立一个丰富的知识库，代表SIGAI成员的信息和想法。
{"title":"AI Policy Matters","authors":"Larry Medsker","doi":"10.1145/3626487.3626490","DOIUrl":"https://doi.org/10.1145/3626487.3626490","url":null,"abstract":"AI Policy Matters is a regular column in AI Matters featuring summaries and commentary based on postings that appear in the AI Matters blog (https://sigai.acm.org/aimatters/blog/). We welcome everyone to make blog comments so we can develop a rich knowledge base of information and ideas representing the SIGAI members.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135735270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This section is compiled from reports of recent events sponsored or run in cooperation with ACM SIGAI. In general these reports were written and submitted by the conference organisers.
{"title":"Conference Reports","authors":"Louise A. Dennis","doi":"10.1145/3626487.3626491","DOIUrl":"https://doi.org/10.1145/3626487.3626491","url":null,"abstract":"This section is compiled from reports of recent events sponsored or run in cooperation with ACM SIGAI. In general these reports were written and submitted by the conference organisers.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135735268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise Dennis, Larry Medsker, Ziyu Yao, Anuj Karpatne, Alan Tsang, Matt Luckcuck
We are delighted to share our annual report with membership. This highlights some of the many activities we do as a SIG, and could provide some inspiration for members who wish to get more involved about the types of activities they could participate in or where they feel new initiatives might be most welcome. If you are interested in being more involved with SIGAI or have ideas for future initiatives, please reach out to any or all of the leadership team.
{"title":"SIGAI Annual Report: July 1 2022 --- August 30 2023","authors":"Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise Dennis, Larry Medsker, Ziyu Yao, Anuj Karpatne, Alan Tsang, Matt Luckcuck","doi":"10.1145/3626487.3626489","DOIUrl":"https://doi.org/10.1145/3626487.3626489","url":null,"abstract":"We are delighted to share our annual report with membership. This highlights some of the many activities we do as a SIG, and could provide some inspiration for members who wish to get more involved about the types of activities they could participate in or where they feel new initiatives might be most welcome. If you are interested in being more involved with SIGAI or have ideas for future initiatives, please reach out to any or all of the leadership team.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135735273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael Guerzhoy, Marion Neumann, Pat Virtue, Carolyn Jane Anderson, Yaman K Singla, Alexi Orchard, Rajiv Ratn Shah
The 13th Symposium on Educational Advances in Artificial Intelligence (EAAI-23), co-chaired by Michael Guerzhoy, Marion Neumann, and Pat Virtue, continued the tradition of the AAAI/ACM SIGAI New and Future AI Educator (NFAIED) Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). This paper is a collection of the "blue sky" essays of the 2023 NFAIED awardees, intended to help motivate discussion around various current and important issues in AI education.
{"title":"EAAI-23 Blue Sky Ideas in Artificial Intelligence Education from the AAAI/ACM SIGAI New and Future AI Educator Program","authors":"Michael Guerzhoy, Marion Neumann, Pat Virtue, Carolyn Jane Anderson, Yaman K Singla, Alexi Orchard, Rajiv Ratn Shah","doi":"10.1145/3609468.3609474","DOIUrl":"https://doi.org/10.1145/3609468.3609474","url":null,"abstract":"The 13th Symposium on Educational Advances in Artificial Intelligence (EAAI-23), co-chaired by Michael Guerzhoy, Marion Neumann, and Pat Virtue, continued the tradition of the AAAI/ACM SIGAI New and Future AI Educator (NFAIED) Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). This paper is a collection of the \"blue sky\" essays of the 2023 NFAIED awardees, intended to help motivate discussion around various current and important issues in AI education.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos, Dhruv Batra
Decades of research into intelligent animal navigation posits that organisms build and maintain internal spatial representations (or maps) 1 of their environment, that enables the organism to determine and follow task-appropriate paths (Epstein, Patai, Julian, & Spiers, 2017; O'keefe & Nadel, 1978; Tollman, 1948). Hamsters, wolves, chimpanzees, and bats leverage prior exploration to determine and follow shortcuts they may never have taken before (Chapuis & Scardigli, 1993; Harten, Katz, Goldshtein, Handel, & Yovel, 2020; Menzel, 1973; Peters, 1976; Toledo et al., 2020). Even blind mole rats and animals rendered situationally-blind in dark environments demonstrate shortcut behaviors (Avni, Tzvaigrach, & Eilam, 2008; Kimchi, Etienne, & Terkel, 2004; Maaswinkel & Whishaw, 1999). Ants forage for food along meandering paths but take near-optimal return trips (Müller & Wehner, 1988), though there is some controversy about whether insects like ants and bees are capable of forming maps (Cheung et al., 2014; Cruse & Wehner, 2011).
几十年来对智能动物导航的研究认为，生物建立并维持其环境的内部空间表征(或地图)1，使生物能够确定并遵循适合任务的路径(Epstein, Patai, Julian， &施皮尔,2017;奥基夫,纳达尔,1978;Tollman惊讶于今秋,1948)。仓鼠、狼、黑猩猩和蝙蝠利用先前的探索来确定并遵循它们以前可能从未走过的捷径(Chapuis &Scardigli, 1993;哈滕，卡茨，戈德施泰因，汉德尔，&;Yovel, 2020;门泽尔,1973;彼得斯,1976;Toledo et al.， 2020)。即使是失明的鼹鼠和在黑暗环境中失明的动物也表现出了捷径行为(Avni, Tzvaigrach， &Eilam, 2008;Kimchi, Etienne， &兹,2004;Maaswinkel,Whishaw, 1999)。蚂蚁沿着蜿蜒的路径寻找食物，但会选择接近最优的回程路线(米勒&Wehner, 1988)，尽管对于蚂蚁和蜜蜂等昆虫是否能够形成地图存在一些争议(Cheung et al.， 2014;瓶,韦娜,2011)。
{"title":"Emergence of Maps in the Memories of Blind Navigation Agents","authors":"Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos, Dhruv Batra","doi":"10.1145/3609468.3609471","DOIUrl":"https://doi.org/10.1145/3609468.3609471","url":null,"abstract":"Decades of research into intelligent animal navigation posits that organisms build and maintain internal spatial representations (or maps) 1 of their environment, that enables the organism to determine and follow task-appropriate paths (Epstein, Patai, Julian, & Spiers, 2017; O'keefe & Nadel, 1978; Tollman, 1948). Hamsters, wolves, chimpanzees, and bats leverage prior exploration to determine and follow shortcuts they may never have taken before (Chapuis & Scardigli, 1993; Harten, Katz, Goldshtein, Handel, & Yovel, 2020; Menzel, 1973; Peters, 1976; Toledo et al., 2020). Even blind mole rats and animals rendered situationally-blind in dark environments demonstrate shortcut behaviors (Avni, Tzvaigrach, & Eilam, 2008; Kimchi, Etienne, & Terkel, 2004; Maaswinkel & Whishaw, 1999). Ants forage for food along meandering paths but take near-optimal return trips (Müller & Wehner, 1988), though there is some controversy about whether insects like ants and bees are capable of forming maps (Cheung et al., 2014; Cruse & Wehner, 2011).","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Estimating 3D human motion from an ego-centric video, which records the environment viewed from the first-person perspective with a front-facing monocular camera, is critical to applications in VR/AR. However, naively learning a mapping between egocentric videos and full-body human motions is challenging for two reasons. First, modeling this complex relationship is difficult; unlike reconstruction motion from third-person videos, the human body is often out of view of an egocentric video. Second, learning this mapping requires a large-scale, diverse dataset containing paired egocentric videos and the corresponding 3D human poses. Creating such a dataset requires meticulous instrumentation for data acquisition, and unfortunately, such a dataset does not currently exist. As such, existing works have only worked on small-scale datasets with limited motion and scene diversity (yuan20183d; yuan2019ego; luo2021dynamics).
{"title":"Ego-Body Pose Estimation via Ego-Head Pose Estimation","authors":"Jiaman Li, C. Karen Liu, Jiajun Wu","doi":"10.1145/3609468.3609473","DOIUrl":"https://doi.org/10.1145/3609468.3609473","url":null,"abstract":"Estimating 3D human motion from an ego-centric video, which records the environment viewed from the first-person perspective with a front-facing monocular camera, is critical to applications in VR/AR. However, naively learning a mapping between egocentric videos and full-body human motions is challenging for two reasons. First, modeling this complex relationship is difficult; unlike reconstruction motion from third-person videos, the human body is often out of view of an egocentric video. Second, learning this mapping requires a large-scale, diverse dataset containing paired egocentric videos and the corresponding 3D human poses. Creating such a dataset requires meticulous instrumentation for data acquisition, and unfortunately, such a dataset does not currently exist. As such, existing works have only worked on small-scale datasets with limited motion and scene diversity (yuan20183d; yuan2019ego; luo2021dynamics).","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This section is compiled from reports of recent events sponsored or run in cooperation with ACM SIGAI. In general these reports were written and submitted by the conference organisers.
{"title":"Conference Reports","authors":"Louise A. Dennis","doi":"10.1145/3609468.3609470","DOIUrl":"https://doi.org/10.1145/3609468.3609470","url":null,"abstract":"This section is compiled from reports of recent events sponsored or run in cooperation with ACM SIGAI. In general these reports were written and submitted by the conference organisers.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hypergraphs offer a powerful abstraction for representing multi-way group interactions, allowing hyperedges to connect any number of nodes. In contrast to prevailing approaches that focus on capturing statistical dependencies, our research explores hypergraphs from a causal perspective. Specifically, we tackle the problem of estimating individual treatment effects (ITE) on hypergraphs, aiming to determine the causal impact of interventions (e.g., wearing face covering) on outcomes (e.g., COVID-19 infection) for each individual node. Existing ITE estimation methods either assume no interference between individuals or consider interference only among connected individuals in regular graphs. However, such assumptions may not hold in real-world hypergraphs. Recognizing this, we propose a novel causality learning framework HyperSCI by modeling high-order interference on hyper-graphs. Through extensive experiments on real-world hypergraphs, we validate the effectiveness of HyperSCI and highlight the potential of causal inference in hypergraphs with complex group interactions. 1
{"title":"Causal Effect Estimation under Interference on Hypergraphs","authors":"Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan","doi":"10.1145/3609468.3609472","DOIUrl":"https://doi.org/10.1145/3609468.3609472","url":null,"abstract":"Hypergraphs offer a powerful abstraction for representing multi-way group interactions, allowing hyperedges to connect any number of nodes. In contrast to prevailing approaches that focus on capturing statistical dependencies, our research explores hypergraphs from a causal perspective. Specifically, we tackle the problem of estimating individual treatment effects (ITE) on hypergraphs, aiming to determine the causal impact of interventions (e.g., wearing face covering) on outcomes (e.g., COVID-19 infection) for each individual node. Existing ITE estimation methods either assume no interference between individuals or consider interference only among connected individuals in regular graphs. However, such assumptions may not hold in real-world hypergraphs. Recognizing this, we propose a novel causality learning framework HyperSCI by modeling high-order interference on hyper-graphs. Through extensive experiments on real-world hypergraphs, we validate the effectiveness of HyperSCI and highlight the potential of causal inference in hypergraphs with complex group interactions. 1","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Welcome to the second issue of this year's AI Matters Newsletter. As usual, we will start the issue with a conference report by Louise A. Dennis. Following it, we are very excited to present three award-winning or candidacy papers by Wijmans et al. (ICLR 2023 Outstanding Paper), Ma et al. (SIGKDD 2022 Best Paper), and Li, Liu, and Wu (CVPR 2023, Award Candidate). The papers cover a range of intriguing topics, such as the formation of spatial memory in navigation agents, causal modeling with hypergraphs, and full-body motion estimation from egocentric videos. Finally, we end this issue by a collection of "blue sky" ideas presented in the AAAI/ACM SIGAI New and Future AI Educator Program at EAAI 2023, summarized by Guerzhoy et al.
{"title":"Welcome to AI Matters 9(2)","authors":"Ziyu Yao, Anuj Karpatne","doi":"10.1145/3609468.3609469","DOIUrl":"https://doi.org/10.1145/3609468.3609469","url":null,"abstract":"Welcome to the second issue of this year's AI Matters Newsletter. As usual, we will start the issue with a conference report by Louise A. Dennis. Following it, we are very excited to present three award-winning or candidacy papers by Wijmans et al. (ICLR 2023 Outstanding Paper), Ma et al. (SIGKDD 2022 Best Paper), and Li, Liu, and Wu (CVPR 2023, Award Candidate). The papers cover a range of intriguing topics, such as the formation of spatial memory in navigation agents, causal modeling with hypergraphs, and full-body motion estimation from egocentric videos. Finally, we end this issue by a collection of \"blue sky\" ideas presented in the AAAI/ACM SIGAI New and Future AI Educator Program at EAAI 2023, summarized by Guerzhoy et al.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：