Every day, governmental and federally funded agencies --- including criminal courts, welfare agencies, and educational institutions --- make decisions about resource allocation using automated decision-making tools (Lecher, 2018; Fishel, Flack, & DeMatteo, 2018). Important factors surrounding the use of these tools are embedded both in their design and in the policies and practices of the various agencies that implement them. As the use of such tools is becoming more common, a number of questions have arisen about whether using these tools is fair, or in some cases, even legal (K.W. v. Armstrong, 2015; ACLU, Outten & Golden LLP, and the Communications Workers of America, 2019).
{"title":"The scales of (algorithmic) justice","authors":"M. Sun, Marissa Gerchick","doi":"10.1145/3340470.3340478","DOIUrl":"https://doi.org/10.1145/3340470.3340478","url":null,"abstract":"Every day, governmental and federally funded agencies --- including criminal courts, welfare agencies, and educational institutions --- make decisions about resource allocation using automated decision-making tools (Lecher, 2018; Fishel, Flack, & DeMatteo, 2018). Important factors surrounding the use of these tools are embedded both in their design and in the policies and practices of the various agencies that implement them. As the use of such tools is becoming more common, a number of questions have arisen about whether using these tools is fair, or in some cases, even legal (K.W. v. Armstrong, 2015; ACLU, Outten & Golden LLP, and the Communications Workers of America, 2019).","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"5 1","pages":"30 - 40"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3340470.3340478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46906379","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 eighth interview profiling a senior AI researcher. This time we will hear from Leslie Kaelbling, Panasonic Professor of Computer Science and Engineering in the Department of Electrical Engineering and Computer Science at MIT.
{"title":"AI profiles","authors":"Marion Neumann","doi":"10.1145/3340470.3340472","DOIUrl":"https://doi.org/10.1145/3340470.3340472","url":null,"abstract":"Welcome to the eighth interview profiling a senior AI researcher. This time we will hear from Leslie Kaelbling, Panasonic Professor of Computer Science and Engineering in the Department of Electrical Engineering and Computer Science at MIT.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"5 1","pages":"4 - 5"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3340470.3340472","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49513871","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}
Language is the primary and most natural means of communication for humans. The learning curve of interacting with various services (e.g., digital assistants, and smart appliances) would be greatly reduced if we could talk to machines using human language. However, in most cases computers can only interpret and execute formal languages.
{"title":"Learning natural language interfaces with neural models","authors":"Li Dong","doi":"10.1145/3478369.3478375","DOIUrl":"https://doi.org/10.1145/3478369.3478375","url":null,"abstract":"Language is the primary and most natural means of communication for humans. The learning curve of interacting with various services (e.g., digital assistants, and smart appliances) would be greatly reduced if we could talk to machines using human language. However, in most cases computers can only interpret and execute formal languages.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"7 1","pages":"14 - 17"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49346504","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 is a regular column in AI Matters featuring summaries and commentary based on postings that appear twice a month in the AI Matters blog (https://sigai.acm.org/aimatters/blog/). Selected posts are summarized in issues of AI Matters.
AI Policy是AI Matters的一个常规专栏,根据每月两次出现在AI Matters博客上的帖子进行总结和评论(https://sigai.acm.org/aimatters/blog/)。选定的员额载于《人工智能事项》。
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Welcome to the first issue of the fifth volume of the AI Matters Newsletter! This issue opens with some news on a new SIGAI Student Travel Scholarship where we aim to encourage students from traditionally underrepresented geographic locations to apply and attend SIGAI supported events. We also summarize the fourth AAAI/ACM SIGAI Job Fair, which continues to grow with the increasing popularity of AI. In our interview series, Marion Neumann interviews Tom Dietterich, an Emeritus Professor at Oregon State University and one of the pioneers in Machine Learning.
{"title":"Welcome to AI matters 5(1)","authors":"A. McGovern, Iolanda Leite","doi":"10.1145/3320254.3320255","DOIUrl":"https://doi.org/10.1145/3320254.3320255","url":null,"abstract":"Welcome to the first issue of the fifth volume of the AI Matters Newsletter! This issue opens with some news on a new SIGAI Student Travel Scholarship where we aim to encourage students from traditionally underrepresented geographic locations to apply and attend SIGAI supported events. We also summarize the fourth AAAI/ACM SIGAI Job Fair, which continues to grow with the increasing popularity of AI. In our interview series, Marion Neumann interviews Tom Dietterich, an Emeritus Professor at Oregon State University and one of the pioneers in Machine Learning.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":" ","pages":"3 - 3"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3320254.3320255","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45893543","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}
D. Hemment, R. Aylett, Vaishak Belle, Dave Murray-Rust, E. Luger, J. Hillston, Michael Rovatsos, F. Broz
Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. It addresses the challenge of finding novel ways of opening up the field of artificial intelligence to greater transparency and collaboration between human and machine. The hypothesis is that art can mediate between computer code and human comprehension to overcome the limitations of explanations in and for AI systems. Artists can make the boundaries of systems visible and offer novel ways to make the reasoning of AI transparent and decipherable. Beyond this, artistic practice can explore new configurations of humans and algorithms, mapping the terrain of inter-agencies between people and machines. This helps to viscerally understand the complex causal chains in environments with AI components, including questions about what data to collect or who to collect it about, how the algorithms are chosen, commissioned and configured or how humans are conditioned by their participation in algorithmic processes.
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As part of its portfolio of student-oriented activities, SIGAI regularly supports its members through the provision of travel scholarships. To date, these have been primarily allocated to key conferences (co-)sponsored by SIGAI, but as the number of events we support formally (whether through financial sponsorship or "in-cooperation" status) has increased substantially, we have identified a need to reach out to a broader community of students participating in, and contributing to, a broader range of events.
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Prolog is a great language to include in an undergraduate AI course. Its logical programming paradigm challenges students to write code in a way that is usually very different from their other courses. Students struggle with its approach but, in my experience, come to appreciate its ability to handle a broad range of AI tasks elegantly.
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The ideal value of an AI Cosmology would be to help the general public, researchers, educators, and practitioners to devise the truth of the definition, meaning, applications, and implications of Artificial Intelligence. The pursuit of that truth even if through an arbitrary contrivance would be a noteworthy goal. The fact of the matter is whether any cosmological structure we have hinted at so far tracks the underlying reality, we cannot escape that there is an underlying reality. At some point in time, we (humans) began the endeavor of trying to replicate the human mind with machines. There was first an effort to understand the human mind, describe its inner workings, and then build machines that could essentially duplicate the thinking process. Surely this point in time must mark or at least point to the Cosmological "Big Bang" for AI. Right?
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Welcome to the eighth interview in our series profiling senior AI researchers. This month we are especially happy to interview our SIGAI advisory board member, Thomas Dietterich, Director of Intelligent Systems at the Institute for Collaborative Robotics and Intelligence Systems (CoRIS) at Oregon State University.
{"title":"AI profiles","authors":"Marion Neumann","doi":"10.1145/3320254.3320258","DOIUrl":"https://doi.org/10.1145/3320254.3320258","url":null,"abstract":"Welcome to the eighth interview in our series profiling senior AI researchers. This month we are especially happy to interview our SIGAI advisory board member, Thomas Dietterich, Director of Intelligent Systems at the Institute for Collaborative Robotics and Intelligence Systems (CoRIS) at Oregon State University.","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"5 1","pages":"7 - 9"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3320254.3320258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64018247","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}