A Call to Arms: Embrace Assistive AI Systems!

A. Broder
{"title":"A Call to Arms: Embrace Assistive AI Systems!","authors":"A. Broder","doi":"10.1145/3159652.3160603","DOIUrl":null,"url":null,"abstract":"A quarter-century ago Web search stormed the world: within a few years the Web search box became a standard tool of daily life ready to satisfy informational, transactional, and navigational queries needed for some task completion. However, two recent trends are dramatically changing the box»s role: first, the explosive spread of smartphones brings significant computational resources literally into the pockets of billions of users; second, recent technological advances in machine learning and artificial intelligence, and in particular in speech processing led to the wide deployment of assistive AI systems, culminating in personal digital assistants. Along the way, the \"Web search box\" has become an \"assistance request box\" (implicit, in the case of voice-activated assistants) and likewise, many other information processing systems (e.g. e-mail, navigation, personal search, etc) have adopted assistive aspects. Formally, the assistive systems can be viewed as a selection process within a base set of alternatives driven by some user input. The output is either one alternative or a smaller set of alternatives, maybe subject to future selection. Hence, classic IR is a particular instance of this formulation, where the input is a textual query and the selection process is relevance ranking over the corpus. In increasing order of selection capabilities, assistive systems can be classified into three categories: Subordinate : systems where the selection is fully specified by the request; if this results in a singleton the system provides it, otherwise the system provides a random alternative from the result set. Therefore, the challenge for subordinate systems consists only in the correct interpretation of the user request (e.g., weather information, simple personal schedule management, a \"play jazz\" request). Conducive : systems that reduce the set of alternatives to a smaller set, possibly via an interactive process (e.g. the classic ten blue links, the three \"smart replies\" in Gmail, interactive recommendations, etc). Decisive : systems that make all necessary decisions to reach the desired goal (in other words, select a single alternative from the set of possibilities) including resolving ambiguities and other substantive decisions without further input from the user (e.g., typical translation systems, self-driving cars). The main goal of this talk is to examine these developments and to urge the WSDM community to increase its focus on assistive AI solutions that are becoming pertinent to a wide variety of information processing problems. I will mostly present ideas and work in progress, and there will be many more open questions than definitive answers.","PeriodicalId":401247,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3159652.3160603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

A quarter-century ago Web search stormed the world: within a few years the Web search box became a standard tool of daily life ready to satisfy informational, transactional, and navigational queries needed for some task completion. However, two recent trends are dramatically changing the box»s role: first, the explosive spread of smartphones brings significant computational resources literally into the pockets of billions of users; second, recent technological advances in machine learning and artificial intelligence, and in particular in speech processing led to the wide deployment of assistive AI systems, culminating in personal digital assistants. Along the way, the "Web search box" has become an "assistance request box" (implicit, in the case of voice-activated assistants) and likewise, many other information processing systems (e.g. e-mail, navigation, personal search, etc) have adopted assistive aspects. Formally, the assistive systems can be viewed as a selection process within a base set of alternatives driven by some user input. The output is either one alternative or a smaller set of alternatives, maybe subject to future selection. Hence, classic IR is a particular instance of this formulation, where the input is a textual query and the selection process is relevance ranking over the corpus. In increasing order of selection capabilities, assistive systems can be classified into three categories: Subordinate : systems where the selection is fully specified by the request; if this results in a singleton the system provides it, otherwise the system provides a random alternative from the result set. Therefore, the challenge for subordinate systems consists only in the correct interpretation of the user request (e.g., weather information, simple personal schedule management, a "play jazz" request). Conducive : systems that reduce the set of alternatives to a smaller set, possibly via an interactive process (e.g. the classic ten blue links, the three "smart replies" in Gmail, interactive recommendations, etc). Decisive : systems that make all necessary decisions to reach the desired goal (in other words, select a single alternative from the set of possibilities) including resolving ambiguities and other substantive decisions without further input from the user (e.g., typical translation systems, self-driving cars). The main goal of this talk is to examine these developments and to urge the WSDM community to increase its focus on assistive AI solutions that are becoming pertinent to a wide variety of information processing problems. I will mostly present ideas and work in progress, and there will be many more open questions than definitive answers.
战斗的召唤:拥抱辅助人工智能系统!
四分之一个世纪以前,网络搜索席卷了世界:在几年内,网络搜索框成为日常生活的标准工具,可以满足完成某些任务所需的信息、事务和导航查询。然而,最近的两个趋势正在戏剧性地改变盒子的角色:首先,智能手机的爆炸式普及将大量的计算资源带入了数十亿用户的口袋;其次,最近机器学习和人工智能方面的技术进步,特别是语音处理方面的技术进步,导致了辅助人工智能系统的广泛部署,最终出现了个人数字助理。在此过程中,“网页搜索框”变成了“辅助请求框”(在声控助手的情况下是隐含的),同样,许多其他信息处理系统(如电子邮件、导航、个人搜索等)也采用了辅助方面。形式上,辅助系统可以被看作是由一些用户输入驱动的一组基本选择中的一个选择过程。输出是一个备选方案或一个较小的备选方案集,可能取决于将来的选择。因此,经典IR是该公式的一个特殊实例,其中输入是文本查询,选择过程是对语料库的相关性排序。按照选择能力的递增顺序,辅助系统可分为三类:从属:完全由请求指定选择的系统;如果结果是单例,系统将提供它,否则系统将从结果集中提供一个随机的替代。因此,下级系统的挑战只在于正确解释用户请求(例如,天气信息、简单的个人日程管理、“播放爵士乐”请求)。有益的:可以通过交互过程(例如,经典的十个蓝色链接,Gmail中的三个“智能回复”,交互式推荐等),将一组选择减少到更小的系统。决定性:做出所有必要决策以达到预期目标的系统(换句话说,从一组可能性中选择一个替代方案),包括在没有用户进一步输入的情况下解决歧义和其他实质性决策(例如,典型的翻译系统,自动驾驶汽车)。这次演讲的主要目标是检查这些发展,并敦促WSDM社区增加对辅助AI解决方案的关注,这些解决方案正在与各种各样的信息处理问题相关。我将主要介绍我的想法和正在进行的工作,还有更多悬而未决的问题,而不是明确的答案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信