Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society最新文献_第3页

Framing Artificial Intelligence in American Newspapers 在美国报纸上构建人工智能

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314285

C. Chuan, W. Tsai, Sumi Cho

引用次数: 55

Epistemic Therapy for Bias in Automated Decision-Making 自动化决策中偏见的认知疗法

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314294

T. Gilbert, Yonatan Dov Mintz

引用次数: 8

Invisible Influence: Artificial Intelligence and the Ethics of Adaptive Choice Architectures 无形的影响:人工智能和自适应选择架构的伦理

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314286

Daniel Susser

{"title":"Invisible Influence: Artificial Intelligence and the Ethics of Adaptive Choice Architectures","authors":"Daniel Susser","doi":"10.1145/3306618.3314286","DOIUrl":"https://doi.org/10.1145/3306618.3314286","url":null,"abstract":"For several years, scholars have (for good reason) been largely preoccupied with worries about the use of artificial intelligence and machine learning (AI/ML) tools to make decisions about us. Only recently has significant attention turned to a potentially more alarming problem: the use of AI/ML to influence our decision-making. The contexts in which we make decisions--what behavioral economists call our choice architectures--are increasingly technologically-laden. Which is to say: algorithms increasingly determine, in a wide variety of contexts, both the sets of options we choose from and the way those options are framed. Moreover, artificial intelligence and machine learning (AI/ML) makes it possible for those options and their framings--the choice architectures--to be tailored to the individual chooser. They are constructed based on information collected about our individual preferences, interests, aspirations, and vulnerabilities, with the goal of influencing our decisions. At the same time, because we are habituated to these technologies we pay them little notice. They are, as philosophers of technology put it, transparent to us--effectively invisible. I argue that this invisible layer of technological mediation, which structures and influences our decision-making, renders us deeply susceptible to manipulation. Absent a guarantee that these technologies are not being used to manipulate and exploit, individuals will have little reason to trust them.","PeriodicalId":418125,"journal":{"name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123933870","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}

引用次数: 35

Towards Emotional Intelligence in Social Robots Designed for Children 面向儿童设计的社交机器人中的情商

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314319

De'Aira G. Bryant

{"title":"Towards Emotional Intelligence in Social Robots Designed for Children","authors":"De'Aira G. Bryant","doi":"10.1145/3306618.3314319","DOIUrl":"https://doi.org/10.1145/3306618.3314319","url":null,"abstract":"Social robots are robots designed to interact and communicate directly with humans, following traditional social norms. However, many of these current robots operate in discrete settings with predefined expectations for specific social interactions. In order for these machines to operate in the real world, they must be capable of understanding the multiple factors that contribute to human-human interaction. One such factor is emotional intelligence. Emotional intelligence allows one to consider the emotional state of another in order to motivate, plan, and achieve one's desires. One common method of analyzing the emotional state of an individual involves analyzing the emotion displayed on their face. Several artificial intelligence (AI) systems have been developed to conduct this task. These systems are often classifiers trained using a variety of machine learning techniques which require large amounts of training data. As such, they are susceptible to biases that may appear during performance analyses due to disproportions existing in training datasets. Children, in particular, are often less represented in the primary datasets of annotated faces used for training such emotion classification systems. This work seeks to first analyze the extent of these performance differences in commercial systems, then to present new computational techniques that work to mitigate some of the effects of minimal representation in datasets, and to finally present a social robot which utilizes an improved emotional AI to interact with children in various scenarios where emotional intelligence is key to successful human-robot interaction.","PeriodicalId":418125,"journal":{"name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117170853","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}

引用次数: 2

The Seductive Allure of Artificial Intelligence-Powered Neurotechnology 人工智能驱动的神经技术的诱人诱惑

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314269

C. Giattino, Lydia Kwong, Chad Rafetto, Nita A. Farahany

{"title":"The Seductive Allure of Artificial Intelligence-Powered Neurotechnology","authors":"C. Giattino, Lydia Kwong, Chad Rafetto, Nita A. Farahany","doi":"10.1145/3306618.3314269","DOIUrl":"https://doi.org/10.1145/3306618.3314269","url":null,"abstract":"Neuroscience explanations-even when completely irrelevant-have been shown to exert a \"seductive allure\" on individuals, leading them to judge bad explanations or arguments more favorably. There seems to be a similarly seductive allure for artificial intelligence (AI) technologies, leading people to \"overtrust\" these systems, even when they have just witnessed the system perform poorly. The AI-powered neurotechnologies that have begun to proliferate in recent years, particularly those based on electroencephalography (EEG), represent a potentially doubly-alluring combination. While there is enormous potential benefit in applying AI techniques in neuroscience to \"decode\" brain activity and associated mental states, these efforts are still in the early stages, and there is a danger in using these unproven technologies prematurely, especially in important, real-world contexts. Yet, such premature use has begun to emerge in several high-stakes set-tings, including the law, health & wellness, employment, and transportation. In light of the potential seductive allure of these technologies, we need to be vigilant in monitoring their scientific validity and challenging both unsubstantiated claims and misuse, while still actively supporting their continued development and proper use.","PeriodicalId":418125,"journal":{"name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115366892","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}

引用次数: 9

The Role and Limits of Principles in AI Ethics: Towards a Focus on Tensions 原则在人工智能伦理中的作用和限制:关注紧张关系

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314289

Jess Whittlestone, Rune Nyrup, A. Alexandrova, S. Cave

{"title":"The Role and Limits of Principles in AI Ethics: Towards a Focus on Tensions","authors":"Jess Whittlestone, Rune Nyrup, A. Alexandrova, S. Cave","doi":"10.1145/3306618.3314289","DOIUrl":"https://doi.org/10.1145/3306618.3314289","url":null,"abstract":"The last few years have seen a proliferation of principles for AI ethics. There is substantial overlap between different sets of principles, with widespread agreement that AI should be used for the common good, should not be used to harm people or undermine their rights, and should respect widely held values such as fairness, privacy, and autonomy. While articulating and agreeing on principles is important, it is only a starting point. Drawing on comparisons with the field of bioethics, we highlight some of the limitations of principles: in particular, they are often too broad and high-level to guide ethics in practice. We suggest that an important next step for the field of AI ethics is to focus on exploring the tensions that inevitably arise as we try to implement principles in practice. By explicitly recognising these tensions we can begin to make decisions about how they should be resolved in specific cases, and develop frameworks and guidelines for AI ethics that are rigorous and practically relevant. We discuss some different specific ways that tensions arise in AI ethics, and what processes might be needed to resolve them.","PeriodicalId":418125,"journal":{"name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132854883","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}

引用次数: 158

Artificial Intelligence's Impact on Mental Health Treatments 人工智能对心理健康治疗的影响

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314311

Michelle C. Ausman

引用次数: 4

Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure 通过学习潜结构发现和减轻算法偏差

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314243

Alexander Amini, A. Soleimany, Wilko Schwarting, S. Bhatia, D. Rus

引用次数: 156

AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI 人工智能扩展:人工智能认知扩展对人类的伦理和社会影响

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314238

J. Hernández-Orallo, Karina Vold

引用次数: 42

Towards a Just Theory of Measurement: A Principled Social Measurement Assurance Program for Machine Learning 迈向公正的测量理论:一个有原则的机器学习社会测量保证计划

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society Pub Date : 2019-01-27 DOI: 10.1145/3306618.3314275

McKane Andrus, T. Gilbert

{"title":"Towards a Just Theory of Measurement: A Principled Social Measurement Assurance Program for Machine Learning","authors":"McKane Andrus, T. Gilbert","doi":"10.1145/3306618.3314275","DOIUrl":"https://doi.org/10.1145/3306618.3314275","url":null,"abstract":"While formal definitions of fairness in machine learning (ML) have been proposed, its place within a broader institutional model of fair decision-making remains ambiguous. In this paper we interpret ML as a tool for revealing when and how measures fail to capture purported constructs of interest, augmenting a given institution's understanding of its own interventions and priorities. Rather than codifying \"fair\" principles into ML models directly, the use of ML can thus be understood as a form of quality assurance for existing institutions, exposing the epistemic fault lines of their own measurement practices. Drawing from Friedler et al's [2016] recent discussion of representational mappings and previous discussions on the ontology of measurement, we propose a social measurement assurance program (sMAP) in which ML encourages expert deliberation on a given decision-making procedure by examining unanticipated or previously unexamined covariates. As an example, we apply Rawlsian principles of fairness to sMAP and produce a provisional just theory of measurement that would guide the use of ML for achieving fairness in the case of child abuse in Allegheny County.","PeriodicalId":418125,"journal":{"name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122593818","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}

引用次数: 4