2020 IEEE International Symposium on Technology and Society (ISTAS)最新文献

A Costly Emergencies Approach to Estimating Costs for Artificial Intelligence Review 人工智能评估成本的昂贵应急方法

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462212

Sara R. Jordan

{"title":"A Costly Emergencies Approach to Estimating Costs for Artificial Intelligence Review","authors":"Sara R. Jordan","doi":"10.1109/ISTAS50296.2020.9462212","DOIUrl":"https://doi.org/10.1109/ISTAS50296.2020.9462212","url":null,"abstract":"Artificial intelligence (AI) research is increasingly considered to be a risky endeavor. The present prevailing model of AI risk management imports the commitments of research ethics, in terms of principles, approach to risk assessment, mitigation, and management. Despite the history and appeal of the research ethics model, alternative models for evaluation of AI risk should be entertained before adopting this approach. Here we propose a hypothetical applied information economics approach that changes the model for risk review from ex ante hypotheticals paid for as a fixed cost borne by all to variable costs that could be calculated in response to consumers’ willingness to pay for risky technology or to be paid for by companies willing to shoulder the cost of risks. Some of these risks will be of such magnitude that mitigating them constitutes an existential emergency for which an ex-ante research review approach may be justifiable. But, for risks that are less than non-remediable, existential, threats, a more cost sensitive approach may represent a more equitable path that shifts costs to those willing to bear them. We approach thinking through AI risks as something with specific costs we can estimate using known risks from similar activities of daily life.","PeriodicalId":196560,"journal":{"name":"2020 IEEE International Symposium on Technology and Society (ISTAS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123142560","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: 1

Risks of Bias in AI-Based Emotional Analysis Technology from Diversity Perspectives 多样性视角下基于人工智能的情感分析技术的偏见风险

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462168

Sumiko Shimo

引用次数: 0

The Effect of Tracking and Reflecting on Study Habits on Study Behavior and Grades 学习习惯的跟踪与反思对学习行为和成绩的影响

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462241

D. Y. Wohn, Michael J. Lee

引用次数: 1

In Search of a Pattern and Algorithmic Code for COVID-19: A Participant Self-Customized Awareness Systems for Diagnostics, Simulation, Tracing and Pattern Matching 寻找COVID-19的模式和算法代码:用于诊断、模拟、跟踪和模式匹配的参与者自定义意识系统

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462189

A. Ebrahimi

{"title":"In Search of a Pattern and Algorithmic Code for COVID-19: A Participant Self-Customized Awareness Systems for Diagnostics, Simulation, Tracing and Pattern Matching","authors":"A. Ebrahimi","doi":"10.1109/ISTAS50296.2020.9462189","DOIUrl":"https://doi.org/10.1109/ISTAS50296.2020.9462189","url":null,"abstract":"The COVID-19 pandemic has become a challenge to our lives and affects us differently under certain circumstances. This project invites and assists participants in developing their awareness systems for COVID-19. The system comes with a set up consisting of standard information and the necessary coding explained to the participant. The findings are open and shared through an honor system. The awareness system consists of four embedded subsystems known as diagnostics systems, simulation, tracing, and pattern-matching systems. The diagnostic system uses inference rules to generate an outcome by diseases with the same symptoms related to COVID-19. The skeleton for the simulation system works as a game, depicting how the virus enters and interacts with the body's cells with different four scenarios such as involved in defeating the body's cell, defeating the virus, neutral coexistence of the virus and enclosure, and at best, turning into a positive virus. At that stage of defeating the body's cell, the virus will replicate itself by an assigned degree with a recursive behavior. The tracing system traces the COVID19 and the participant's health using red, green, and blue (RGB) colors. The combination of RGB creates more than 16 million using 24 bits in binary or hexadecimal. The red color reserves for COVID-19, with 16 shades of red for a symptom with a 16 degree of severity. The pattern-matching system's skeleton provides four databases for asymptomatic, mild, severe, and fatal cases. The digitized information will quickly identify the pattern. One database may compare with another database for similarities or differences.The transfer of learning from one system can flow into another, ultimately resulting in a solution pattern. This project's implication will guide others to initiate their participant system to find a way and formulate a solution.","PeriodicalId":196560,"journal":{"name":"2020 IEEE International Symposium on Technology and Society (ISTAS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115015604","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: 0

Tesseract Optimization for Data Privacy and Sharing Economics 面向数据隐私和共享经济的立方体优化

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462236

Shubhadip Ray, Tharangini Palanivel, Norbert Herman, Yixuan Li

{"title":"Tesseract Optimization for Data Privacy and Sharing Economics","authors":"Shubhadip Ray, Tharangini Palanivel, Norbert Herman, Yixuan Li","doi":"10.1109/ISTAS50296.2020.9462236","DOIUrl":"https://doi.org/10.1109/ISTAS50296.2020.9462236","url":null,"abstract":"As human beings, we have the inherent bias towards our likes and dislikes. These likes and dislikes are influenced by our psychographic attributes, morals, values, beliefs and societal networks in both circles of influence and circles of concern. We continuously consume products, services as well as produce products and services for others to consume. Due to our inherent bias of likes and dislikes, we unintentionally or intentionally end up liking products and/or services that are personalized for us, or somehow unintentionally match our likes. This personalization makes our lives easier and more comfortable as it may save time, and/or enable us to achieve desired experiences. This personalization is influenced by the data gathered about us directly or indirectly. The richer the data is about us, the more personalized products and services we receive, thereby saving us time and money whilst meeting our desired goals for experience or exchange of value for the offers we are wanting. We remain forever concerned about the direct or accidental use of our data that can fall into the hands of nefarious users of the dark web, or criminals who can cause us all kinds of harm using the data we shared. Herein lies the paradox of personalization and privacy. To solve this paradox, we acknowledge that there has to be a trade-off between data privacy and personalization, and an optimized match on trust, value etc. between the data owners (data subjects) and data buyers. In this paper, we propose approaches to handle these trade-offs in an optimized way with the acceptance threshold determined by a methodology to optimize the match between trust and value perceptions specific to an individual, and in context of the trust we place on the data controller, processor or buyer entity with which we share and entrust our data for the exchange of value provided.","PeriodicalId":196560,"journal":{"name":"2020 IEEE International Symposium on Technology and Society (ISTAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114460025","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: 0

Ethical Concerns: An overview of Artificial Intelligence System Development and Life Cycle 伦理关注:人工智能系统发展与生命周期概述

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462201

Hassan Al Shazly, A. Ferraro, K. Bennet

引用次数: 0

Categorizing Online Harassment Interventions 在线骚扰干预分类

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462206

Chenlu Feng, D. Y. Wohn

引用次数: 1

Using Open Source Licensing to Regulate the Assembly of LAWS: A Preliminary Analysis 使用开源许可规范法律汇编:初步分析

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462195

Cheng Lin, AJung Moon

{"title":"Using Open Source Licensing to Regulate the Assembly of LAWS: A Preliminary Analysis","authors":"Cheng Lin, AJung Moon","doi":"10.1109/ISTAS50296.2020.9462195","DOIUrl":"https://doi.org/10.1109/ISTAS50296.2020.9462195","url":null,"abstract":"Lethal autonomous weapons (LAWS) are an emerging technology capable of automatically targeting and exercising lethal force. Many scholars and advocates have petitioned to ban the technology internationally for a myriad of reasons. However, there are practical challenges to implementing a ban. One such challenge is posed by the “intangible” nature of the software that LAWS depends on, which is incompatible with implementation mechanisms such as export control. Given the dual-use nature of software, and the fact that software is developed by teams of individuals, a number of soft governance mechanisms have been proposed to regulate this technology. In this paper, we investigate the feasibility of one particular approach: leveraging open source licenses as a means to prohibit the use of certain software in LAWS. This approach is largely motivated by the fact that open source software underpins all of technology, especially AI. Through a review of the recent tech activism and open source activism, we evaluate whether open source licenses can feasibly limit the use of open source software to only non-LAWS applications. We distill the current challenges facing “ethics-driven” open source licensing efforts into three main obstacles: the need for clarity of licensing language, the lack of enforceability of licenses, and the lack of cohesiveness of the open source community. We propose that addressing these factors are also success criteria for future anti-LAWS open source initiatives. We find that open source licenses provide more theoretical than practical promise in regulating LAWS, and conclude that cohesion in the open source community is the key to their potential practical success in the future.","PeriodicalId":196560,"journal":{"name":"2020 IEEE International Symposium on Technology and Society (ISTAS)","volume":"225 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114539586","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: 0

Aging in Smart Environments for Independence 智能环境下的老龄化

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462211

Jordan Miller, T. McDaniel, M. Bernstein

引用次数: 3

Body Modifications and Their Health Implications 身体变化及其健康影响

2020 IEEE International Symposium on Technology and Society (ISTAS) Pub Date : 2020-11-12 DOI: 10.1109/ISTAS50296.2020.9462217

Lauryn Remmers, Katina Michael

引用次数: 0