Towards Establishing Criteria for the Ethical Analysis of Artificial Intelligence

Science and Engineering Ethics - Ethical reflection on Artificial Intelligence (AI) has become a priority. In this article, we propose a methodological model for a comprehensive ethical analysis of...     

Safety Engineering for Artificial General Intelligence

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we challenge the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement.     

逻辑与人工智能

20世纪中期以来,计算机科学以撼世惊人的速度不断向前发展.作为其核心分支的人工智能研究亦取得了一次又一次的突破,并且以其不断逼近与挑战人类智能的姿态而引人注目.在人工智能成就的背后,逻辑学是促其前行的最主要动力引擎之一.逻辑为人工智能提供了根本性的观点与方法,并促成了人工智能研究中最主要派别--逻辑主义AI.而有着漫长学科发展史的逻辑学本身也在与人工智能的结姻过程中获得了自数学公理化、形式化运动以来的又一次全新发展契机.有论者认为"人工智能将是21世纪逻辑学发展的主要动力源泉,并且在很大程度上将决定21世纪逻辑学的面貌".[1]     

人工智能医疗的三个逻辑

人们对人工智能医疗的发展普遍持乐观态度,仅有少数研究从数据相关的角度对其负面效应表示了谨慎的担心。研究回顾了支撑人工智能医疗发展的技术和市场逻辑指出,是冷战竞赛和经济衰退等历史偶然性导致了人工智能医疗对以错误率为代表的“客观”结果和市场规模、收购金额以及医院成本收益等“主观”价值的片面关注。但以“黑箱化”的方式忽略社会逻辑,尤其是对医疗体制尚不成熟的中国而言,不可避免地会引发专业人才缺口进一步加剧、优质医疗资源进一步集中,以及缺医少药的部分人群始终被排除在新技术的美好蓝图之外等一系列的严重后果。     

Artificial Intelligence and Medical Humanities

The use of artificial intelligence in healthcare has led to debates about the role of human clinicians in the increasingly technological contexts of medicine. Some researchers have argued that AI will augment the capacities of physicians and increase their availability to provide empathy and other uniquely human forms of care to their patients. The human vulnerabilities experienced in the healthcare context raise the stakes of new technologies such as AI, and the human dimensions of AI in healthcare have particular significance for research in the humanities. This article explains four key areas of concern relating to AI and the role that medical/health humanities research can play in addressing them: definition and regulation of “medical” versus “health” data and apps; social determinants of health; narrative medicine; and technological mediation of care. Issues include data privacy and trust, flawed datasets and algorithmic bias, racial discrimination, and the rhetoric of humanism and disability. Through a discussion of potential humanities contributions to these emerging intersections with AI, this article will suggest future scholarly directions for the field.

     

Incorporating Ethics into Artificial Intelligence

This article reviews the reasons scholars hold that driverless cars and many other AI equipped machines must be able to make ethical decisions, and the difficulties this approach faces. It then shows that cars have no moral agency, and that the term ‘autonomous’, commonly applied to these machines, is misleading, and leads to invalid conclusions about the ways these machines can be kept ethical. The article’s most important claim is that a significant part of the challenge posed by AI-equipped machines can be addressed by the kind of ethical choices made by human beings for millennia. Ergo, there is little need to teach machines ethics even if this could be done in the first place. Finally, the article points out that it is a grievous error to draw on extreme outlier scenarios—such as the Trolley narratives—as a basis for conceptualizing the ethical issues at hand.     

人工智能医疗器械的伦理审查要点

人工智能医疗器械分为具备辅助识别的二类和辅助诊断的三类医疗器械,我国三类人工智能医疗器械刚进入注册申报阶段。很多人工智能医疗器械以科研方式进入医疗机构,为受试者免费试用以获取临床试验数据,这给伦理审查带来极大挑战。伦理委员会审查三类人工智能医疗器械的核心问题包括风险评估、数据库、数据安全及软件更新。除关注医疗器械产品与试验操作外,更要从适用范围、研究要求与资料、研究方案、风险控制、数据库、数据安全和软件更新等方面仔细把关,不断总结经验,切实保护受试者权益,也助推我国人工智能医疗器械的健康快速发展。     

人工智能中知识获取面临的哲学困境及其未来走向

一人工智能中知识获取研究的现状所谓知识获取(knowledge acquistion,简称KA)就是把问题求解的专门知识(如事实、经验、规则等)从专家头脑或其他知识源(如书本、文献)中提取出来,然后将之转换成计算机系统内部表示的转换过程。综合而言,KA的任务是:获取领域专家或书本上的知识,在对其理解、选择、分析、抽取、汇集、分类和组织的基础上,转换成某种形式的系统内部表示;对已有的知识进行求精;检测并消除已有知识的矛盾性和冗余性,保持知识的一致性和完整约束性;通过某种推理或学习机制产生新的知识,扩充知识库。由于KA在人类智能活动中的重…     

The Human Side of Artificial Intelligence

Science and Engineering Ethics - Artificial moral agents raise complex ethical questions both in terms of the potential decisions they may make as well as the inputs that create their cognitive...     

Some Artificial Intelligence Tools for Argument Evaluation: An Introduction

Even though tools for identifying and analyzing arguments are now in wide use in the field of argumentation studies, so far there is a paucity of resources for evaluating real arguments, aside from using deductive logic or Bayesian rules that apply to inductive arguments. In this paper it is shown that recent developments in artificial intelligence in the area of computational systems for modeling defeasible argumentation reveal a different approach that is currently making interesting progress. It is shown how these systems provide the general outlines for a system of argument evaluation that can be applied to legal arguments as well as everyday conversational arguments to assist a user to evaluate an argument.     

一般人工智能概述(英文)

AGI是为解决传统人工智能存在的问题而产生的,更注重通用智能的基础问题和人工实现,与认知科学、心灵哲学也密切相关。本文通过介绍AGI的发展历史、AGI的定义及其与传统AI的关系以及一些有代表性的AGI方案等对AGI进行介绍。     

Rehabilitating AI: Argument Loci and the Case for Artificial Intelligence

This article examines argument structures and strategies in pro and con argumentation about the possibility of human-level artificial intelligence (AI) in the near term future. It examines renewed controversy about strong AI that originated in a prominent 1999 book and continued at major conferences and in periodicals, media commentary, and Web-based discussions through 2002. It will be argued that the book made use of implicit, anticipatory refutation to reverse prevailing value hierarchies related to AI. Drawing on Perelman and Olbrechts-Tyteca's (1969) study of refutational argument, this study considers points of contact between opposing arguments that emerged in opposing loci, dissociations, and casuistic reasoning. In particular, it shows how perceptions of AI were reframed and rehabilitated through metaphorical language, reversal of the philosophical pair artificial/natural, appeals to the paradigm case, and use of the loci of quantity and essence. Furthermore, examining responses to the book in subsequent arguments indicates the topoi characteristic of the rhetoric of technology advocacy.