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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/ai-ethics
课程评论:没有评论
课程名称:人工智能:伦理与社会挑战 概述:该课程为期四周,探讨人工智能技术(AI)日益使用带来的伦理和社会方面。课程旨在提高对AI伦理和社会影响的认知,并激发对AI在社会中应用的反思与讨论。课程包括四个模块,每个模块代表一个星期的兼职学习。每个模块包含多个讲座和阅读材料,每节课后都有一项强制性的作业,要求学生总结本节课获得的重要知识和见解,并审阅其他参与者的总结。评估旨在促进学习并激励对AI在社会中使用的伦理和社会问题的反思。参与论坛讨论是自愿的,但极力鼓励。 第一模块讨论算法偏见和监控。算法真的是完全逻辑且无偏见的吗?还是它们也可能与我们一样偏见?如果是,那么原因何在,我们能做些什么?AI在许多方面使监视变得更加有效,但如果我们以更复杂的方式被监视,这对我们意味着什么? 接下来,我们讨论AI对民主的影响。我们将讨论为什么民主重要,AI如何妨碍公众的民主讨论,同时它也能够改善民主。例如,我们将探讨社交媒体如何可能为威权政权所用,以及利用AI工具改善民主运作的一些想法。 课程的第三周关注伦理问题,即我们对人工智能的对待是否对它们本身重要。人工制品能够意识到自己吗?我们所谓的“意识”究竟是什么意思?意识与智力之间的关系是什么? 最后一个模块将讨论责任和控制。如果一辆自动驾驶汽车撞击一个自动机器人,谁负责?谁有责任确保AI以安全和民主的方式发展? 课程的最后一个问题,也是许多人类面临的终极问题,是如何控制比我们更聪明的机器。我们的智力赋予我们对所生活世界的权力。我们真的应该把这份权力交给机器吗?如果交出去,我们又该如何保持主导地位? 课程结束时,您将具备以下能力: - 对AI偏见现象和监控中AI的角色有基本理解 - 了解AI与民主之间的重要性,并熟悉相关的共同问题 - 理解“智力”和“意识”概念的复杂性,接触到创建人工意识的常见方法 - 理解“向前看”和“向后看”的责任概念,并了解将这些概念应用于AI时遇到的问题 - 有对AI控制问题的基本理解,并了解有关此问题的常见讨论解决方案 - 能够讨论和反思上述问题的伦理和社会方面。
Name:Algorithmic Bias and Surveillance
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Name:Democracy
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Name:Artificial Consciousness
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Name:Responsibility and Control
Description:
Artificial Intelligence: Ethics & Societal Challenges is a four-week course that explores ethical and societal aspects of the increasing use of artificial intelligent technologies (AI). The aim of the course is to raise awareness of ethical and societal aspects of AI and to stimulate reflection and discussion upon implications of the use of AI in society. The course consists of four modules where each module represents about one week of part-time studies. A module includes a number of lectures and readings. Each lesson finishes with a mandatory assignment in which you write a short sum-up of the most important new knowledge/insight you gained from this lesson, and review a lesson sum-up written by another student/participant. The assessments are intended to encourage learning and to stimulate reflection on ethical and societal issues of the use of AI in society. Participating in forum discussions is voluntary but strongly encouraged. In the first module, we will discuss algorithmic bias and surveillance. Is it really true that algorithms are purely logical and free from human biases or are they maybe just as biased as we are, and if they are, why is that and what can we do about it? AI in many ways makes surveillance more effective, but what does it mean to us if we are increasingly being watched in more and more sophisticated ways? Next, we will talk about the impact of AI on democracy. We discuss why democracy is important, and how AI could hamper public democratic discussion, but also how it can help improve democracy. We will for instance talk about how social media could play in the hands of authoritarian regimes and present some ideas on how to make use of AI tools to develop the functioning of democracy. A further ethical question concerns whether our treatment of AI could matter for the AIs themselves. Can artefacts be conscious? What do we even mean by “conscious”? What is the relationship between consciousness and intelligence? This is the topic of the third week of the course. In the last module we will talk about responsibility and control. If an autonomous car hits an autonomous robot, who is responsible? And who is responsible to make sure AI is developed in a safe and democratic way? The last question of the course, and maybe also the ultimate question for our species, is how to control machines that are more intelligent than we are. Our intelligence has given us a lot of power over the world we live in. Shall we really give that power away to machines and if we do, how do we stay in charge? At the end of the course, you will have · a basic understanding of the AI bias phenomenon and the role of AI in surveillance, · a basic understanding of the importance of democracy in relation to AI and acquaintance with common issues with democracy in relation to AI, · an understanding of the complexity of the concepts ‘intelligence’ and ‘consciousness’ and acquaintance with common approaches to creating artificial consciousness, · a basic understanding of the concepts of ‘forward-looking’ and ‘backward-looking responsibility’ and an acquaintance with problems connected to applying these concepts on AI, · a basic understanding of the control problem in AI and acquaintance with commonly discussed solutions to this problem, · and an ability to discuss and reflect upon the ethical and societal aspects of these issues.