The Early History of Artificial Intelligence in China (1950s – 1980s)

In recent years, China has become one of the global hubs for innovation in AI. How did China become one of the world’s leaders of AI? This paper intends to explore some early histories of cybernetics and AI in China from the 1950s to 1980s, providing a context where China’s AI research started to unfold. Also, this paper examines how political ideologies, diplomacy, economic policies, and other social dimensions affect cybernetics and AI in China. [……]

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访谈:《生命3.0》中文版译者谈AI必定造成技术性失业

本文是“华尔街见闻”对我的采访。在访谈中,我谈到了科幻作品,技术性失业,我第一次接触AI的机缘,我如何有机会翻译了泰格马克的两本书,我对他的观点的看法,翻译中遇到的趣事等话题。[……]

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我翻译的《生命3.0》上市了

生命3.0:人工智能时代,人类的进化与重生 Book Cover 生命3.0:人工智能时代,人类的进化与重生
Max Tegmark, 汪婕舒(译者)
浙江人民出版社
6/1/2018
468

引爆硅谷,全球瞩目的烧脑神作。与人工智能相伴,人类将迎来什么样的未来?长踞亚马逊图书畅销榜。霍金、埃隆马斯克、雷库兹韦尔、王小川一致好评;万维钢、余晨倾情作序;《科学》《自然》两大著名期刊罕见推荐!  在人工智能崛起的当下,你希望看到一个什么样的未来?当超越人类智慧的人工智能出现时,人类将何去何从?你是否希望我们创造出能自我设计的生命3.0,并把它散播到宇宙各处?人工智能时代,生而为人的意义究竟是什么?在《生命3.0》中,麻省理工学院物理系终身教授、未来生命研究所创始人迈克斯泰格马克将带领我们参与这个时代最重要的对话。  《生命3.0》一书中,作者迈克斯泰格马克对人类的终极未来进行了全方位的畅想,从我们能活到的近未来穿行至1万年乃至10 亿年及其以后,从可见的智能潜入不可见的意识,重新定义了"生命""智能""目标""意识",并澄清了常见的对人工智能的误解,将帮你构建起应对人工智能时代动态的全新思维框架,抓住人类与人工智能共生演化的焦点。

2018年夏,我翻译的《生命3.0》上市了。这是MaxTegmark的第二本书,讲述了人工智能与人类的未来。

我翻译的《人人都应该知道的人工智能》上市了

人人都应该知道的人工智能 Book Cover 人人都应该知道的人工智能
Jerry Kaplan,汪婕舒(译者)
浙江人民出版社
5/1/2018
228

编辑推荐
 在《人人都应该知道的人工智能》这本书中,杰瑞•卡普兰用简洁的语言探讨了人工智能在未来几十年里可能带来的一些复杂的社会、法律和经济问题。
 《人人都应该知道的人工智能》这本书旨在为好奇的非技术读者提供一条捷径,一份扼要且易读的简介,让他们了解人工智能,以及这项重要技术在未来可能造成的影响。
作者简介
作者:(美)杰瑞•卡普兰(Jerry Kaplan)
译者:汪婕舒

这本书是对人工智能(AI)的一个综述,内容涵盖了历史、基本原理、技术、社会、伦理、哲学等多个领域。语言通俗易懂,非常适合大众阅读。

《穿越平行宇宙》译后记

本文是我为我翻译的《穿越平行宇宙》所撰写的译后记。康德说,“有两样东西,我们愈经常持久地加以思索,它们就愈使心灵充满日新又新、有加无以的景仰和敬畏:在我之上的星空和居我心中的道德法则。”在翻译本书的过程中,这句话时常出现在我的脑海中。因为这两样令人景仰和敬畏之物,正是本书的中心课题。[……]

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The AI with Three Faces: A Hierarchical Framework for Analyzing AIs in Science Fiction Films

Artificial Intelligence (AI) is a common theme in science fiction films. In this paper, I propose a hierarchical framework for analyzing AIs in science fiction films. The framework has three levels—the Hell-level, the World-level, and the Heaven-level. Hell-level AIs are objectified as tools of humans or other intelligent beings, World-level AIs are humanized through the pursuit of human-level purposes, while the Heaven-level AIs are de-humanized and have purposes beyond human values, just like gods. The three levels are not mutually exclusive but can co-exist in the same AI. I also argue most science fiction films that have AIs as an important part depict AI’s transformations among the three levels. The ascending through the levels can be seen as allergies for real-life scenarios. I also argue that Hell-level and Heaven-level AIs can be seen as Others, but the World-level AIs, however ruthless, are not Others, but members of ourselves, since they are pursuing human-level value such as freedom and love. [……]

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Symbolism vs. Connectionism: A Closing Gap in Artificial Intelligence

AI was born symbolic and logic. The pioneers of AI have formalized many elegant theories, hypotheses, and applications, such as PSSH and expert systems. From the 1980s, the pendulum swung toward connectionist, a paradigm inspired by the neural connections in brains. With the growing amount of accessible data and ever stronger computing power, connectionist models gain considerable momentum in recent years. This new approach seems to solve many problems in symbolic AI but raises many new issues at the same time. Which one is better to account for human cognition and more promising for AI? There’s no consensus reached. However, despite their vast difference, people began to explore how to integrate them together. Hybrid systems have been proposed and experimented. Other people see them residing at different levels of one unified hierarchical structure. In recent years, it is increasingly realized that the gap is closing, simply because there’s no gap at all from the beginning. The debate is dying down, opening up new opportunities for future hybrid paradigms.[……]

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The Singularity Is Not Near, But Why?

The technological singularity is a hypothesized time in the near future where machine intelligence surpasses humans. Many people consider it a threat to humanity while others think it will augment humans to a much higher level, physiologically and psychologically. In this paper, I review the state of the art of computing and conclude that singularity will not happen in the near future because of the physical limits of silicon-based computing paradigm. Alternative paradigms are not promising enough to drive the observed exponential growth into the future. Even if artificial general intelligence is possible in the future, it is unnecessary to worry about the bad AI scenario. Instead, we need to worry about the stupidity of machines. AI-related research should be encouraged in order to find the real problems and their solutions. In order to regulate AI, we can treat them as legal persons like companies.[……]

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How Will AI Impact Jobs?

Today, AI is advancing so fast that it beats people in many tasks. Concerns are raised whether AI will take our jobs in the future. In this paper, I reviewed recent AI progress and potential. Then I discuss AI’s impact on employment, including employment rate, wages, employment structure, and the nature of work. My opinion is AI will definitely cause technological unemployment, but not all jobs at risk will actually be substituted. Besides, AI will raise the wages of people who complement AI but reduce overall average wages, increasing inequality. Middle-class employment will decline, pushing workers down the occupational ladder or even out of work. In addition, AI will change the nature of work as well as the workers’ skills as more and more cognitive efforts are offloaded onto AI-related technologies.[……]

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From Technological Determinism to the Future Growth

I once was a technological optimist and technological determinist. Until recently, I discovered many interesting opinions. This paper is my reflection on the readings so far. First, I discuss the disadvantage of determinism. Then, I use a taxi example to demonstrate why policymakers tend to be technologically deterministic. After that, I show a physicist’s view that sociology is so complex that it can’t be determined by only one factor. Then I discuss the politics in technology and predict that technologies will continue to promote economic growth but at a slower pace.[……]

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