分类目录归档：Artificial Intelligence

AI-augmented Innovation Must Bend the Spoon

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In the movie Matrix, when Neo visited the Oracle in the Matrix, he met a boy who can bend spoons with his mind. Neo was taught that to bend the spoon, try not to, because it was impossible according to physical rules. “Instead, only try to realize the truth,” said the boy, “there is no spoon.” What was bent here was not the spoon, but the rules used by the Matrix to create the virtual space. In the movie, this realization became essential for Neo to fight against the Matrix. It turns out that it is also the key to achieve AI-augmented innovation. [……]

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How to Expect a Smart Future: An Essay on Artificial Intelligence, Responsible Innovation, and Anticipatory Governance

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This essay talks about Artificial Intelligence (AI) and Responsible Innovation (RI), especially the dimension of anticipatory governance. The vast potential of AI has sparked off a heated debate about how to regulate AI. I argue that RI could be a useful framework in this endeavor. Four suggestions are offered here for the anticipatory governance of AI. First, recognizing AI’s nature of General-Purpose Technology could help predict the future of AI. Second, issues of equity and equality of AI needs urgent attention. Third, sci-fi could be very helpful for developing scenarios, drawing public awareness, and encouraging discussions about AI. Fourth, design principles established in Human-Computer Interaction could be applied for helping formulate AI policies.[……]

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

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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

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

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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

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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?

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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?

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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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