“人工智能换人”技术取代叙事的历史唯物主义审视

在人工智能与人类智能双向赋能中,人工智能表现出极其强大的能力,不仅使人类既有使能技术智能化,而且提出了人工智能取代人的存在论问题。从人机对立或技术悲观主义者的立场来看,人工智能取代人意味着人工智能时代是一个新异化的时代,是一个物体系绝对胜利的时代,也是一个人类智能或将退位的时代。但是从历史唯物主义观点来看,人工智能是人基于对智能的理解、对物质的调动、对规律的认知和对系统的设计所创造出来的物体系,其延续了自动化时代取代技术对人活动领域性排除,也展开了人类技术发展史亘古常新的存在论焦虑。因此,面对人工智能时代全新的技术取代叙事,只有深入其缘起,才能正视存在论排除的焦虑;只有把握技术运行的社会原则,才能避免技术取代的泛滥;只有探索人机共存的存在逻辑,才有可能真正认知智能的本质并获得自由的可能。     

智能在场与主体之困：人工智能时代人的主体性危机与破局

人工智能已然成为21世纪最具创新性和爆发力的技术手段。它对人类社会造成的强烈冲击,非简化问题本质的“价值中立说”所能够涵摄和覆盖。人工智能营造的便捷生活表象遮蔽了人作为主体被技术裹挟的事实和难以“逃逸”的困境。“存在的非存在”是人工智能时代人类主体性存在的二元悖反,作为行动元的人类现实地存在于人工智能“座架”的经验世界,但却成为“不被需要”的“非存在者”。人工智能的历史性在场与技术化运作愈益显示出超越人类智能的力量,不断僭越人的主体地位代替人选择、判断、思考和行动,人工智能的高度自主性使人的自主性被遮蔽,其对生产生活的全面操控阻碍了人的创造性和能动性的发挥,加剧了人被智能技术宰制而失去自由和反思批判精神的主体性危机。数智化背景下,应通过批判审思人工智能技术范式,适时采取自觉的“中辍”行为,以人之理性矫正技术的任性,引导智能技术为人的自由解放与全面发展服务,清除智能拜物教意识形态迷思,营造人机和谐共生、良性互动的生态系统,从而推动加快智能社会建设步伐。     

人工智能时代的政务智慧转型

当前人工智能技术的不断发展和广泛应用使得人类逐渐进入到人工智能时代.人工智能技术对以自然人为主体构成的整个人类社会产生了深远的影响.对行政体系而言,包括对传统政府的主体、行为模式、组织运作等都产生了深刻的影响.从知识管理的角度出发,政府可视为一种公共管理的智慧集合,在人工智能不断渗入的情况下,传统政府正在从单一的自然人的政务智慧集合逐渐演化为人机高度融合的泛政务智慧体系.人工智能是人类文明的一次巨大飞跃,最终会形成人与人工智能密切融合的新的社会文明形态,而传统的行政体制也将形成新的人机高度融合的新形态.     

人工智能大猜想

正什么是人工智能?尽管随着人机大战,人工智能已经成为了一个耳熟能详的热词,但究竟什么是人工智能,却在行业内都难以有一个确定的定义。其实简单地说人工智能就是对人的意识、思维过程的模拟,但之所以人工智能的定义难以确认,关键在于对"智能"的定义难以确认,在人工智能领域经常有一句话说:我们连人的智能是什么都不知道,何谈人工智能?因此目前大家普遍认可的还是由约翰·麦卡锡(John Mccarthy)在1956年的达特矛斯会议     

人工智能悲观主义批判

随着新一代人工智能的兴起,各种悲观主义观点也应运而生。人工智能虽然可能给人类带来各种新问题,但悲观主义是缺乏根据的。从技术历史维度看,每一次新技术的出现都会有人陷入悲观主义窠臼,人工智能悲观主义只是技术悲观主义的翻版;从技术本质维度看,人工智能取代人类劳动只是人类解放的继续;从技术发展维度看,人工智能被许多人高估;从人机关系维度看,人工智能与人类并不存在本质冲突,而且完全可能相互依存、和谐共生。因此,我们应该乐观面对新一代人工智能,不必过分悲观失望。     

人工智能不能代替人的思维

关于智能机器能否代替人的思维或者超过人类思维的问题是自然科学界和哲学界自七十年代末学术开禁以来的热门话题之一。我的看法是:智能机器或人工智能的出现,是人类改造自然活动的深入,但它只能模拟而不能代替人脑的全部功能,也绝对不会在整体上超过人,只能作为人     

主奴辩证法与相互承认:试论人工智能战胜人类的可能性

人工智能战胜人类的可能性,会成为未来社会科学讨论的关键问题。奇点是西方学者用以描述人工智能超越人类的临界点。目前,人工智能的发展非常有可能超出人类控制的范围,而自学习就是人工智能最令人类生畏的地方。遗传算法可以帮助人类获得问题的最优解,但人类并不知道这一算法的运行逻辑及其背后的实现路径。自我意识可能会成为人类智能的最终屏障,然而,情感计算在帮助机器理解人类意图的同时,也会增加机器发现其主体间性的可能。在未来,机器与人的关系很有可能会上演又一次主奴辩证法的循环。尽管人类的初衷是功利性地使用机器,但人类对机器的依赖最终很有可能达成与机器相互承认。换言之,人工智能很有可能在与人类的斗争中,取得自己的主体地位,并实现黑格尔意义上的相互承认。     

人工智能对人类劳动的挑战及其应对

随着新一代人工智能的兴起,机器智能越来越接近人类智能,过去专属于人类的劳动,特别是脑力劳动,越来越被智能机器所取代,因此,人工智能给人类劳动带来了巨大的挑战。但是,对人类来说这种挑战本身也是一种机遇,它让人类从繁重的体力和脑力劳动中解放出来,人类由此获得了全面的解放和自由,并有闲暇去享受生活和全面发展。当然,要实现这些目标,我们必须改变传统观念、提升自身能力,并改变财富分配方式,提高社会福利,以便逐渐向闲暇时代过渡。     

新技术革命推动下的应急管理——访中国科学院大学应急管理研究中心执行主任董传仪

2019年5月,有两件大事引起世人关注。一件发生在16日,国家主席习近平致信第三届世界智能大会,强调"当前,由人工智能引领的新一轮科技革命和产业变革方兴未艾。在移动互联网、大数据、超级计算、传感网、脑科学等新理论新技术驱动下,人工智能呈现深度学习、跨界融合、人机协同、群智开放、自主操控等新特征,正在对经济发展、社会进步、全球治理等方面产生重大而深远的影响。     

如何看待人工智能对人的自由全面发展的作用——从《资本论》视域中的“自由人联合体”谈起

马克思在《资本论》中系统地阐述机器与大工业的关系,从机器取代劳动者——提高劳动生产率——缩减必要劳动时间的发展路线,阐明人类进入"自由人联合体"社会的现实可能性,为我们理解人工智能与人的自由全面发展内在关系提供一种新的理论研究路径。基于人类劳动的解放,人工智能促进人机融合,变革社会生产模式,使人的劳动回归到"自由自觉"的活动,最大限度地增加可自由支配的时间,并且人工智能为人类走向"自由人联合体"社会提供物质保障,为加速资本主义制度的消亡奠定基础。     

Book reviews

Oscar Wilde captures the deep challenges relating to intelligence when he states that, ‘it is the spectator, and not life, that art really mirrors’. This statement elucidates the negative force of cognitive closure on intelligence, as well as bringing attention to the importance of an understanding of the human factor in intelligence production, and its relationship to discourse failure. Intelligence literature after 9/11 has focused on the causes and nature of intelligence failure, though few inquests have conceived intelligence as a deeply cognitive, and therefore mental and moral landscape that needs to be explored in all its complexity. Intelligence operators, like art spectators, perceive reality filtered through all sorts of implicit and explicit ideological prisms, and these ideologies, whether they are political assumptions or social orthodoxies, manifest themselves as cognitive closure, and shape the discourse in intelligence organizations, as well as between these organizations and society at large. This paper consequently argues that discourse failure is increased because of a flaw in the epistemic process among intelligence operators and consumers.     

Competitive intelligence and national intelligence estimates

National Intelligence Estimates are consensus-driven intelligence products. Yet there is considerable evidence supporting the use of competitive intelligence at every level of activity, including the presentation of finished products to consumers. We examine NIEs from two important periods in US foreign policy: the buildup in Vietnam and Gorbachev's reforms. We find in both cases alternate viewpoints were not presented in the US IC's premier intelligence product when such views could have made a difference. Consistent with contemporary findings in cognitive psychology, we argue the manner in which NIEs are structured and presented should be reformed to offer better decision support.     

Regulating human control over autonomous systems

In recent years, many sectors have experienced significant progress in automation, associated with the growing advances in artificial intelligence and machine learning. There are already automated robotic weapons, which are able to evaluate and engage with targets on their own, and there are already autonomous vehicles that do not need a human driver. It is argued that the use of increasingly autonomous systems (AS) should be guided by the policy of human control, according to which humans should execute a certain significant level of judgment over AS. While in the military sector there is a fear that AS could mean that humans lose control over life and death decisions, in the transportation domain, on the contrary, there is a strongly held view that autonomy could bring significant operational benefits by removing the need for a human driver. This article explores the notion of human control in the United States in the two domains of defense and transportation. The operationalization of emerging policies of human control results in the typology of direct and indirect human controls exercised over the use of AS. The typology helps to steer the debate away from the linguistic complexities of the term “autonomy.” It identifies instead where human factors are undergoing important changes and ultimately informs about more detailed rules and standards formulation, which differ across domains, applications, and sectors.     

二元论的逻辑错误

从使用人工语言表示一个一元论或二元论观点入手,首先,在一阶逻辑上定义"归元谓词",并使用集合的观点改写其表达式;其次,运用"归元谓词"定义一元论和二元论,并指出二元论的逻辑错误;然后将以上观点运用于对一个实例的分析,即对试图使用哥德尔定理反驳强人工智能观点的工作加以反驳;最后得出结论:讨论"世界本原"问题是无意义的,一个一元论仅仅是在承认空集存在的意义上被我们接受。     

Augmenting human cognition to enhance strategic,operational, and tactical intelligence

The unprecedented increase in the volume and velocity of data collected by open source and classified platforms is simultaneously disrupting and transforming the intelligence enterprise. This article posits a technology-based approach for augmenting human cognition by leveraging high-performance computing and artificial intelligence applications to enhance the intelligence enterprise’s capability to identify, synthesize, and act on the key intelligence-relevant information elements embedded in those data. Adapting AI to the intelligence enterprise and national security decisions more broadly thus facilitates rapidly bringing to bear the essential human element of interpreting context and intent amid an otherwise insurmountable cascade of data.     

Indian spies inside Pakistan: South Asian human intelligence across borders

This article examines India’s historical efforts to spy inside Pakistan from the mid-1960s to the early 1970s. It draws from memoirs of notable Indian spies who were jailed for espionage in Pakistan and spy ‘fiction’ written by former Indian intelligence and military officers who allege their writing is based on actual cases. The article highlights commonalities among Indian spies using the words of Indian officers to better understand human intelligence efforts inside Pakistan. It finds that Indian spies in these books have initially been Hindus or from multi-religious families, from the Indian-Pakistan border and have been poorly treated by the Indian government and its intelligence services.     

Rethinking the training of intelligence analysts

Abstract

Despite intense scrutiny and promised fixes resulting from intelligence ‘transformation’ efforts, erroneous analytic assessments persist and continue to dominate news coverage of the US intelligence community. Existing analytic training teaches analysts about common cognitive biases and then aims to correct them with structured analytic techniques. On its face, this approach is eminently reasonable; on close inspection, incomplete and imbalanced. Current training is anchored in a mid-twentieth century understanding of psychology that focuses on checking over-confidence and rigidity but ignores the problems of under-confidence and excessive volatility. Moreover it has never been validated against objective benchmarks of good judgment. We propose a new approach: (a) adopting scientifically validated content and regularly testing training to avoid institutionalizing new dogmas; (b) incentivizing analysts to view training guidelines as means to the end of improved accuracy, not an end in itself.     

Artificial Morality. Concepts,Issues and Challenges

Artificial morality is an emerging field in artificial intelligence which explores whether and how artificial systems can be furnished with moral capacities. Since this will have a deep impact on our lives it is important to discuss the possibility of artificial morality and its implications for individuals and society. Starting with some examples of artificial morality, the article turns to conceptual issues that are important for delineating the possibility and scope of artificial morality, in particular, what an artificial moral agent is; how morality should be understood in the context of artificial morality; and how human and artificial morality compare. Outlined next is how moral capacities can be implemented in artificial systems in general and in more detail with respect to an elder care system. On the basis of these findings some of the arguments that can be found in public discourse about artificial morality will be reviewed and the prospects and challenges of artificial morality are discussed.     

Artificial Intelligence,Neom and Saudi Arabia's Economic Diversification from Oil and Gas

Saudi Arabia is diversifying its economy by becoming a global technological hub. Driven by its ‘Vision 2030' initiative, it has embarked on the most ambitious and far-reaching transformation plan in the Kingdom's history. At the core of this transformation are the investment and development of artificial intelligence (AI) and its integration into a new mega-city, Neom. Currently under construction, Neom is seeking to integrate robotics and AI seamlessly into every aspect of citizens' lives in a bid to generate revenues from key economic sectors for the future. This transition from an economy based on hydrocarbons to AI is, however, more than economic. It is a bid to secure the survival of the House of Saud and meet the growing challenges of constructing a state around oil. Nevertheless, what happens in Neom may provide insights into how AI will impact the world beyond a cross-roads built on sand.     

智慧司法中的忧虑:想象、剖析与展望

智慧司法建设如火如荼的同时,学术界对智慧司法可能带来的负面效应过分忧虑:担忧对诉讼参与人贴标签会出现主观偏见、担心裁判算法黑箱可能会产生歧视、忧心人工智能代替法官思考甚至取代法官。上述忧虑乃是基于对智慧司法的想象。事实上,贴标签并不会产生偏见;智慧司法确实充满了黑箱,但并不构成逻辑困扰;智慧司法并没有增加裁判过程中的歧视,而是限制了本就存在的歧视行为;算法没有能力代替法官思考,更不可能取代法官。未来在讨论智慧司法建设时应当破除对新鲜事物的恐惧,摘除针对算法的有色眼镜,关注算法对司法带来的各种冲击。