BMAB

SCIENCE/ 科学

Driven by curiosity, human beings have embarked on a long journey in questing for the wonders of the universe. We use science as a systematic enterprise; we build and organize knowledge in the form of testable explanations and predictions about the universe. The fine structure of its constituents and their reactions are known as chemistry, while the DNA carriers and oxygen users are covered by biology; the laws of physics govern the dynamics of which, all these branches of knowledge unite together to decipher our beautifully mysterious universe for more than thirteen billion years.

In the last five centuries, in physical science starting from Galileo and Newton to Einstein and Higgs, almost all scales of the universe have been explored. Our knowledge of the universe divided into three parts, matter that we know 4%, dark matter about 25% and the rest is dark energy. In 17th century, Newton described the macroscopic world through classical mechanics to formulate gravity. The classical picture of mechanics vis-a-vis nature failed to explain the structure of matter and its dynamics at short distances. That led to the era of quantum physics in the beginning of 20th century. In the other hand, in 1915, Einstein formulated the theory of gravitation to equate the dynamics of the space time geometry to the energy of matter. The fact that quantum mechanics and general relativity have been found fundamentally incompatible stands as the greatest failure of twentieth century science, and provides the greatest challenge at the dawn of the twenty-first century.

All motivations of theories are based on the idea of finding one mathematical framework to derive all the laws of nature. Since 1970s, some theories such as string theory seek both quantized gravity and grand unified theory within one framework as a theory of everything. String theory in 26 dimensions mutated from an unsuccessful theory in hadrons physics to prospective unified theory of all interactions in ten dimensions. Reiner Hedrich said: “String theory is no theory at all, but rather a labyrinth structure of mathematical procedures and intuitions… It has no clear and unambiguous homological basis; no physically motivated fundamental principle is known. ” Leonard Susskind said: “… with absolutely no experimental basis, string theorists constructed a monumental mathematical edifice”. One of the ways out is to take a step backward and redefine the concept of time, space, matter, energy and vacuum, not from mathematics but from observations.

We have come to an encounter a very critical stage of the natural triangle humans-knowledge-nature. Facing the greatest “crisis” - the “stagnation” of science today is led by vectorisation of mathematical frame works, and romanticizing of pure theories. Mathematics as the “universal language” function as frame work for science, nonetheless it unavoidably suffers from its own fate of “epistemological obstacle”, epistemological leap is needed, “laws of physics” may not be so “lawful” and perhaps need to be re-written. It may be helpful to examine the scientific methods itself, and head back early approach of nature philosophy for the yet unknown, or perhaps even for the unknowables.


在好奇心的驱使下,人类踏上了探索宇宙奥妙的漫漫长路。我们用科学的方法论来建立和组织知识,用可验证的理论解释并推测宇宙世界。其构成成分之间所发生的反应及其精妙的结构属于化学的范畴;基因携带者与依靠氧气的生命体属于生物的范畴;事物的运动则遵循着物理规律。所有的知识分支汇聚到一起揭秘已存在了一百三十多亿年的璀璨神秘的宇宙。

近五百年来,从伽里略到牛顿,从爱因斯坦到希格斯,物理科学几乎探索到了宇宙的各个尺度。我们已知的宇宙由三部分组成:可测物质占4%,暗物质约为25%,其余为暗能量。牛顿于17世纪将引力公式化,用经典力学描述了宏观世界。但经典力学却无法解释微观尺度下物质的结构及运动问题。于是,量子力学领域的研究便于20世纪初拉开帷幕。与此同时,爱因斯坦于1915年提出了联系时空几何和物质能量的方程。量子力学与相对论无法兼容这一问题,既是二十世纪科学界最大的失败,也是本世纪科学界面临的最大挑战。

目前来看,似乎所有的理论都在尝试找一个能够推演一切自然法则的数学理论框架,自1970年代开始,某些物理理论如弦理论就尝试糅合重力的量子化和统一场论为一个统领一切的理论。26维的絃理论从强子物理中不是特别成功的理论中演变到未来所预期的包括所有(粒子)反应的10维的统一场论。莱纳·海德里希(Reiner Hedrich)曾说:“弦理论与其说是一种真正的理论,不如说是一座由数学过程与直觉构造出的迷宫……它既没有清晰明了的同源基础,也没有任何从物理学出发的根本法则被验证。”伦纳德·萨斯坎德(Leonard Susskind)也说过:“在没有任何实验论证的基础上,弦理论家们生生构建了一幢纪念碑般宏伟的数学华厦。”走出这个迷宫的方法之一,就是后退一步,非从数学框架角度,而用观察来重新定义时间、空间、物质、能量和真空的概念。

人类现已步入权衡人、知识与自然这三角关系的关键阶段。数学体系的向量化与对纯理论的浪漫主义情结,使科学陷入停滞不前的巨大危机。数学 - “宇宙通用语言”,作为科学研究的框架依托的同时,无法挣脱其“认知论障碍”的命运。因此,认知论层面上的超越成为必需:物理定律并不全为“定”论,可被推翻和重写。或许我们应当审视科学方法论本身,重回自然哲学之道,尝试揭秘尚未知的、甚至不可知的事物。

BIG DATA/ 大数据

The Chinese modern has always been distinctive from Western counterparts for the unique nature of the collective: today, technological formats such as internet search browsers, e-commerce platforms, and chat apps assume different roles than the same technologies assume in the West.

The depoliticized discourse of technology in California becomes much more ideologically charged in China, land of human flesh searches, taobao villages, and a vast, interlocking web of humans whose internal articulations and struggles to attain selfhood often are mediated by Wechat.

We explore the significance of Foucault’s notion of biopolitics and how it could help us to understand what China’s new technological mediatized society means, and how it fits into the history of Chinese political and artistic thought: China's online world is one of a population always outrunning whatever algorithms enclose them.

Questions about copyright law, data privacy, and online security are really political questions about the border between the public and the private, and the nature of ownership: the folk practices of China's internet show an ongoing resistance to the emergence of politically autistic digital landlords.

The Chinese internet is merely a representation of the China's urbanizing geography, featuring the same dialectic of a population encountering law in a specifically defined territory: but how can we use biopolitics to understand a population defined not in terms of shared life, but shared information?

Chinese “culture,” whatever that might mean, serves as an algorithm, a sorter of the data points that human beings have become as they travel across the national web of circulation which is the greatest of all Chinese technologies.

A phone with a handful of apps on it is all we need not only to negotiate and navigate the Chinese city but even to find our own place in it; not only to locate where we are on the map or where the nearest coffee shop is, but who the others are, what kind of relationships we have with them, how we can buy and sell.

China’s 1.5 billion population are the data, the contradictory history of New China the algorithm; when we crack the code, we’ll have reached a utopia of total circulation, where all data can move freely along the web, whether that’s the spatialized web of the city, the halfway abstracted one of the economy, or the pure flow of information itself. What would an autonomous mass look like?


现代中国与西方国家一直存在着差异,前者有着独一无二的集体主义特性。在今日中国,互联网搜索引擎、电商平台以及聊天应用等技术形式相较于它们在西方国家扮演着不同的角色。

美国加利福尼亚的技术去政治化论述在中国变得更具意识形态意味。这片土地上有着人肉搜索、淘宝以及由微信构建出的一个庞大的、相互关联的、自我实现的“人网”。

我们以福柯的生命政治学为理论视野来帮助大家理解新科技化的中国社会形态的意义,以及这种形态是如何与中国历史上长期以来的政治与艺术思想相适应的。中国的网络世界即是一个不断突破算法边界的社群。

版权法、数据隐私以及网络安全等一系列的政治问题,探讨着“公共”与“私有”的界限划分以及所有权的本质。中国互联网的普通网民正不断实践着对虚拟操控者反抗,而这些操控者本身在政治上是自闭的。

中国的互联网是中国城市地理的一种表现,它与在特定地区人们对规则的认识有着相同的逻辑。我们该如何用生命政治学的理论去解释这样一个不由“共享化生活”来定义而是由“共享性信息”来定义的人文国度?

无论中国“文化”的意义为何,它已经成为一种运算法则,不断处理着人们在互联网上活动的数据,而互联网是中国最强大的技术。

想在中国的城市里畅行无阻,你只需要一个装配好不同应用程序的手机,用它不仅能谈生意、导航,甚至还能为自己安个家。人们能在地图应用中为自己定位、找到附近的咖啡厅,还能了解其他人、理解我们与他人的关系,甚至轻松地完成一笔交易。

中国的十五亿人口正是数据,而充满矛盾的新中国历史正是这个“算法”。当我们破解了密码,便可以到达一个完整循环的乌托邦。届时所有的数据都可以在网络上自由运行,这个“网络”可以是城市里空间化的网络,可以是经济领域中半抽象化的网络,也可以是单纯意义上的信息流动网络。试想一下,一个完全自治化的巨大数据库最终将呈现出怎样一番景象?试想一下,一个完全自治化的巨大数据库最终将呈现出怎样一番景象?

ARTIFICIAL INTELLIGENCE/ 人工智能

An Open Letter

RESEARCH PRIORITIES FOR ROBUST AND BENEFICIAL ARTIFICIAL INTELLIGENCE

Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents systems that perceive and act in some environment.

In this context, “intelligence” is related to statistical and economic notions of rationality colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic and decision-theoretic representations and statistical learning methods has led to a large degree of integration and cross-fertilization among AI, machine learning, statistics, control theory, neuroscience, and other fields.

The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable successes in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems.

As capabilities in these areas and others cross the threshold from laboratory research to economically valuable technologies, a virtuous cycle takes hold whereby even small improvements in performance are worth large sums of money, prompting greater investments in research.

There is now a broad consensus that AI research is progressing steadily, and that its impact on society is likely to increase. The potential benefits are huge, since everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable.

Because of the great potential of AI, it is important to research how to reap its benefits while avoiding potential pitfalls.The progress in AI research makes it timely to focus research not only on making AI more capable, but also on maximizing the societal benefit of AI.

Such considerations motivated the AAAI 2008-09 Presidential Panel on Long-Term AI Futures and other projects on AI impacts, and constitute a significant expansion of the field of AI itself, which up to now has focused largely on techniques that are neutral with respect to purpose.

We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial: our AI systems must do what we want them to do.

The attached research priorities document gives many examples of such research directions that can help maximize the societal benefit of AI. This research is by necessity interdisciplinary, because it involves both society and AI. It ranges from economics, law and philosophy to computer security, formal methods and, of course, various branches of AI itself.

In summary, we believe that research on how to make AI systems robust and beneficial is both important and timely, and that there are concrete research directions that can be pursued today.


关于提升人工智能技术的性能和社会效益的研究重点说明

人工智能(AI)的研究工作自概念时期已经探索过不同的问题及其解决办法,但是在过去二十年左右,研究的问题主要还是围绕在“智能代理”的构建上,也就是在特定环境下进行观察并采取行动的系统。

在这种语境下,“智能”和理性意识上的统计学和经济学息息相关。通俗来讲,就是指一种能做出正确决定、计划和推断的能力。对概率和决定的应用,即理论表现与统计数据的学习方法,在很大程度上让人工智能发展到一种复合和跨根源的现状:与机器学习、数据统计、控制理论、神经科学以及其他不同领域相互影响和推动。

共享理论框架的建立,外加可用的数据和数据处理功能,让人工智能在不同的方向上取得了可观的成就:语言识别、图像分类、无人驾驶汽车、机器翻译、有腿移动以及智能问答系统等等。

当这些领域的能力从实验室的研究项目变为有实际经济价值的技术,一个循环随即出现,尽管是一个很小的技术提升,也需要巨大的资金支持,继而引发大量的研究经费投入。

目前社会上的广泛共识认为人工智能的研究进展平稳,人工智能对社会的影响很可能会提升。人工智能的潜在效益十分巨大,因为一切人类文明的成果都是人类智慧的功劳,我们尚无法预知在人工智能工具提升后,人工智能的加强会带给我什么成功,但至少对消除疾病和贫穷的使命上会有可观的影响。

正因为人工智能有巨大的潜力,所以研究工作的重点在于该如何尽可能的收获这门技术的效益而同时规避它的弊端。人工智能的研究工作十分紧迫,我们不仅仅要关注在如何让人工智能技术越来越强大,而且要关注如何最大化人工智能的社会效益。

这些思考促使了AAAI 2008-09 Presidential Panel on Long-Term AI Future (人工智能技术未来长期发展主席论坛)的产生,以及其他探讨人工智能社会影响的项目,也大大拓展了人工智能自身的领域范围。到目前为止,这一领域范围大部分集中在社会尊重与实际目的中保持中立态度的技术上。

我们提议拓展的研究工作要确保放在如何让不断提升的人工智能技术不仅是强大的,也是有社会效益的:人工智能技术一定要应用到我们希望它应用的地方。

研究重点文献包含很多能够帮助我们最大化人工智能技术的社会效益的研究方向。不可避免,该研究是跨学科领域的,因为不进涉及了人工智能技术,也涉及了社会本身。其中包括了经济学、法学、哲学以及计算机安全、形式化方法,当然,还有人工智能本身的不同分支领域。

总体来看,如何让人工智能技术变的强大同时有社会效益,这个研究不仅十分重要,也是迫在眉睫的,同时,我们现在的确有实际具体的研究方向,允许我们在今天就可以开始行动了。


MIXED REALITY/ 混合现实

Unlike VR and AR, the concept of MR (Mixed Reality) is more perplexing, because it’s not “reality” that is being mixed, but how the V (virtual) and the A (augmented) can be mixed is untold. What I proposed is a more inclusive concept, namely, expanded reality (ER), that refers to a self-contained virtual world as a result of a merge between networked VR and IoT (Internet of Things). In this world, humans or post-humans are immersed in an artificial environment and control the manufacturing facilities through teleoperation while they remain immersed. Such a scenario is comparable to the movie scene as presented in The Matrix. In fact, I already built a Human-Machine Interfacing Lab wherein a mini ER model is equipped. In what I call a Teleportation experience in the lab, the transition lines between the virtual and the real are already erased on the experiential level. In a way, all my effort in designing and constructing such a lab points to the concern of how to prevent this new type of technology from being controlled and manipulated by a handful of people as an efficient tool for impeding human freedom and dignity. There are two important factors involved in this concern. First, it is about how to come up with more precise and acute analysis of the structural changes in our socio-political life due to the science and technology advancement, and draw on technology itself to prevent non-transparent technological manipulation. The development of technology should always be carried out in an open social space, such that technological power would not be monopolised by a small number of political or commercial manipulators. Secondly, it is about how to imbue technological achievements with humanistic rationality.  Philosophers, artists and social scientists should be actively involved throughout technological innovation. Based on their attentive observation of the process, they should voice their most pressing concerns about the moral, aesthetically and social issues to those who work in areas of science, technology, industry and, especially, in political affairs. We should establish a humanistic ethical firewall against technological abuses.

Prof. Philip Zhai

Head of Human machine interconnection lab


混合现实(MR)比起虚拟现实(VR)和增强现实(AR)来说其不同之处是更加复杂。原因是并非“现实”被混合,而是虚拟现实(VR)和增强现实(AR)的融合。在这里我提出一个更加有包容度的概念:拓展现实(ER),即一个融合了互联网虚拟现实和物联网的结果,一个自给自足的虚拟世界。这个世界的人类或后人类沉浸在虚拟的环境里并通过遥控操作掌控生产设施,我们也曾经在《骇客帝国》中见证过类似的场景。事实上我已经建构了一个带有基本拓展现实(ER)模型的人机交互实验室。我称之为实验室中的隐形传输体验,虚拟与现实之间转换的界限已经在体验层面上被抹除了。在某种方式上来说,我不计时日的花费精力建立这样一个实验室,主要原因是因为我深深的担心:这种科技如果被掌握在少数人手中,有一天他会被成为威胁人类自由和尊严的有效工具。两点有关于这个忧虑。其一:受到科技发展的影响,我们如何能得到一个当今社会政治中结构变化的准确而深刻的分析,并利用科技本身来防止不透明的技术操纵。科技发展应该在社会空间里公开进行。这样的技术力量不会被少数政治或商业操作所垄断。其二关于如何对人们通过人文理性灌输技术成果。哲学家,艺术家和社会科学家应该积极参与到整个科技创新过程中去。通过他们对过程的细心观察,并对伦理、美学和社会问题,向科学技术领域、产业,尤其是政治事务表达他们最迫切的忧虑。我们应该构建一个防止技术滥用的人类伦理防火墙。

翟振明教授

中山大学人机互联实验室主任

BIO-GENETICS/ 生物基因

When biology first became a study, it was still in a convoluted state, at a cross-section between theology and natural history. In the 20th century, it entered its golden age. During the establishment of modern biology as a science, two significant factors played significant roles: one was the ideological transformation from holism to reductionism, and the other was “experiment” becoming the standard procedure in practice. From this point on, cell biology, biochemistry, genetics, and embryology all began developing rapidly, facilitating each other. In 1953, DNA’s double helix structure was discovered. Scientists then tackled a series of problems related to “central dogma”, making the “DNA-RNA-Protein” process a classic that was added to textbooks. Thenceforth, the paradigm shift of biological sciences was complete. The era of molecular biological officially started.

After the new paradigm shift was complete, scientists generally stopped questioning existing theoretical models. Some experts changed their direction from theoretical to applied sciences, applying theoretical research to technical applications, which led to the growth of subclassifications such as genetic engineering and cell engineering. After technologies including PCR and GFP solved technological bottlenecks one after another, genetic engineering experienced a period of explosive growth.

Around the turn of the millennium, due to several phenomenal events, discussion of gene technology broke away from the scientific realm, entered into popular view, and even grabbed the world’s attention. The birth of Dolly the sheep in 1997 amazed the world, but also prompted people to ponder how technology affect living organisms. Another groundbreaking project, the Human Genome Project that began in 1990 and completed in 2003 was dedicated to identifying and mapping all the DNA on 23 pairs of chromosomes, so that men could know their own selves on a physical level. Although it laid the foundation for many fields including gene therapy, it also made the public wary of genetic privacy. The gene editing technology, CRISPR/Cas for instance, is such a double sword. On the one hand, it could improve precision in clinical medicine and promote human well-being; on the other hand, it allows men to customize the specific makeups of their own bodies as well as their descendants, closing in on playing God.

With the extraordinary advancement of biotechnology (especially genetic engineering), the importance of bioethics as a offset becomes paramount. On a molecular level, people are mainly concerned with the following aspects of bioethics: 1. health and wellness, and the prediction, diagnosis and treatment of diseases; 2. genetic privacy; 3. application of genetic modification. However, many problems do not arise from technology, but are interwoven with complex social factors such as politics and religion.Thus, for us who live in the “post-genome era”, we shouldn’t try to stop but instead guide the overwhelming advancement of technology. This is not an issue that the biology field and technology field need to face, but a task that all humanity needs to solve together.


生物学在形成之初,尚处于和神学、博物学等互相交织的混沌状态,直到20世纪才进入其黄金发展阶段。现代生物学在建立过程中,有两大因素极为重要,一是在思想方式上从整体论到还原论的转变;另一是在实践方式上将“实验”作为标准手段。之后细胞学、生物化学、遗传学、胚胎学各自进入飞速发展时期并相互推动,最终于1953年发现了DNA的双螺旋结构。科学家们继而爆发式地解决了一系列“中心法则”问题,使得“DNA-RNA-蛋白质”模式成为经典并逐渐进入教科书。自此生物科学的范式转换完成,正式进入分子生物学时代。

当新的范式转换完成后,科学界通常不再质疑已有的理论模式,一部分专业人士由理论科学转向应用科学,也就是将理论研究层面推进到技术应用层面,产生了诸如基因工程、细胞工程等一些更为细化的领域。随着聚合酶链式反应(PCR)和绿色荧光蛋白(GFP)等技术一一解决了各个时期的技术瓶颈后,基因工程处于阶段性迅猛发展。

千禧年前后出现了几个现象级事件使得对基因技术的讨论突破了科学范畴,进入到大众舆论,甚至成为全球关注焦点。1997年多莉羊的诞生,让人们既为克隆技术惊叹不已也开始思考技术对于生命体的影响力。另一跨时代的项目——始于1990年完成于2003年的人类基因组计划(HGP)则致力于全面定位人类23对染色体上的全部基因,让人们了解物质层面的自我本体。它虽然奠定了基因治疗等一系列领域的基础,却也开始使大众忧虑基因隐私问题;近期备受瞩目的基因编辑技术,即CRISPR/Cas系统也是一把双刃剑。它一方面能大力促进精确医疗,增进人类福利,另一方面也让人类越来越接近上帝的角色,能够预制自身和后代的构成细节。

面对突飞猛进的生物技术(尤其是基因工程),生物伦理作为其制衡方变得非常重要。在分子层面的生物伦理中,人们比较关心的领域包括:1、个人健康和疾病的预测、诊断和治疗;2、个人基因隐私;3、基因改良生物(转基因生物只是其中一类)的应用等,但很多问题绝非是技术本身的问题,而是和复杂的政治、宗教等社会原因相互交织。因此,处于“后基因组时代”的我们,对于汹涌而至的技术洪流不应采取“堵截”而是“疏导”。这不仅是生物学科或者科技界需要直面的问题,更是全人类需要共同面对和解决的课题。