Editorial | 《人工智能与创新》发刊词 Introducing AI & Innovation

2026-04-28 11:16:01, 人工智能与创新 Know it All光谱数据库



作者

【意大利】法觅舸(Mirko Farina),【中国】纪荣嵘,【中国】陈劲,【中国】余霄,【荷兰】文森特·布洛克(Vincent Blok),【意大利】保罗·钱卡利尼(Paolo Ciancarini),【南非】恩卡伟尼·布萨尼(Ngcaweni Busani),【加拿大】维托尔德·佩德里兹(Witold Pedrycz)


首次发表日期:2025年10月13日

First published: 13 October 2025



1

人工智能与技术创新:创办新期刊的动力

AI and Technological Innovation: 

Motivations for Our New Journal

近年来,人工智能(Artificial Intelligence,简称AI)已深刻地改变了众多行业的面貌,重塑了社会结构,并促使个人与企业重新定义其运作方式。简而言之,人工智能已在多个领域为我们的生活带来了革命性的变化[1]

In recent years, Artificial Intelligence (AI) has changed the face of many sectors, altered the fabric of our society and contributed to redefine how both individuals and businesses operate. AI, in brief, has revolutionized our lives in several domains [1].


人工智能对科学发现的推动作用尤为显著。当前,全球研究人员已广泛采用人工智能技术,正以过去难以想象的方式获取新见解、提出假设、设计实验、收集和解读数据[2-4]。这一现象在众多学科领域均得到了充分验证,包括气候科学[5]、生物学[6, 7]、数学[8, 9]、物理学[10, 11]、数据科学[12, 13]、化学[14, 15],以及医学[16]

AI''s impact on scientific discovery has been quite remarkable. Researchers around the world nowadays regularly use AI to discover new insights, generate hypotheses, design experiments, collect and interpret data in ways that were previously thought to be impossible [2-4]. This is true in many fields. For example, in climate science[5], in biology [6, 7], in mathematics [8, 9], in physics [10, 11], in data science[12, 13], in chemistry [14,15], and even in medicine [16].


与此同时,人工智能已成为工业和经济发展的强劲驱动力,尤其在智能自动化领域表现尤为突出。制造业[17]便是其中的典型代表,人工智能技术被广泛应用于预防设备故障和优化生产线。在这一领域,人工智能还助力于工业机器人的开发,使其能够在高度受控的人类环境中执行以往通常极为复杂的任务[18]。金融领域也是人工智能取得显著进展的重要领域[19],其在交易、欺诈检测以及个性化理财建议等方面均展现出强大的应用潜力。此外,农业正充分利用人工智能的变革性力量[20,21],相关技术的应用有效优化了作物产量、监测作物健康状况以及精准检测病虫害。

Yet, AI has also become a driving force for industrial and economic development, especially in the context of intelligent automation. This is particularly true, for example, in manufacturing [17] where AI is used to prevent equipment failures and optimize production lines. In this sphere, AI is also used for the development of industrial robots that can carry out usually complicated tasks in highly controlled human environments [18]. Finance is another area in which AI is making mighty inroads [19]. In finance AI is used for trading, in fraud detection, as well as for personalized financial advice. Agriculture is also taking full advantage of AI''s transformative powers [20, 21]. The application of AI technologies in agriculture can optimize crop yields, monitor crop health, or detect pests.


更广泛地来看,过去十年见证了数字技术的迅猛发展,其影响之深远,以至于被许多人誉为“颠覆十年”。如今,许多我们习以为常的事物,如5G、语音识别、云计算、物联网、电动汽车、自动驾驶汽车、无人机、3D打印、区块链等,在十年前几乎都尚未出现。而这些技术正是在人工智能的基础上得以积极构建和迅速发展[22]。因此,可以毫不夸张地断言,人工智能正在积极且决定性地推动这场新的数字革命[23-29]

More generally, one can say that the last decade has seen an incredible growth in the development of digital technologies to the extent that many have described it as “The Decade of Disruption.” Much of what is nowadays normal (including 5G, voice recognition, cloud computing, Internet of Things, electric vehicles, self-driving cards, drones, 3D printing, blockchain, just to mention a few), barely existed 10 years ago and is being actively built on the basis of AI technologies [22]. So, it is not an exaggeration to assert that AI is actively and decisively driving the new digital revolution [23-29].


然而,人工智能的影响可能更为深远——它有望成为一种全新的通用“发明方法”,从而重塑创新过程的本质及研发的组织模式。换言之,人工智能能够成为人类能力的增强器,使人们能够彼此(甚至远程虚拟地)或与人工智能驱动的系统进行协作,从而提升创造力、生产力和效率,以及优化决策过程[30]

However, AI may have an even larger impact by serving as a new general-purpose “method of invention” that can reshape the nature of the innovation process and the organization of research and development.1 In other words, AI can act as a booster of human capacities allowing people to collaborate [even virtually, at distance] among themselves or with AI-powered systems to boost creativity, productivity, efficiency, as well as decision-making processes [30].


然而,在这些巨大的潜在效益之外,我们也面临着某些挑战和重要的伦理考量,如人工智能可能产生的偏见与歧视,以及隐私和可解释性问题,这些问题对我们的信任构成了挑战。尽管如此,人工智能在决策中的应用正变得日益普遍,这一点显而易见。事实上,人工智能正在改变企业和政府解决问题、收集和处理数据的方式,甚至影响着其在商业战略和公共政策制定中的推理和执行方案。因此,将设计实践与人工智能的伦理、法律及社会影响(ELSA)考量相结合至关重要。例如,我们需要思考:以人类为中心的人工智能是否足以实现社会目标?抑或应该将其拓展至那些可能加剧——但也可能通过以生物为中心的人工智能来解决的挑战 [31]

Yet, next to these potentially enormous benefits, also come certain challenges and important ethical considerations (related to AI''s potential for bias and discrimination, as well as issues concerning privacy and explainability) that put at risk our trust in this technology. Despite these challenges, though, it is clear that AI''s applications in decision-making are becoming increasingly more frequent. AI is, de facto, changing how companies and governments address problems, gather and process data, and even reason and execute solutions in their business strategies and general public policies. Therefore, it is important to connect design practices with the consideration of ethical, legal and social aspects (ELSA) of AI, and for instance, to consider whether human centered AI is sufficient to serve societal goals or should be extended to challenges that could increase but also could be addressed by bio-centered AI [31].


未来的创新本质上依赖于人类与人工智能技术之间的深度协作。这种生物与技术的融合伙伴关系,若能得以恰当实施,将显著提升人类能力,并催生出人类或人工智能任何一方都无法单独实现的联合成果。

Future innovations will quintessentially depend on advanced collaboration between humans and AI technologies. These bio-synthetic partnerships, if properly implemented, shall augment human capabilities and lead to joint outcomes that could not be reached separately, independently by either humans or AI technologies on their own.


在此背景下,负责任的发展显得尤为关键。我们应当积极推行伦理规范,完善治理机制,并针对这些技术的可能性与前景展开审慎的技术性反思,以此引导和塑造正在兴起的人工智能革命,确保我们共同走向一个包容、可持续且契合人类价值观的未来。

In this context, responsible development is therefore crucial. Ethical standards, as well as proper governance and careful technical reflections on the possibilities and prospects of these technologies should be actively pursued and implemented to guide, shape, and mold the ongoing AI revolution and ensure a future for all of us that is inclusive, sustainable, and aligned with human values.


我们也必须清醒地认识到,通往负责任人工智能未来的道路并非一帆风顺。当前,关于人工智能治理的全球对话——涵盖其议程设置、伦理框架乃至核心优先事项——仍主要由少数强势声音所主导。占全球人口大多数、蕴含着蓬勃创新活力的全球南方国家,却往往被迫沦为旁观者或被讨论的对象,而非作为共同塑造数字命运的积极参与者。

Yet, we must also soberly recognize that this path to a responsible AI future is not preordained. At present, the global discourse on AI governance—its agendas, its ethical frameworks, and indeed its very priorities—is still predominantly shaped by a handful of dominant voices. The Global South, home to the majority of the world''s population and a vibrant wellspring of talent, has too often been relegated to the role of a spectator or a subject of discussion, rather than an architect of our shared digital destiny.


这种失衡必须得到纠正,这恰恰是本刊创办的核心使命之一。我们致力于打造一个战略平台,旨在放大那些代表性不足的声音,连接碎片化的智慧与认识论体系,挑战那些被视为常态的权力结构和本体论。我们坚信,一个真正公平且具有韧性的全球人工智能生态系统,必须建立在对多元发展路径和文明智慧的深刻尊重以及平等对话的基础之上。

This imbalance must be corrected. This is one of the core mandates animating the launch of this journal. We are committed to serving as a strategic platform to amplify underrepresented voices, to connect fragmented wisdom and epistemologies, and to challenge unspoken power structures and ontologies. We believe that a truly equitable and resilient global AI ecosystem must be built upon a profound respect for, and an equal dialog among, diverse developmental pathways and civilizational insights.



2

宗旨,使命与目标

Aims, Mission, and Objectives

《人工智能与创新》(以下简称AI²)是一本国际性的、经过同行评审的多学科期刊。该期刊由金砖国家新工业革命伙伴关系框架下的金砖创新基地数字经济研究中心(IDEAS)主办,并与清华大学技术创新研究中心及厦门大学人工智能学院达成战略合作,联合推出。

AI & Innovation (henceforth AI²) is an international, peer-reviewed, multi-disciplinary journal sponsored by the Institute for Digital Economy and Artificial Systems [IDEAS] under BRICS Partnership for New Industrial Revolution and developed in strategic partnership with both the Research Centre for Technological Innovation at Tsinghua University and with the Institute of Artificial Intelligence of Xiamen University.


本刊独立运营,专注于从宏观且跨学科的视角,深度剖析即将到来的人工智能革命所引发的深远社会技术影响及其伦理衍生效应——尤其在创新、技术进步以及全球性挑战治理等领域。

The journal, which nevertheless runs independently from those institutions, is devoted to exploring, from a holistic and interdisciplinary perspective, the profound socio-technical implications, as well as the ethical ramifications, of the forthcoming AI revolution; especially in relation to innovation, technological development, and governance of global challenges.


AI²致力于提供权威的学术成果,助力决策者积极应对并成功引领这场新工业革命。我们的使命是构建一个充满活力的学术生态,不仅推动科学认知的持续进步,更引导人工智能以负责任且造福社会的方式融入人类生活。

AI² aims to provide authoritative scholarship capable of enabling decision-makers to intentionally engage and successfully guide the new Industrial Revolution. Our mission is to cultivate a vibrant intellectual ecosystem that will not only advance scientific understanding but also guide the responsible and beneficial integration of AI into the fabric of society.


这一使命的核心在于深刻认识到:人工智能不仅是科技前沿的象征,更是推动产业、机构乃至社会数字化转型的强大引擎。人工智能创新正日益成为社会变革的强劲催化剂,它正在重塑经济模式、文化实践和治理结构,这要求我们既要进行严谨的学术探索,又要履行负责任的引导职责。通过深入探究人工智能、创新与数字化转型之间的互动机制,本刊致力于引领构建可持续的社会技术生态系统,实现技术卓越、伦理前瞻与以人为本价值观的有机融合。

At the heart of this mission lies the recognition that Artificial Intelligence is not only a scientific and technological frontier but also a powerful driver of digital transformation across industries, institutions, and societies. Innovation in AI increasingly acts as the catalyst of social change, reshaping economic models, cultural practices, and governance structures in ways that demand both rigorous intellectual inquiry and responsible stewardship. By exploring the reciprocal dynamics between AI, innovation, and digital transformation, this journal aspires to guide the development of sustainable socio-technical ecosystems that integrate technological excellence with ethical foresight and human-centric values.


我们的办刊理念深深植根于强调内外兼修的智慧传统。我们秉持“修身”理念,即不懈追求严谨学术,持续投入自我提升;我们坚守“济世”宗旨,确保所有知识与创新都承载着推动人类福祉和社会进步的重大责任。我们践行“行胜于言”的原则,立志将深刻的学术见解转化为应对现实挑战的可行方案。

Our editorial philosophy is deeply inspired by wisdom traditions that emphasize a synthesis of inner cultivation and outer contribution. We believe in “Self-Discipline,” a relentless dedication to rigorous inquiry and a commitment to continuous self-improvement. We also hold fast to “Social Commitment,” the profound responsibility to ensure that all knowledge and innovation carry the weight of advancing human well-being and societal progress. We champion the principle that “Actions Speak Louder Than Words,” dedicating ourselves to translating deep academic insights into actionable solutions for real-world challenges.


AI²的战略定位为“开创而非模仿”。我们深知,历史上最具影响力的期刊往往是通过开创并奠定新的研究领域而闻名。因此,我们并不打算在成熟的人工智能或创新类期刊的既定赛道上展开竞争,而是致力于定义并引领一个新兴、关键且高度跨学科的领域——或可称之为“全球人工智能治理与公平创新”。我们的目标是成为这一新领域的学术引力中心,为全球学者提供亟需的新颖见解和独特平台,以便开展对人工智能基础科学、工程系统、社会影响及伦理治理之间相互作用的整合性、系统性分析。

The strategic positioning of AI² is one of “field creation, not imitation”. We recognize that the most influential journals in history have often created and institutionalized new areas of inquiry. Therefore, we do not seek to necessarily compete in the established lanes of mature AI or innovation journals. Instead, we are dedicated to defining and leading an emergent, vital, and highly interdisciplinary field, which we may call “Global AI Governance and Equitable Innovation.” We aim to become the intellectual center of gravity for this new field, providing much needed novel insights and a unique platform for scholars worldwide to conduct integrated, systemic analysis of the interplay between AI''s foundational science, its engineering systems, its societal impact, and its ethical governance.


为此,AI²确立了以下三项核心使命:

For these reasons, AI² embraces three core mandates, as follows:


01

Interdisciplinarity

跨学科融合:本刊的独特之处在于其显著的跨学科特性。投稿文章需至少整合本刊所涵盖领域中两个不同维度的学术观点。这一要求旨在促进知识体系的交叉融合,进而打破传统学科界限的桎梏。

Interdisciplinarity: A unique trait of the journal is its interdisciplinary nature. Submissions ought to integrate insights from at least two of the research dimensions listed in the journal''s description. This requirement ensures the synthesis of knowledge required to push beyond traditional disciplinary boundaries.

02

Diversity and Inclusivity

多元与包容:本刊的影响力不仅限于学术界,更积极融入社会,为决策者提供有力参考。我们的编委会成员遍布全球20多个国家,尤其注重吸纳新兴经济体的学者,全力推崇多元方法论及差异化的认知与伦理视角。这种全球化布局使本刊成为推动多边化、去中心化人工智能政策发展的重要催化剂——这些政策旨在最大化人工智能革命的效益,惠及全人类,助力实现人类繁荣与道德进步。

Diversity and Inclusivity: The journal exerts its influence beyond academic confines to actively engage society and inform decision-makers. Our editorial board representing more than 20 countries, with a significant focus on emerging economies, champions diverse methodologies and varies epistemological and ethical insights. Its global reach positions the journal as a vital catalyst for developing multilateral, decentralized AI policies that are aimed at maximizing the benefits of the AI Revolution for human flourishing and moral development.

03

Top-Notch Expertise Shaping Global Discourse

引领全球对话的顶尖专家团队:编委会汇聚了享誉国际的学者,成员包括多国权威科学院院士(如中国科学院、俄罗斯科学院、加拿大皇家学会、英国国家学术院、澳大利亚人文科学院等)、顶尖专业组织的核心成员(如IEEE终身会士)、国家级重要荣誉获得者,以及重要科学协会的现任或前任主席(如国际模糊系统协会、IEEE计算智能协会等)。这一卓越的专家团队不仅确保了最高的学术严谨性,更保障了期刊的广泛代表性及真正的全球影响力。

Top-Notch Expertise Shaping Global Discourse: The editorial board is composed of world-renowned scholars and includes Fellows of esteemed national academies (such as the Chinese Academy of Sciences, The Russian Academy of Sciences, The Royal Society of Canada, The Royal Society of Edinburgh, The British Academy, The Australian Academy of Humanities etc), members of leading professional organizations (such as IEEE Life Fellows), as well as recipient of significant national honors (e.g., Officers of the Order of Australia, Australia Laureate Fellows) and current or past Presidents of important scientific societies (such as the International Fuzzy Systems Association, the IEEE Computational Intelligence Society, among the others). This unparalleled expertise ensures the highest level of academic rigor while guaranteeing representativeness and a truly global reach.

为实现这一宏伟使命,本刊将致力于达成以下核心目标:

This ambitious mission is best served by pursuing the following core objectives:

01

Pushing the Boundaries of Science

推动科学前沿探索:构建权威的学术交流平台,促进跨学科对话,加速科学进步,引领社会各界全面认识人工智能在技术创新、经济范式及社会结构中的变革性潜力。

Pushing the Boundaries of Science: by serving as the definitive academic and professional venue for catalyzing cross-disciplinary dialog, accelerating scientific advancements and fostering a holistic understanding of AI''s transformative potential in technological innovation, economic paradigms, and societal structures.

02

Empowering Visionary Governance and Strategic Foresight

赋能远见治理与战略前瞻:发布严谨且权威的学术成果,为决策者、行业领袖及政策制定者提供基于实证的深刻洞见与伦理框架,使其能够主动参与并审慎引领当前人工智能驱动的全球变革,推动社会和谐发展。

Empowering Visionary Governance and Strategic Foresight: by publishing rigorous, authoritative scholarship capable of endowing decision-makers, industry leaders, and policymakers with the evidence-based insights and ethical frameworks necessary to proactively engage with, and judiciously steer, the ongoing AI-driven global transformation, toward societal harmony.

03

Championing Human-Centric Values and Sustainable Futures in the AI Era

弘扬人本价值,构筑可持续未来:深入剖析人工智能带来的社会经济影响,阐释其背后的理论图景与价值体系,积极倡导并推动那些注重人类公平发展、尊重民主价值、促进社会长期福祉的政策与创新。

Championing Human-Centric Values and Sustainable Futures in the AI Era: by critically analyzing the socio-economic impacts precipitated by AI, articulating theoretical landscapes and value systems, as well as by promoting the design and adoption of policies and innovations that prioritize equitable human flourishing, democratic values, and enduring societal well-being.

基于上述宗旨,AI²期刊诚挚征集具有高度学术影响力、原创性及跨学科特性的研究成果。投稿应致力于对人工智能与创新交汇领域所面临的复杂挑战与机遇进行富有雄心的综合性分析。本刊要求来稿既展现概念深度,又具备实证严谨性,其研究议题需涵盖认知、伦理、产业、经济、政治、法律及社会文化等多个层面。因此,投稿的论文必须实质性地涉及并贡献于以下至少两个(或更多)研究方向或领域:

For these reasons, AI² seeks high-impact, original and interdisciplinary submissions that undertake ambitious, integrative analyses of complex challenges and opportunities arising at the confluence of AI and innovation. Contributions are expected to bridge conceptual depth with empirical rigor, addressing issues across cognitive, ethical, industrial, economic, political, legal, and socio-cultural strata. Thus, submissions to AI² must meaningfully engage with, and contribute to, at least two (or more) of the following research directions or domains:

01

Foundations and Frontiers of AI Science

人工智能科学的基础与前沿:推动创新性理论范式的发展,探索智能的基本原理。

Foundations and Frontiers of AI Science: Advancing innovative theoretical paradigms and exploring the fundamental underpinnings of intelligence.

02

AI Engineering and Systems Innovation

人工智能工程与系统创新:聚焦于人工智能硬件、软件及集成系统中具有变革性的技术突破。

AI Engineering and Systems Innovation: Spotlighting transformative technological breakthroughs in AI hardware, software, and integrated systems.

03

AI Applications and Societal Impact

人工智能应用与社会影响:探讨特定关键领域的应用,以及从医疗健康到气候变化等全球性挑战与社会结构变革。

AI Applications and Societal Impact: Addressing critical sector-specific applications and global challenges and societal disruption, from healthcare to climate change.

04

AI Ecosystems, Governance and Ethics

人工智能生态系统、治理与伦理:通过构建坚实的伦理框架与公平的治理模式,开辟通往负责任的人工智能未来的路径。

AI Ecosystems, Governance and Ethics: Forging pathways to responsible AI futures through robust ethical frameworks and equitable governance models.


3

稿件类型

Types of Contributions

AI²期刊诚挚邀请各类稿件,致力于促进人工智能革命与技术创新之间的建设性互动。无论是纯学术研究,还是可能对其发展产生影响的公共政策制定或企业实践探索,均在征稿范围之内。本刊亦欢迎采用多元方法论、融合不同文化视角、伦理观念及认识论智慧的文章,旨在为关于新兴人工智能技术及其社会影响的实质性、前瞻性议题提供建设性见解。我们旨在为这一研究领域内日益增多的跨学科学者打造一个多学科、多元且包容的学术交流平台。

AI² invites manuscripts that contribute toward the productive engagement between the ongoing AI revolution and technological innovation, whether through purely academic investigations or through the development of public policies or private actions that may govern their development. AI² also welcomes articles that use various methodologies and diverse cultural, ethical as well as epistemological insights to productively inform and advance ongoing debates on substantive, future-oriented questions about new AI technologies and their impact in society. AI² thus wants to provide a multidisciplinary, diverse, and inclusive platform for the increasing number of highly interdisciplinary scholars working in this research domain.

此外,AI²不仅面向学术界,也力求触及广大相关领域的实践者,包括技术评估与开发、战略研究管理、人工智能治理与伦理等领域的从业者,以及人文、工程、计算机科学、管理与商科等学科的教师。为此,本刊特别欢迎以下五类投稿:

In addition, AI² wishes to reach not only scholars, but also practitioners in areas of focus such as technology assessment/development, strategic research management, AI governance, AI ethics as well as teachers in the humanities, engineering, computer science, management and business. To this extent, AI² welcomes 5 major types of contributions, as follows:

01

Research Articles

研究论文(不超过10,000字):展示实证研究、实验或理论工作的创新性发现。此类文章通常包括结构化摘要、引言、研究方法、结果、讨论以及局限性分析。

Research Articles (up to 10,000 words): Present novel findings from empirical studies, experiments, or theoretical work. These articles typically include a structured abstract, introduction, methods, results, discussion, and limitations.

02

Review Articles

综述文章(不超过12,000字):总结并批判性评述特定主题的现有文献。此类文章应提供新见解,指出研究空白,并提出未来研究方向。

Review Articles (up to 12,000 words): Summarize and critically evaluate existing literature on a specific topic. Such articles should provide new insights, identify gaps, and suggest future research directions.

03

Short Communications

简短通讯(不超过2,500字):针对具有即时学术价值的原创研究数据进行简要报告,通常包含简明的引言、方法、结果与讨论。

Short Communications (up to 2500 words): Brief reports of data from original research that are of immediate interest. Typically includes a concise introduction, methods, results, and discussion.

04

Editorial Opinions

社论观点(不超过1,500字):由期刊编辑团队或特邀专家撰写,主要针对具有社会意义的议题或本刊已发表文章进行评述。

Editorial Opinions (up to 1500 words): Pieces written by the journal''s editorial team or invited experts, often commenting on issues of societal relevance or articles published in the journal.

05

Perspective Articles

观点文章(不超过4,000字):学者针对某一领域发表的个人见解或前瞻性评论,通常侧重于业界视角。

Perspective Articles (up to 4000 words): Author opinions or forward-looking commentaries on a field, often industry oriented.


与此同时,《人工智能与创新》期刊诚挚邀请学界同仁投稿高质量专题(特刊)提案。与众多仅将人工智能视为技术挑战,或单纯关注商业与管理创新的既有期刊不同,本刊旨在构建一个融合性的学术空间。我们的独特价值在于:将长期相互隔离的各学科研究视角汇聚于同一平台,以此填补学术生态中的重要空白——当前正缺乏能系统整合人工智能科学基础与其全球社会影响、治理需求于一体的学术论坛。通过放大来自代表性不足地区及认知传统的声音,本刊不仅追随现有学术讨论,更致力于重塑讨论范式。这种跨学科性、包容性与全球公平性的深度融合,使《人工智能与创新》成为一项开创性事业,有望为未来数十年的研究与辩论树立全新标准。

AI & Innovation also encourages prospective authors to submit for consideration for publication high-quality proposals for Topical Collections (Special Issues). Unlike many established journals that address AI narrowly as a technical challenge or focus exclusively on innovation in business and management, AI & Innovation is deliberately conceived as a hybrid intellectual space. Its uniqueness lies in bringing together the often siloed perspectives of engineering, ethics, governance, economics and socio-cultural studies into a single platform. In doing so, it addresses a critical gap in the scholarly ecosystem: the absence of a forum that systematically integrates the scientific foundations of AI with its global societal consequences and governance imperatives. By amplifying voices from underrepresented regions and epistemic traditions the journal does not merely follow existing discourses but reshapes them. This combination of interdisciplinarity, inclusivity and global equity makes AI & Innovation a pioneering venture capable of setting new standards for research and debate in the decades ahead.



4

致谢

Acknowledgments

创办新刊是一项浩大工程,我们需向众多人士表达由衷的谢意。首先,感谢威立(Wiley)团队自始至终展现的专业精神、迅速响应与全情投入;其次,感谢由64位国际学者组成的卓越编委团队,他们以满腔热忱与非凡担当,积极参与本刊建设,从创刊之初便倾力奉献;再次,感谢各位副主编在承担繁重工作的同时,欣然接受为本刊履行学术职责;最后,更要感谢亲爱的读者与潜在供稿人——我们坚信,诸位将共同构筑一个充满活力的学术共同体,形成对“创新中的人工智能”的深刻共识。我们期望,这不仅将推动学术进步,更将在当今这个日新月异的多中心世界里,重塑科学、技术与创新的存在方式。在此,谨向亲爱的读者们致以诚挚的谢意,欢迎您加入《人工智能与创新》的探索之旅!

There are numerous people to thank for the significant undertaking of starting a new journal. Firstly, the team at Wiley which has been dedicated, responsive and very professional from the very beginning. Secondly, the 64 international members of our stellar editorial board, who demonstrated kindness and remarkable commitment in joining the activities of this new venue and enthusiastically contributing to it from the start. Thirdly, the associate editors, who despite their heavy commitments, have kindly accepted to perform academic duties for the journal. Lastly, all of you our dear readers and potential contributors, who, we are sure will contribute to form a vibrant intellectual community and a common understanding of AI in Innovation that we hope will make real inroads not only to scholarship but also to the ways in which science, technology and innovation exist in today''s ever changing, polycentric world. So, thank you, dear readers, and welcome to AI & Innovation.


参考文献

[1] A. Brem, F. Giones, and M. Werle, “The AI Digital Revolution in Innovation: A Conceptual Framework of Artificial Intelligence Technologies for the Management of Innovation,” IEEE Transactions on Engineering Management 70, no. 2 (2021): 770–776, https://doi.org/10.1109/tem.2021.3109983.

[2] H. Wang, T. Fu, Y. Du, et al., “Scientific Discovery in the Age of Artificial Intelligence,” Nature 620, no. 7972 (2023): 47–60, https://doi.org/10.1038/s41586-023-06221-2.

[3] M. Hutson, “Hypotheses Devised by AI Could Find ‘Blind Spots’ in Research: Artificial Intelligence Is Asking Questions That Humans Hope to Answer,” Nature (2023), https://doi.org/10.1038/d41586-023-03596-0.

[4] S. Erduran and O. Levrini, “The Impact of Artificial Intelligence on Scientific Practices: an Emergent Area of Research for Science Education,” International Journal of Science Education 46, no. 18 (2024): 1982–1989, https://doi.org/10.1080/09500693.2024.23066

[5] C. Wong, “How AI Is Improving Climate Forecasts,” Nature 628, no. 8009 (2024): 710–712, https://doi.org/10.1038/d41586-024-00780-8.

[6] R. Kwok, “AI Empowers Conservation Biology,” Nature 567, no. 7746 (2019): 133–134, https://doi.org/10.1038/d41586-019-00746-1.

[7] C. I. Wu and C. Li, “Artificial Intelligence and Biological Research,” National Science Review 11, no. 11 (2024): nwae415, https://doi.org/10.1093/nsr/nwae415.

[8] H. Kunze, D. La Torre, A. Riccoboni, and M. R. Galán, eds., Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications (CRC Press, 2023).

[9] S. Ahmad, K. Shah, and A. Debbouche, “Structural Equation Modelling for Causal Effect Estimation With Machine Learning,” Journal of Computational and Applied Mathematics 475 (2025): 117020, https://doi.org/10.1016/j.cam.2025.117020.

[10] P. Lemos, N. Jeffrey, M. Cranmer, S. Ho, and P. Battaglia, “Rediscovering Orbital Mechanics With Machine Learning,” ArXiv 2202.02306 (2022), https://doi.org/10.48550/arXiv.2202.02306.

[11] L. Jiao, X. Song, C. You, et al., “AI Meets Physics: A Comprehensive Survey,” Artificial Intelligence Review 57, no. 9 (2024): 256, https://doi.org/10.1007/s10462-024-10874-4.

[12] R. Van Noorden and J. M. Perkel, “AI and Science: What 1,600 Researchers Think,” Nature 621, no. 7980 (2023): 672–675, https://doi.org/10.1038/d41586-023-02980-0.

[13] M. Farina, A. Gorb, A. Kruglov, and G. Succi, “Technologies for GQM-Based Metrics Recommender Systems: A Systematic Literature Review,” IEEE Access 10 (2022): 23098–23111, https://doi.org/10.1109/access.2022.3152397.

[14] D. Schwalbe-Koda, Z. Jensen, E. Olivetti, and R. Gómez-Bombarelli, “Graph Similarity Drives Zeolite Diffusionless Transformations and Intergrowth,” Nature Materials 18, no. 11 (2019): 1177–1181, https://doi.org/10.1038/s41563-019-0486-1.

[15]  E. A. Olivetti, J. M. Cole, E. Kim, et al., “Data-Driven Materials Research Enabled by Natural Language Processing and Information Extraction,” Applied Physics Reviews 7, no. 4 (2020): 041317, https://doi.org/10.1063/5.0021106.

[16] B. Gomes and E. A. Ashley, “Artificial Intelligence in Molecular Medicine,” New England Journal of Medicine 388, no. 26 (2023): 2456–2465, https://doi.org/10.1056/nejmra2204787.

[17] O. Mypati, A. Mukherjee, D. Mishra, S. K. Pal, P. P. Chakrabarti, and A. Pal, “A Critical Review on Applications of Artificial Intelligence in Manufacturing,” supplement Artificial Intelligence Review 56, no. S1 (2023): 661–768, https://doi.org/10.1007/s10462-023-10535-y.

[18] R. R. Murphy, Introduction to AI Robotics (MIT Press, 2019).

[19] L. Cao, “Ai in Finance: Challenges, Techniques, and Opportunities,” ACM Computing Surveys 55, no. 3 (2022): 1–38, https://doi.org/10.1145/3502289.

[20] S. Y. Liu, “Artificial Intelligence (AI) in Agriculture,” IT Professional 22, no. 3 (2020): 14–15, https://doi.org/10.1109/mitp.2020.2986121.

[21] M. van Hilten, M. Ryan, V. Blok, and N. de Roo, “Ethical, Legal and Social Aspects (ELSA) for AI: An Assessment Tool for Agri-Food,” Smart Agricultural Technology 10 (2025): 100710, https://doi.org/10.1016/j.atech.2024.100710.

[22] H. Yang, Z. Li, W. Pedrycz, and M. Farina, “Deep Learning From Crowds on a Healthy Data Diet,” IEEE Transactions on Systems, Man and Cybernetics: Systems 55, no. 9 (2025): 6150–6163, https://doi.org/10.1109/tsmc.2025.3578893.

[23] M. Farina, X. Yu, and J. Chen, Digital Development: Technology, Ethics and Governance (Routledge, 2025).

[24] M. Farina, P. Ciancarini, X. Yu, and J. Chen, Digital Transformation in Artificial Systems: Engineering Requirements, Political, Economic, and Philosophical Challenges (Elsevier, Morgan Kaufmann, 2025).

[25] M. Farina, W. Yuxuan, and S. Kladko, “Ethical and Epistemological Reflections on Autonomous AI-Powered Agents,” Topoi (2025), https://doi.org/10.1007/s11245-025-10218-z.

[26] MIT Sloan Management Review, How to Go Digital: Practical Wisdom to Help Drive Your Organization''s Digital Transformation (MIT Press, 2018).

[27] T. H. Davenport and G. Westerman, “Digital Transformation,” Harvard Business Review (2018), https://hbr.org/2018/03/why-so-many-high-profile-digital-transformations-fail.

[28] M. Farina and W. Pedrycz, “Machine Learning in Society: Prospects, Risks, and Benefits,” Philosophy & Technology 37, no. 3 (2024): 99, https://doi.org/10.1007/s13347-024-00782-4.

[29] G. Elia, G. Solazzo, A. Lerro, F. Pigni, and C. L. Tucci, “The Digital Transformation Canvas: A Conceptual Framework for Leading the Digital Transformation Process,” Business Horizons 67, no. 4 (2024): 381–398, https://doi.org/10.1016/j.bushor.2024.03.007.

[30] Z. Tekic and J. Füller, “Managing Innovation in the Era of AI,” Technology in Society 73 (2023): 102254, https://doi.org/10.1016/j.techsoc.2023.102254.

[31] L. Stellinga, P. Korenhof, and V. Blok, “Bio-Centred Artificial Intelligence: Towards a Progressive AI-Biosphere Relation Through the Concepts of Poiesis and Mimesis,” Topoi (2025).

关于AI²


《人工智能与创新》(AI & Innovation,简称 AI²)学术期刊由金砖创新基地数字经济研究中心(Institute for Digital Economy & Artificial Systems,简称IDEAS)与清华大学技术创新研究中心、厦门大学人工智能研究院共同主办,并联合威立(Wiley)出版。本期刊基于AI的基础理论、工程系统、社会治理和创新生态四大战略维度,致力于在跨学科视角下全面研究智能科学发展领域,推动全球数字创新和发展研究,建立国际权威话语体系,帮助政府机构和行业制定适应数字经济发展战略。


IDEAS是依托厦大、莫大建设的前沿交叉学科研究阵地、新兴战略产业高端智库、科技成果转化服务平台、国际专业人才合作通道。在金砖国家新工业革命伙伴关系框架内,IDEAS以"数字化,为了更智慧的全球合作:全球化,为了更广阔的数字包容”(Digitalization, for a Wiser Global Cooperation, Globalization, for aWider Digital Inclusion)为理念,与各方共建国际数字经济与智能科技协同研发网络。






威立(Wiley)是权威内容与科研智慧领域的全球领导者,致力于推动科学探索、创新发现与学习发展。两个多世纪以来,我们始终立于学术生态体系的中心,将悠久的出版传承与人工智能驱动的平台深度融合,重塑知识的发现、获取与应用方式。从独立研究员、莘莘学子到世界500 强企业的研发团队,威立始终助力将先进的科学突破转化为切实的社会实践。从知识到影响力 —— 我们正在重新定义科学与求知领域的无限可能。






  • 客服电话: 400-6699-117 转 1000
  • 京ICP备07018254号
  • 电信与信息服务业务经营许可证:京ICP证110310号
  • 京公网安备1101085018
  • 客服电话: 400-6699-117 转 1000
  • 京ICP备07018254号
  • 电信与信息服务业务经营许可证:京ICP证110310号
  • 京公网安备1101085018

Copyright ©2007-2026 ANTPEDIA, All Rights Reserved