人工智能时代企业管理变革的逻辑与分析框架

人工智能作为社会发展和技术创新的产物,已经成为新一轮科技创新和产业变革的核心驱动力,正在对世界经济、社会进步和人民生活产生极其深刻的影响。人工智能的商业应用会改变企业内部运作和生产经营的过程,为企业管理带来了诸多挑战和变革机遇。本文结合人工智能的特征与发展趋势,从管理对象、管理属性、管理决策和管理伦理四个方面对人工智能时代企业管理变革的逻辑进行了梳理,得出如下推论:第一,人工智能时代,被管理者将出现越来越多的"人工智能员工",以"社会人"为中心的管理理论和管理手段的适用性降低,如何管理"人工智能员工"以及协调人类员工与智能机器人的关系将对管理者提出挑战;第二,人工智能时代,管理属性不仅包括管理理论的科学性、管理实践的艺术性,还包括管理过程的技术性;第三,人工智能时代,将出现一批优秀的技术管理者,此时,技术管理者指的不是管理技术的人,而是掌握智能技术的管理者;第四,人工智能时代,管理者的决策环境得到优化,管理活动中的决策准则将由"满意决策"过渡为"最优决策";第五,人工智能时代,管理手段的智能化发展可能会加剧管理效率和管理伦理的冲突,管理者必须提升管理道德,经营过程中强化社会责任的履行;第六,随着人工智能技术发展,政府、社会团体和行业协会有必要从政策、法律与行业标准等多个方面构建人工智能发展伦理的多层次约束机制。     

人工智能背景下医疗法律责任的现实困境与完善路径

医疗人工智能利用深度学习和计算机算法等现代化技术，实现辅助诊疗、医学影像、药物发掘、健康诊疗等功能，是人工智能应用最具前景的领域之一。随着人工智能技术发展，具备自主思维和决策能力的智能机器人医生等人工智能将对现有的医疗法律责任制度带来颠覆性影响。在人工智能背景下，医疗人工智能是否具有独立法律主体地位、传统的医疗过错责任归责能否适用、因果关系如何认定等成为现代民事法律责任制度的严峻挑战，也成为实践中的必答之问。因此，在借鉴欧美人工智能领域的探索经验的基础上，在当前阶段通过修正和完善我国民事法律责任制度，提出针对不同的人工智能侵权情形适用差别化归责原则，并尝试建立人工智能强制保险或储备金制度，设置人工智能监管机构及行业标准，以实现既保障患者合法公平权益，又鼓励人工智能技术有效发展之间的平衡。     

Scientific consensus,the law,and same sex parenting outcomes

While the US Supreme Court was considering two related cases involving the constitutionality of same-sex marriage, one major question informing that decision was whether scientific research had achieved consensus regarding how children of same-sex couples fare. Determining the extent of consensus has become a key aspect of how social science evidence and testimony is accepted by the courts. Here, we show how a method of analyzing temporal patterns in citation networks can be used to assess the state of social scientific literature as a means to inform just such a question. Patterns of clustering within these citation networks reveal whether and when consensus arises within a scientific field. We find that the literature on outcomes for children of same-sex parents is marked by scientific consensus that they experience “no differences” compared to children from other parental configurations.     

人工智能辅助地方立法的应用与规制

我国地方立法权随着2015年《立法法》的修改扩至所有设区的市，随之掀起地方立法热潮。但目前地方立法的质量普遍不高，存在诸多问题，人工智能技术的应用能为地方立法开辟新路径。基于互联网及大数据的人工智能，能被应用于资料检索、立项论证、立法公开与意见征集、辅助草案起草、立法后评估与备案审查。与此同时，当人工智能被应用于地方立法工作时，需要确立“辅助原则”，规范人工智能地方立法程序的选用标准，限制人工智能地方立法程序的算法，以此来规制人工智能带来的不利影响。     

How leader role identity influences the process of leader emergence: A social network analysis

Contemporary theories on leadership development emphasize the importance of having a leader identity in building leadership skills and functioning effectively as leaders. We build on this approach by unpacking the role leader identity plays in the leader emergence process. Taking the perspective that leadership is a dynamic social process between group members, we propose a social network-based process model whereby leader role identity predicts network centrality (i.e., betweenness and indegree), which then contributes to leader emergence. We test our model using a sample of 88 cadets participating in a leadership development training course. In support of our model, cadets who possess a stronger leader role identity at the beginning of the course were more likely to emerge as leaders. However this relationship was only mediated by one form of network centrality, indegree centrality, reflecting one's ability to build relationships within one's group. Implications for research and practice are discussed.     

How do countries choose their monetary policy frameworks?

This paper investigates the determinants of countries’ choices of monetary policy framework. A brief narrative focused on groupings of countries motivates an econometric analysis which draws on previous work on the determinants of exchange rate regimes, bringing in standard factors as well as the trade networks of potential anchor currency blocs and the financial market depth that are emphasised in the narrative. The model turns out to be able to predict three quarters of countries’ choices, and there is no obvious systematic pattern in the errors. The results have important implications for how countries should choose their monetary policy frameworks.     

汇率货币模型的非线性协整关系检验——基于深度GRU神经网络

本文采用深度门控循环单元（GRU）神经网络探讨三种汇率货币模型（弹性价格、前瞻性和实际利率差模型）的非线性协整关系。GRU技术在深度学习中具有智能记忆、自主学习和强逼近能力等优点。为此，本文运用该技术对6组典型浮动汇率制国别数据进行了非线性Johansen协整检验。结果表明，汇率与宏观经济基本面之间存在非线性协整关系，从而说明了货币模型在非线性条件下的有效性，以及先进的深度学习工具在检验经济理论中的优势。     

Security Investment in Contagious Networks

Security of the systems is normally interdependent in such a way that security risks of one part affect other parts and threats spread through the vulnerable links in the network. So, the risks of the systems can be mitigated through investments in the security of interconnecting links. This article takes an innovative look at the problem of security investment of nodes on their vulnerable links in a given contagious network as a game‐theoretic model that can be applied to a variety of applications including information systems. In the proposed game model, each node computes its corresponding risk based on the value of its assets, vulnerabilities, and threats to determine the optimum level of security investments on its external links respecting its limited budget. Furthermore, direct and indirect nonlinear influences of a node's security investment on the risks of other nodes are considered. The existence and uniqueness of the game's Nash equilibrium in the proposed game are also proved. Further analysis of the model in a practical case revealed that taking advantage of the investment effects of other players, perfectly rational players (i.e., those who use the utility function of the proposed game model) make more cost‐effective decisions than selfish nonrational or semirational players.     

用联想神经网络设计的信道均衡器

研究了联想神经网络在数字通信信道均衡器实现中的应用,讨论了其设计方法和设计步骤,给出了计算机模拟结果,并进行了性能比较。研究结果表明:Hopfield联想神经网络实现的信道均衡器具有比传统线性横向均衡器更优越的性能。     

模糊技术在高校教学评估中的研究

研究了高校教学评估中知识的模糊关系及权重问题,讨论在有关模糊隶属函数计算方法的基础上,将模糊技术应用在教学评估中,为教学评估的研究提供一条新的途径。