情报信息的侦查模式

侦查模式是指侦查主体进行侦查活动时所采用的程式。传统侦查模式可分为从案到人、从人到案、从案到人、从物到案等模式。情报信息的侦查模式是利用情报信息系统和通讯网络开展的侦查方式,从侦查切入点、侦查思维、侦查措施、侦查效率等方面与传统侦查模式有着较大的差别。情报信息的侦查模式具有反应迅速、过程保密、结果客观、成本低、效率高等优势和特点。     

The Promise and Peril of Automated Negotiators

Innovations in artificial intelligence are enabling a new class of applications that can negotiate with people through chat or spoken language. Developed in close collaboration with behavioral science research, these algorithms can detect, mimic, and leverage human psychology, enabling them to undertake such functions as the detection of common mistakes made by novice negotiators. These algorithms can simulate the cognitive processes that shape human negotiations and make use of these models to influence negotiated outcomes. This article reviews some of the scientific advances enabling this technology and discusses how it is being used to advance negotiation research, teaching, and practice.     

同事排斥对新入职毕业生工作绩效的影响 ：情绪智力的调节作用

职场排斥不利于高校毕业生的角色适应和绩效提升。本研究基于资源保存理论,从职场排斥现阶段研究较少的同事角度入手,探讨同事排斥、情绪智力对新入职毕业生工作绩效的影响。研究发现:(1)同事排斥负向影响工作绩效(任务绩效、关系绩效);(2)情绪智力正向影响工作绩效(任务绩效、关系绩效);(3)情绪智力负向调节同事排斥与任务绩效的关系,即情绪智力会弱化同事排斥对新入职员工任务绩效的负面效应。     

从矛盾到共生：论智能化时代劳动教育资源的科技化向度

第四次工业革命的到来颠覆了人类的劳动认知与劳动形式,数字化技术、信息化技术的迅速发展对劳动教育带来巨大冲击,表现为劳动中人类主体性价值被弱化、劳动的教育性被淡化、劳动教育的时空泛在化。究其根本是因为劳动教育资源开发滞后于社会的发展。首先,劳动教育资源认知的滞后导致劳动教育开展的局限性;其次,劳动教育传统资源开发手段使得劳动教育技术落后;最后,劳动教育资源开发的内容处于“象牙塔”中,致使劳动教育与社会脱节。要将智能化时代带来的“危”转化为劳动教育发展的“机”,需聚焦劳动教育资源开发的科技化,更新概念认知、跳出惯性思维,善用大数据等方式促使劳动教育与智能技术和谐共生。     

建构非对称竞争优势的尝试:俄罗斯人工智能治理体系的结构与逻辑解析

俄罗斯人工智能治理体系的外在形态是“一体两翼”式的政策网络,以《2030年前俄罗斯联邦国家人工智能发展战略》作为基本战略构想,以数字经济框架内的人工智能“路线图”和人工智能联邦项目建构发展议程,以《2024年前俄罗斯人工智能和机器人技术领域监管发展构想》为核心确立监管议程。而俄罗斯人工智能治理体系的实体结构则表现为在联邦政府统一领导下的二元平行系统运作模式,由国防部担任操盘手的军事人工智能板块已经建立了完整的闭环系统,而以俄罗斯联邦储蓄银行为主要操盘手的民用人工智能板块的运行机制仍有待进一步完善。特殊的治理体系源于俄罗斯人工智能战略的底层逻辑,是俄罗斯政府面对战略目标与现实困境巨大鸿沟所做出的现实抉择,这种剑走偏锋的设计虽然取得了部分短期成果,但并未实际解决制约俄罗斯人工智能发展的关键问题,能否走出一条人工智能发展的“俄罗斯道路”仍有待观察。     

The Scharff technique: training military intelligence officers to elicit information from small cells of sources

ABSTRACT

Studies have demonstrated the efficacy of the Scharff technique for gathering human intelligence, but little is known about how this efficacy might vary among different samples of practitioners. In this training study we examined a sample of military officers (n?=?37). Half was trained in the Scharff technique and compared against officers receiving no Scharff training. All officers received the same case file describing two sources holding information about a terrorist attack. University students (n?=?74) took the role of the semi-cooperative sources. Scharff-trained officers adhered to the training as they (1) aimed to establish the ‘knowing-it-all’ illusion, (2) posed claims as a means of eliciting information, and (3) asked fewer explicit questions. The ‘untrained’ officers asked many explicit questions, questioned the reliability of the provided information, pressured the source, and displayed disappointment with the source's contribution. Scharff-trained officers were perceived as less eager to gather information and left their sources with the impression of having provided comparatively less new information, but collected a similar amount of new information as their untrained colleagues. The present paper both replicates and advances previous work in the field, and marks the Scharff technique as a promising technique for gathering human intelligence.     

人工智能时代精准人才管理探析

人才是组织获得长远发展的第一资源。随着人工智能时代的到来,如何运用人工智能技术对人才进行精准化地选、用、育、留、储,是组织探索解决人才管理瓶颈的关键。研究从人工智能时代精准人才管理的挑战与机遇入手,指出基于"合不合"理论以构建智能化精准人才管理系统,并探讨了"AI人才管理专家系统"的具体运用情况,以期为各类组织进行精准人才管理提供帮助。     

美国国家安全情报传递机制论析

作为世界上情报体系最为发达的国家,美国国家安全情报机制一直以来备受各方关注。九一一事件催生了美国情报体系全面而彻底的改革。经过十多年的努力,美国情报界实现了从机构林立的分散体系到由国家情报总监办公室领导的有机整体的重大转型。从总体机制来看,美国情报界现已形成情报机构一体化与任务一体化的双轮驱动体系,其情报传递网络不仅涵盖领导、协调、执行三个层级间的纵向传送,而且包括不同情报机构之间的横向协调,基本实现了情报整合与信息共享。美国国家情报总监办公室成为名副其实的美国情报界统领,其下设的反恐、反扩散、反情报和网络情报中心构成了美国国家安全情报分类传递机制的四大支柱。通过比较,四大分类传递机制中最为成熟的是反恐中心,其次是反情报与安全中心,再次是网络威胁情报整合中心,最后是反扩散中心。由于各类情报机制自身发展程度的不同,其改革过程中所面临的挑战也不一样。美国国家安全情报传递机制的改革“瓶颈”既有发展不足导致的结构性困境,也有外部安全环境变化带来的挑战。此外,特朗普政府上台后的一系列政策举措使得美国国家安全情报体系的发展方向呈现出新的态势。     

论人工智能赋值国家治理:方法、视角与维度

赋值是智能政治学的重要研究课题,赋值研究是智能政治学的重要分析方法.人工智能赋值国家治理,从分析视角来看,表现为人工智能科学、人工智能技术、人工智能形态和人工智能体对国家治理的多重赋值和多源性影响作用.从分析维度来讲,表现为人工智能从赋益、赋义、赋能、赋权、赋则和赋责等多维度影响作用或赋值国家治理,甚至推动国家治理从"...     

Responsibility Determination: Free Will and Legal Responsibility in the Age of Artificial Intelligence

Free will is the foundation of determination of responsibility. Genetic enginnering represented by technologies of gene editing, artificial medical devices and AI have fundamentally challenged the concept of free will and so have significantly influenced determination of legal responsibility. These challenges are fundamental, not instrumental, and can be divided into two aspects in legal philosophy. First, the direct challenge, that is, the emerging technology represented by genetic engineering and artificial narrow intelligence (ANI) has challenged the concept of free will. Second the would-be ultimate challenge, that is, presented by an artificial general intelligence (AGI) agent that is considered to reach humanlevel free will, can be a legal subject, thus taking full legal responsibility. The direct challenge constitutes a new “forgiveness” condition for taking responsibility. The would-be ultimate challenge deserves significant attention, because the concept of free will is not only about human responsibility, but also about human dignity.