随着组织电子存储信息量的增长，早期案件评估已演变为一种寻求可操作情报的"数字考古"工作：筛选庞大的数字挖掘场、找到关键人物、确定事实、挖掘文档并构建案件。我们将早期案件评估这一更广泛的演变称为"早期案件情报"，它涵盖了传统的早期案件评估、早期数据评估和审阅准备。
As organizations’ volumes of ESI (electronically stored information) have grown, early case assessment (ECA) has become a kind of “digital archaeology” in search of actionable intelligence: sifting through enormous digital dig sites, finding the key players, determining the facts, unearthing the documents, and curating your case. We call this broader evolution of ECA “Early Case Intelligence” or ECI, encompassing traditional ECA, early data intelligence (EDA) and review preparation.
律师仅了解法律和其客户已远远不够；他们必须作为数字考古学家来构建这种早期案件情报能力。
要探索被称为"早期案件情报"的一系列实践，我们必须首先探究驱动传统早期案件评估的数字考古学。
It’s not enough for lawyers to merely understand the law and their clients; they must build this ECI competency as digital archaeologists.
To explore the set of practices referred to as “ECI” or Early Case Intelligence, we must first explore the digital archaeology that drives traditional ECA.
本文中，我们将回顾如何收集早期案件情报，以便法律从业者能够成为有效挖掘可操作早期案件情报的数字考古学家。
In this article, we review how to gather early case intelligence (ECI) so that legal practitioners can become digital archaeologists capable of effectively unearthing actionable ECI.
从早期案件评估到早期案件情报
Starting with ECA and ECI
2012年8月，美国律师协会对其《职业行为示范规则》进行了修改，明确要求律师需保持技术能力。自那时起，已有四十个州实施了此项要求或其变体。
In August 2012, the American Bar Association (ABA) implemented changes to its Model Rules of Professional Conduct, making the need to maintain technology competence explicit. Since then, this requirement or its variations have been implemented in forty states.
要成为一名高效的数字考古学家，关键不在于使用尽可能多的工具，而在于选择最适合当前目标的工具——无论是进行传统的早期案件评估、数据评估、调查还是审阅准备——然后在此基础上逐步实现项目的所有目标。
When it comes to being an effective archaeologist, it is not a question of utilizing as many tools as possible. Rather, it is a question of selecting the right ones to best serve your current goal, whether that’s traditional ECA, data assessment, investigation, or review preparation, then building on those steps to achieve all your project’s goals.
进行传统的早期案件评估
Pursuing Traditional ECA
传统的早期案件评估是一套旨在减少新法律事项带来的风险和费用相关不确定性的策略，用于为如何推进案件提供决策依据。
进行早期案件评估需要审阅相关的电子存储信息；因此，使用电子数据展示流程对于有效的传统早期案件评估至关重要。
Traditional ECA is a set of tactics focused on lessening the uncertainties that come with the risks and expenses related to a new legal matter, which are used to inform decisions on how to proceed.
Undertaking this requires reviewing relevant electronically stored information (ESI); as such, using eDiscovery processes is essential for effective traditional ECA.
如果您对所寻找的材料了解不多，最好从一种或多种最适合揭示未知信息的工具和技术入手：
If you don’t know a lot about the materials you’re seeking, you will want to start with one or more of the tools and techniques best suited to revealing unknowns:
普遍性估算：
基于正式抽样，用于确定您所掌握内容（例如，相关文件、特权文件、需要编辑的文件等）的数量。
Prevalence estimations, based on formal sampling, are used to determine the amount of something under your possession (e.g., relevant documents, privileged docs, documents requiring redaction, etc.).
正式与判断抽样：
可用于获取您所描述的语言横截面。这些抽样技术用于选择和分析数据子集（如文档、电子邮件或其他电子存储信息），以便对更大的数据集做出决策。
Formal and judgmental sampling can be used to get the linguistic cross-section you describe. These sampling techniques are used to select and analyze subsets of data, such as documents, emails, or other ESI to make decisions about the larger data set.
可视化工具：
（如通信图、词云等）可以揭示沟通和行为模式，帮助完善事件全貌。
Visualization tools (communication maps, word clouds, etc.) can reveal patterns of communication and behavior and help complete the picture of what happened.
概念索引功能：
让您能够使用概念搜索来查找相关材料（即使不知道最佳搜索词），使用概念聚类来探索主题横截面，并使用分类功能通过少量相关示例进行操作。
Conceptual indexing features let you use concept searching to find relevant materials without knowing the best search terms, concept clustering to explore a cross-section of topics, and categorization to use a few relevant examples.
实体提取：
较新的实体提取工具通过帮助识别案件中的关键个人、组织和地点，也有助于传统的早期案件评估。分析工具可以识别和提取广泛的信息，如人名、地址、电子邮件地址、电话号码、组织名称等。实体提取应用程序，也称为命名实体识别器，应用人工智能对各种类型的实体（如地点、个人或组织）进行分类。
Entity Extraction: Newer entity extraction tools also aid in traditional ECA by helping you identify the key individuals, organizations, and locations in your matter. Analytics tools can identify and extract a broad array of information, such as people’s names, addresses, email addresses, phone numbers, organization names, etc. Entity extraction applications, which are also known as Named Entity Recognizers (NERs), apply artificial intelligence to classify various types of entities, such as a location, a person, or an organization.
图像分析：
图像分析工具使用户能够在图像或视频中查找感兴趣的对象。在处理手机数据或监控视频时，经常需要在图像中搜索感兴趣的对象（例如，某个人、护照照片）。图像分析应用程序通过检查图像的像素来识别对象。当一组像素形成特定模式时，应用程序可以隔离图像中的不同对象。
Image Analysis: Image analysis tools allow users to find objects of interest within images or videos. Searching images for objects of interest (e.g., a person, a passport photo) often occurs when working with mobile phone data or security video. Image analysis applications work to identify objects by examining an image’s pixels. When a group of pixels form a pattern, the application can then isolate distinct objects within the image.
持续主动学习工作流：
可以在合适的文档集合中快速找到相关材料。
·Continuous active learning (TAR 2.0) workflows can rapidly surface relevant materials in suitable document collections.
一旦了解了要寻找什么，就可以从这些初步的探索性工作转向更有针对性的搜索和筛选工作，从而快速找到相关材料。在找到相关审阅文档时，还可以使用线程和重复项管理工具来查找相关材料以了解上下文，例如相关的电子邮件、替代草稿等。
Once you understand what you’re seeking, you can transition from these initial, exploratory efforts to more targeted search and filtering efforts, which can quickly find relevant materials. As you find relevant documents to review, you can also use thread and duplicate management tools to find related materials for context, such as with related emails, alternate drafts, etc.
进行电子数据评估
Pursuing Electronic Data Assessment(EDA)
如果您的首要任务是评估电子存储信息，那么查找单个文档就不如确保收集足够完整以及在处理过程中应用的任何筛选都未过度重要。在这种情况下，重点应放在看清电子存储信息收集的全貌并揭示其中的缺失：
If your top priority is assessing your ESI, finding individual documents is less important than ensuring a sufficiently complete collection has taken place and that any filtering applied during processing has not been excessive. In such situations, your focus should be on seeing the big picture of your ESI collection and revealing the gaps within it:
元数据过滤和可视化工具：
可以通过发现元数据值（包括日期范围）中的缺失、生成通信图以显示保管人之间的联系来帮助评估电子存储信息收集的完整性。它们还可以生成词云以显示常用语言。
Metadata filtering and visualization tools can help you assess the completeness of your ESI collection by discovering gaps in metadata values, including date ranges, by generating communication maps to show the connections between custodians. They can also generate word clouds to show the language commonly used.
概念聚类：
可以提供关于材料内容类型和主题的宝贵概述，包括揭示预期内容的缺失或不必要内容的存在。
Concept clustering can provide a valuable overview of the content types and topics within your materials, including revealing an absence of things you expected or the presence of unnecessary things.
线程和重复项管理工具：
可以揭示需要进一步收集的缺失，或者显示存在过多的近似重复项，这表明收集或处理存在问题。
Thread and duplicate management tools can also reveal gaps requiring further collection, or they can reveal the presence of excessive near-duplicates, suggesting a collection or processing issue.
个人身份信息分析：
个人身份信息包括某人的姓名、社会安全号码、护照号码、驾驶执照号码、纳税人识别号、患者识别号、生物识别数据等。随着越来越多的隐私法律法规在各司法管辖区普及，保护个人身份信息变得愈发重要，因为它也出现在为诉讼和调查收集的电子存储信息中。
PII Analytics: Personally Identifiable Information (PII) includes someone’s name, social security number, passport number, driver’s license number, taxpayer identification number, patient identification number, biometric data, etc. As more privacy laws and regulations spread throughout jurisdictions, protecting PII is becoming all-the-more important, as it also appears in the ESI gathered for litigation and investigations.
个人身份信息分析工具：
旨在自动识别收集的电子存储信息中任何地方出现的某些类型的个人身份信息。这些工具可以通过以下两种方式工作：基于模式匹配运行，或基于算法或人工智能分析运行。
PII analytic tools are designed to automatically identify certain kinds of PII wherever it appears in the collected ESI. These tools can work in the two following ways: by operating based on pattern matching or they can operate based on algorithmic or AI analysis.
如果对于需要解决的保留和收集的适当范围存在争议，正式随机抽样会很有用。用于估计普遍性的抽样可用来确定不同来源和保管人的优先级，并估算与特定拟议工作相关的成本和收益。
Formal random sampling is useful if there are disputes over the appropriate scope of preservation and collection that need to be resolved. Sampling to estimate prevalence can be used to prioritize different sources and custodians and to estimate costs and benefits associated with specific proposed work.
进行审阅准备
Pursuing Review Prep
当您的首要任务是审阅规划和准备时，需要了解待审阅电子存储信息的属性和构成。这种理解可以为选择有效的筛选工具和技术以及选择有效的审阅方法提供信息。您可以利用以下技术：
When your top priority is review planning and preparation, you’ll need to understand the properties and composition of the ESI to be reviewed. That understanding can then inform the selection of effective tools and techniques for culling and the selection of effective methodologies for review. You can leverage the following techniques:
正式普遍性估算：
用于揭示关于文档集合的各种重要细节，包括存在多少相关、特权或敏感材料。利用这些信息，法律从业者可以有效地评估潜在的工作流程（包括技术辅助审阅和持续主动学习工作流），并准确估算所需的时间和成本。
Formal prevalence estimates work to reveal a variety of important details about a document collection, including how much relevant, privileged, or sensitive material is present. Leveraging this information, legal practitioners can effectively evaluate potential workflows, including TAR and CAL workflows, and can accurately estimate the time and costs required.
正式随机抽样：
可用于测试分类器，迭代改进将用于筛选的搜索，确保它们最大限度地减少不必要的下游审阅工作并避免遗漏任何重要材料。
Formal random sampling can be used to test classifiers, iteratively improving searches you will apply for culling, ensuring that they minimize unnecessary downstream review work and avoid missing any important materials.
搜索和元数据过滤：
可以在不损失不合理数量"小麦"的情况下消除大量"谷壳"，从而降低所有下游审阅和生成的成本。搜索和过滤工具，包括较新的可视化工具，可以查找特定材料，识别收集工作中的缺失，并在审阅前消除不相关材料。
Searching and metadata filtering can eliminate much of the chaff without losing an unreasonable amount of the wheat, reducing all downstream review and production costs. Search and filtering tools, including newer visualization tools find specific materials, identify gaps in your collection, eliminating irrelevant materials prior to review.
线程和重复项管理工具：
可以显著加快后续审阅工作，消除不需要审阅的材料并提供更好的组织性。
Thread and duplicate management tools can dramatically speed up later review work, eliminating materials not requiring review and providing superior organization.
语义索引功能：
提供概念聚类以组织和确定后续审阅活动的优先级，并提供分类功能以支持技术辅助审阅工作流。
Semantic indexing features offer concept clustering to organize and prioritize subsequent review activity and categorization to power TAR workflows.
生成式人工智能：
人工智能应用程序可以根据其对现有内容的理解决策生成新内容。现已创建的应用程序能够响应自然语言查询、起草自然语言回复、生成图像、生成音频和生成视频。大语言模型是一种生成式人工智能，它在海量文本集合（通常从互联网爬取）上进行训练，使生成式人工智能应用程序能够理解语法和句子结构，从而能够准确预测下一个最佳词集。
Generative AI: AI applications can generate new content based on their understanding of existing content. Applications have been created that can respond to natural language queries, draft natural language responses, generate images, generate audio, and generate video. Large language models are a kind of GenAI trained on enormous collections of text, often scraped from the Internet (LLMs allow generative AI applications to understand grammar and sentence structure, enabling them to predict the best next set of words accurately.
掌握早期案件情报
Mastering Early Case Intelligence
取证中的早期案件评估阶段已经演变，涵盖了三个相互关联但又 distinct 的"考古式"情报收集活动：传统的早期案件评估、早期数据评估和审阅准备。
The early case assessment phase of discovery has evolved, encompassing three connected-but-distinct “archaeological” intelligence gathering activities: traditional early case assessment, early data assessment, and review preparation.
为了进行这三项活动并实现其目标，从业者可以利用以下工具和技术：抽样；搜索和过滤；结构分析；概念分析；以及使用个人身份信息分析、实体提取、图像分析和生成式人工智能的新工具。
To pursue these three activities and their goals, practitioners can leverage the following tools and techniques: sampling; searching and filtering; structural analytics; conceptual analytics; and newer tools that use PII analytics, entity extraction, image analysis, and generative AI.
要成功实现您的电子存储信息目标，需要根据您寻求发现的内容以及您已有的了解程度，综合利用这些工具和技术。如需更多更深入洞察，请通过下方通讯方式联系我们。
Successfully achieving your ESI goals requires leveraging the right combination of these tools and techniques based on what you seek to find and how much you already know. For more in-depth insights, please contact us via the communication methods below.
更多业务咨询，请联系
斯振飞 Jeff Si
凯律电子证据开示公司中国区高级区域总监
Consilio LLC Senior Regional Director, China
jeff.si@consilio.com
+86 21 51166846 (点击拨打)
Consilio是全球eDiscovery（电子取证）、文件审查、灵活法律人才服务以及法律咨询和转型服务领域的领导者。通过其“Consilio Complete”能力组合，公司为跨国律师事务所和企业提供创新软件、成本高效的托管服务以及深厚的法律与合规行业专业知识。Consilio以其在诉讼、HSR第二请求、内部和监管调查、电子取证、文件审查、信息治理、合规风险评估、网络安全、法律部门管理以及合同管理方面的专业知识而闻名。其旗下的Lawyers On Demand部门还在法律人员配置与招聘领域表现出色。Consilio全球拥有行业顶尖的专业人才，在电子取证和风险管理生命周期的所有阶段，采用可审计的工作流程并运用专利及经过行业验证的技术。公司通过ISO/IEC 27001:2022认证，在欧洲、亚洲和北美设有办公室、文件审查和数据中心。
Consilio stands as the global leader in eDiscovery, document review, flexible legal talent, and legal advisory & transformation consulting services. With its Consilio Complete suite of capabilities, the company empowers multinational law firms and corporations using innovative software, cost-effective managed services, and deep legal and regulatory industry expertise. Renowned for its expertise in litigation, HSR second requests, internal and regulatory investigations, eDiscovery, document review, information governance, compliance risk assessments, cybersecurity, law department management, and contracts management, Consilio also excels in legal staffing and recruitment through its Lawyers On Demand division. Consilio globally employs leading professionals in the industry, applying defensible workflows with patented and industry-proven technology across all phases of the eDiscovery and risk management lifecycle. ISO\IEC 27001:2022 certified, the company operates offices, document review, and data centers across Europe, Asia, and North America.
