Automated legal sensemaking: the centrality of relevance and intentionality

Introduction: In a perfect world, discovery would ideally be conducted by the senior litigator who is responsible for developing and fully understanding all nuances of their client’s legal strategy. Of course today we must deal with the explosion of electronically stored information (ESI) that never is less than tens-of-thousands of documents in small cases and now increasingly involves multi-million-document populations for internal corporate investigations and litigations. Therefore scalable processes and technologies are required as a substitute for the authority’s judgment. The approaches taken have typically either substituted large teams of surrogate human reviewers using vastly simplified issue coding reference materials or employed increasingly sophisticated computational resources with little focus on quality metrics to insure retrieval consistent with the legal goal. What is required is a system (people, process, and technology) that replicates and automates the senior litigator’s human judgment. In this paper we utilize 15 years of sensemaking research to establish the minimum acceptable basis for conducting a document review that meets the needs of a legal proceeding. There is no substitute for a rigorous characterization of the explicit and tacit goals of the senior litigator. Once a process has been established for capturing the authority’s relevance criteria, we argue that literal translation of requirements into technical specifications does not properly account for the activities or states-of-affairs of interest. Having only a data warehouse of written records, it is also necessary to discover the intentions of actors involved in textual communications. We present quantitative results for a process and technology approach that automates effective legal sensemaking

Strange bedfellows? Keyword and conceptual search unite to make sense of relevant ESI in electronic discovery

In the brief history of electronic discovery, the latter part of the twentieth century witnessed the demise of paper by a digital hero that emancipated the content of paper documents with OCR and TIFF. This technology added a third dimension to the realm of 2D paper document review and production that lead to a sea change in discovery methods. By many accounts what we have before us is a three-stage evolution from paper to digital to clustering in order to overcome the problems of volume and complexity of ESI. The intent of this position paper is to describe the development of the digital hero and methodology that is emancipating the content and context of ESI – conceptual search that spans file formats, languages and technique, and includes keyword search on a common, shared index

Blended automation: integrating algorithms on the floor of the New York Stock Exchange

The recent automation of the American stock market has replaced floor intermediaries with trading algorithms, calling into question the sociological claim that markets are structured by networks of intermediaries. Our study examines the social nature of markets in automated settings with an inductive, qualitative study of the automation of the NYSE during the period 2003-12. It proposes the concept of blended automation to denote an automation design that preserves the social structure of a market. Our analysis of the Flash Crash of 2010 suggests that such design offers greater resilience to economic shocks. Our study contributes to the literature on technology in organizations by characterizing a novel automation design that reconciles technology with social relations, and contributes to economic sociology by outlining how automated markets can remain socially structured, pointing to role of politics, ideology and design in market automation

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

Understanding “influence”: An exploratory study of academics’ process of knowledge construction through iterative and interactive information seeking

The motivation for this study is to better understand the searching and sensemaking processes undertaken to solve exploratory tasks for which people lack pre-existing frames. To investigate people’s strategies for that type of task, we focused on “influence” tasks because, although they appear to be unfamiliar, they arise in much academic discourse, at least tacitly. This qualitative study reports the process undertaken by academics of different levels of seniority to complete exploratory search tasks that involved identifying influential members of their academic community and “rising stars, ” and to identify similar roles in an unfamiliar academic community. 11 think-aloud sessions followed by semi-structured interviews were conducted to investigate the role of specific and general domain expertise in the process of information seeking and knowledge construction. Academics defined and completed the task through an iterative and interactive process of seeking and sensemaking, during which they constructed an understanding of their communities and determined qualities of “being influential”. Elements of the Data/Frame Theory of Sensemaking (Klein et al., 2007) were used as sensitising theoretical constructs. The study shows that both external and internal knowledge resources are essential to define a starting point or frame, make and support decisions, and experience satisfaction. Ill-defined or non-existent initial frames may cause unsubstantial or arbitrary decisions, and feelings of uncertainty and lack of confidence

Improving the cost structure of sensemaking: analysing user concepts to inform information systems design

n many everyday contexts people interact with information systems in order to make sense of a domain of interest. However, what this means and how it can best be supported are poorly understood. In particular, there has been little research on how to develop system representations that simplify naturally occurring sense making processes by matching people’s conceptualizations of the domain. In this paper we draw on Klein et al.’s data-frame theory and Russell at al’s notion of cost-structures in sensemaking to propose an approach to understanding sensemaking that supports reasoning about system requirements. The two key elements of the approach are the identification of the process and the transformational steps within that process that could benefit from support to reduce costs, and the identification of primary concepts which are cued by information in the context of a given sensemaking task and domain, and around which users integrate information to form a structured understanding. Our general principle is that by understanding a sensemaking transformation in terms of its source data and the integrating structures it creates, one is better able to anticipate the evolving information needs that it tends to invoke. We test this approach with a case study of fraud investigation performed by a team of lawyers and forensic accountants and consider how to support the elaboration of prototypical user-frames once they have been invoked

Making sense of blockchain technology: How will it transform supply chains?

This research uses sensemaking theory to explore how emerging blockchain technology may transform supply chains. We investigate three research questions (RQs): What are blockchain technology’s perceived benefits to supply chains, where are disruptions mostly likely to occur and what are the potential challenges to further blockchain diffusion? We conducted in-depth interviews with 14 supply chain experts. Cognitive mapping and narrative analysis were deployed as the two main data analysis techniques to aid our understanding and evaluation of people’s cognitive complexity in making sense of blockchain technology. We found that individual experts developed different cognitive structures within their own sensemaking processes. After merging individual cognitive maps into a strategic map, we identified several themes and central concepts that then allowed us to explore potential answers to the three RQs. Our study is among the very few to date to explicitly explore how blockchains may transform supply chain practices. Using the sensemaking approach afforded a deeper understanding of how senior executives diagnose the symptoms evident from blockchains and develop assumptions, expectations and knowledge of the technology, which will then shape their future actions regarding its utilisation. We demonstrate the usefulness of sensemaking theory as an alternative lens in investigating contemporary supply chain phenomena such as blockchains. Bringing sensemaking theory to this discipline in particular enriches emerging behavioural operations research. Our contributions also lie in extending the theories of prospective sensemaking and adding further insights to the stream of technology adoption studies