Learning and Exposure Affect Environmental Perception Less than Evolutionary Navigation Costs

Russell E. Jackson is with University of Idaho, Chéla R. Willey is with University of California Los Angeles, Lawrence K. Cormack is with UT Austin.Most behaviors are conditional upon successful navigation of the environment, which depends upon distance perception learned over repeated trials. Unfortunately, we understand little about how learning affects distance perception–especially in the most common human navigational scenario, that of adult navigation in familiar environments. Further, dominant theories predict mutually exclusive effects of learning on distance perception, especially when the risks or costs of navigation differ. We tested these competing predictions in four experiments in which we also presented evolutionarily relevant navigation costs. Methods included within- and between-subjects comparisons and longitudinal designs in laboratory and real-world settings. Data suggested that adult distance estimation rapidly reflects evolutionarily relevant navigation costs and repeated exposure does little to change this. Human distance perception may have evolved to reflect navigation costs quickly and reliably in order to provide a stable signal to other behaviors and with little regard for objective accuracy.Psycholog

Inconsistent Responsiveness Determination in Document Review: Difference of Opinion or Human Error?

This Article analyzes the inconsistency between different document review efforts on the same document collection to determine whether that inconsistency is due primarily to ambiguity in applying the definition of responsiveness to particular documents, or due primarily to human error. By examining documents from the TREC 2009 Legal Track, the Authors show that inconsistent assessments regarding the same documents are due in large part to human error. Therefore, the quality of a review effort is not simply a matter of opinion; it is possible to show objectively that some reviews, and some review methods, are better than others

Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review

E-discovery processes that use automated tools to prioritize and select documents for review are typically regarded as potential cost-savers – but inferior alternatives – to exhaustive manual review, in which a cadre of reviewers assesses every document for responsiveness to a production request, and for privilege. This Article offers evidence that such technology-assisted processes, while indeed more efficient, can also yield results superior to those of exhaustive manual review, as measured by recall and precision, as well as F1, a summary measure combining both recall and precision. The evidence derives from an analysis of data collected from the TREC 2009 Legal Track Interactive Task, and shows that, at TREC 2009, technology-assisted review processes enabled two participating teams to achieve results superior to those that could have been achieved through a manual review of the entire document collection by the official TREC assessors

Artificial Intelligence as Evidence

This article explores issues that govern the admissibility of Artificial Intelligence (“AI”) applications in civil and criminal cases, from the perspective of a federal trial judge and two computer scientists, one of whom also is an experienced attorney. It provides a detailed yet intelligible discussion of what AI is and how it works, a history of its development, and a description of the wide variety of functions that it is designed to accomplish, stressing that AI applications are ubiquitous, both in the private and public sectors. Applications today include: health care, education, employment-related decision-making, finance, law enforcement, and the legal profession. The article underscores the importance of determining the validity of an AI application (i.e., how accurately the AI measures, classifies, or predicts what it is designed to), as well as its reliability (i.e., the consistency with which the AI produces accurate results when applied to the same or substantially similar circumstances), in deciding whether it should be admitted into evidence in civil and criminal cases. The article further discusses factors that can affect the validity and reliability of AI evidence, including bias of various types, “function creep,” lack of transparency and explainability, and the sufficiency of the objective testing of AI applications before they are released for public use. The article next provides an in-depth discussion of the evidentiary principles that govern whether AI evidence should be admitted in court cases, a topic which, at present, is not the subject of comprehensive analysis in decisional law. The focus of this discussion is on providing a step-by-step analysis of the most important issues, and the factors that affect decisions on whether to admit AI evidence. Finally, the article concludes with a discussion of practical suggestions intended to assist lawyers and judges as they are called upon to introduce, object to, or decide on whether to admit AI evidence

Hypercrosslinked materials

This chapter describes the chemistry of hypercrosslinked materials, and presents a description of their synthesis, defining physico-chemical features and their most important applications. The synthesis section will examine the different monomers, precursor polymers, reagents and synthetic strategies used to prepare hypercrosslinked materials. Each synthesis section also details the chemical and morphological properties of the hypercrosslinked materials and the main field of application

Hypercrosslinked materials : preparation, characterisation and applications

This review article provides an overview of hypercrosslinking technology. In particular, it covers the preparation and characterisation of hypercrosslinked materials and their applications. The synthesis section examines the different monomers, precursor polymers and reagents used to prepare hypercrosslinked materials, but also the different synthetic approaches disclosed in the literature. The various chemical modification reactions relevant to this area are also reviewed. Several examples of applications for hypercrosslinked materials are described; these applications are grouped into thematic areas such as chromatography, gas storage and the trapping of organic contaminants

Fermi Surface as the Driving Mechanism for Helical Antiferromagnetic Ordering in Gd-Y Alloys

The first direct experimental evidence for the Fermi surface (FS) driving the helical antiferromagnetic ordering in a gadolinium-yttrium alloy is reported. The presence of a FS sheet capable of nesting is revealed, and the nesting vector associated with the sheet is found to be in excellent agreement with the periodicity of the helical ordering.Comment: 4 pages, 4 figure