Next-Generation Discovery? HaystackID® Unveils HaystackID Discovery Intelligence

According to Hal Brooks, CEO of HaystackID, “HaystackID Discovery Intelligence encapsulates everything we do. It manifests what we have developed all along – a holistic approach to solving discovery challenges with a combination of AI, data science, machine learning, and our next-generation review capabilities.”

Considering Discovery Intelligence? HaystackID® and Next-Generation Discovery

According to the recent overview from HaystackID, by synergistically harnessing the potential of artificial intelligence, the precision of data science, the power of machine learning, and the practicality of expertly trained and managed reviewers, HaystackID Discovery Intelligence delivers insight and intelligence that allows you to reach decision points faster and more economically than previously possible.

Reducing Algorithmic Opacity: Technical Solutions for Understanding Systems and Outcomes

A significant factor in the adoption of algorithmic systems for decision-making is their capacity to process large amounts of varied data sets (i.e. big data), which can be paired with machine learning methods in order to infer statistical models directly from the data. The same properties of scale, complexity, and autonomous model inference however are linked to increasing concerns that many of these systems are opaque to the people affected by their use and lack clear explanations for the decisions they make.

Accountability and Artificial Intelligence? A Framework from the U.S. Government Accountability Office

This report from the US GAO describes an accountability framework for artificial intelligence (AI). The framework is organized around four complementary principles and describes key practices for federal agencies and other entities that are considering and implementing AI systems. Each practice includes a set of questions for entities, auditors, and third-party assessors to consider, along with audit procedures and types of evidence for auditors and third-party assessors to collect.

Considering Cyber Discovery? A Strategic Framework from HaystackID™

Developed based on the European Union Agency for Cybersecurity (ENISA) framework for artificial intelligence lifecycle stages and modified through the lens of the Electronic Discovery Reference Model (EDRM), the HaystackID Cyber Discovery Framework defines, depicts, and discusses a strategic framework that may be useful for understanding and applying the discipline of data and legal discovery in support of cybersecurity-centric challenges.

Defining Cyber Discovery? A Definition and Framework

Cyber Discovery can be defined as the application of a combination of data discovery and legal discovery approaches to enable the exploration of patterns, trends, and relationships within unstructured and structured data with the objective of uncovering insight and intelligence to proactively or reactively respond to cybersecurity-centric challenges. The presented definition and framework, based on high-level artificial intelligence lifecycle stages as developed by the European Union Agency for Cybersecurity (ENISA) and modified through the lens of traditional eDiscovery planning and practices grounded within the Electronic Discovery Reference Model (EDRM), represents one potential methodology for describing and framing the stages and tasks of cyber discovery.

Reinventing Enterprise Search? AWS Announces Amazon Kendra

Amazon Kendra is a highly accurate and easy to use enterprise search service that’s powered by machine learning. Kendra delivers powerful natural language search capabilities to websites and applications so end users can more easily find the information they need within the vast amount of content spread across their company.

Unprovability Comes to Machine Learning

Machine learning has matured as a mathematical discipline and now joins the many subfields of mathematics that deal with the burden of unprovability and the unease that comes with it. Perhaps results such as this one will bring to the field of machine learning a healthy dose of humility, even as machine-learning algorithms continue to revolutionize the world around us.

From Russia (and China) with Love? The UK National Cyber Security Centre Annual Review

According to the NCSC Annual Review, China remained a highly sophisticated...

New Federal Government Cybersecurity Incident and Vulnerability Response Playbooks

According to Matt Hartman, Deputy Executive Assistant Director for Cybersecurity, "The...

A Surge in Cybercriminality? The Annual ENISA Threat Landscape Report – 9th Edition

According to EU Agency for Cybersecurity Executive Director Juhan Lepassaar, “Given...

Considering Zero Trust? November 2021 Cyber Events Report from NATO CCDCOE

Computer security professionals love to say that there is no such...

Epiq Acquires Simplex

According to the release, the acquisition will increase the overall scale...

A Long Runway? KLDiscovery Files for Initial Public Offering

On Tuesday, November 23, 2021, KLDiscovery took a strong step toward...

Modus Secures Working Capital Facility from J.P. Morgan

According to Steven Horan, Chairman, and CEO of Modus, “Having the...

Driven and Innovative Discovery Merge

According to the announcement, Silver Oak Services Partners, a private equity...

An eDiscovery Market Size Mashup: 2021-2026 Worldwide Software and Services Overview

From market retraction in 2020 to resurgence in 2021, the worldwide...

A New Era in eDiscovery? Framing Market Growth Through the Lens of Six Eras

There are many excellent resources for considering chronological and historiographical approaches...

An eDiscovery Market Size Mashup: 2020-2025 Worldwide Software and Services Overview

While the Compound Annual Growth Rate (CAGR) for worldwide eDiscovery software...

Resetting the Baseline? eDiscovery Market Size Adjustments for 2020

An unanticipated pandemeconomic-driven retraction in eDiscovery spending during 2020 has resulted...

Five Great Reads on Cyber, Data, and Legal Discovery for November 2021

From worldwide eDiscovery market sizing and discovery intelligence to cybersecurity playbooks...

Five Great Reads on Cyber, Data, and Legal Discovery for October 2021

From artificial intelligence and predictive coding to eDiscovery business confidence and...

Five Great Reads on Cyber, Data, and Legal Discovery for September 2021

From countering ransomware to predictive coding and packaged services, the September...

Five Great Reads on Cyber, Data, and Legal Discovery for August 2021

From the interplay of digital forensics in eDiscovery to collecting online...

Alternative Reality? Winter 2022 eDiscovery Pricing Survey Results

Based on the complexity of data and legal discovery, it is...

Calm Before the Storm? Eighteen Observations on eDiscovery Business Confidence in the Fall of 2021

In the fall of 2021, 71.2% of survey respondents felt that...

Help Wanted? Issues Impacting eDiscovery Business Performance: A Fall 2021 Overview

In the fall of 2021, 27.4% of respondents viewed lack of...

Harvest Time? eDiscovery Operational Metrics in the Fall of 2021

In the fall of 2021, 67 eDiscovery Business Confidence Survey participants...