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    Beginning in early 2012 the topic of Technology-Assisted Review began the gradual move from expert-led explanations to mainstream mentions in eDiscovery articles, opinions, surveys and reports.  ComplexDiscovery has tracked many of these explanations and mentions as part of its daily eDiscovery coverage on Twitter via @ComplexD and weekly eDiscovery coverage as part of Weekly eDiscovery Top Story Digest newsletter updates.  Provided below for your research, review and consideration are a compilation of key headlines and links from online sources on the topic of Technology-Assisted Review from February 2012 (LegalTech New York 2012) until February 2014 (LegalTech New York 2014).

    February 2, 2014

    Technology-Assisted Review Related Articles/Posts

    JANUARY 2014

    • Scientific Proof of Law’s Overreliance On Reason: The “Reasonable Man” is Dead – Part 1 –; Part 2 –; Part 3 – (Ralph Losey)
    • How Technology-Assisted Review Is Redefining Lawyers’ Ethical Obligations - (Gabriela Baron)
    • Vendor Voice: 5 Myths About Technology-Assisted Review – (John Tredennick)
    • Is Predictive Coding Overriding Lawyers? (Bill Dimm)
    • Big Data Law And Hybrid Analytics In The Second Machine Age – (Michael Prounis)
    • Technology: The Role of Probability & Certainty in Developing Document Review Strategies – (Andy Kraftsow)
    • Understanding Statistical Sampling, Statistics in eDiscovery – (Maureen O’Neill)
    • As Predictive Coding Goes Mainstream, Practitioners Grapple with When and How to Use It - (ACEDS)
    • Vendor Voice: The Schlemiel and the Schlimazel and the Psychology of Reasonableness – (Herbert Roitblat)
    • “Do You Have to Share and Share Alike With Technology-Assisted Review?” (Stuart LaRosa)
    • Keyword Filtering Prior To Predictive Coding Deemed Reasonable – (All Voices)
    • Rethinking Negotiating Strategies for Predictive Coding – (Ali Waheed)

    DECEMBER 2013

    • Use Predictive Coding As an Information Governance Tool – (Rebecca Shwayri)
    • Technology: What’s Next for Predictive Coding – (Drew Lewis)
    • The Rise of Predictive Coding for Pharmaceutical Companies – (Jessica Kykora)
    • Rise Of The Machines: Technology-Assisted Coding In The ESI Age – (Robert Burns, Benjamin Wilson)
    • Bingham eDiscovery News – Winter 2013 (PDF) – (Bingham)
    • In Re: Biomet Order Addresses Hot Button Predictive Coding Issue – (Matt Nelson)
    • In Re: Biomet M2A – Info and Orders – (Northern District of Indiana – United States District Court)
    • Predictive Coding and Proportionality: A Marriage Made In Heaven – (Ralph Losey)
    • Predictive Coding: Making It Work – (Barclay Blair)
    • Predictive Coding: Revolutionary or a Fading Trend? (Joseph Fantani)
    • In the World of Big Data, Human Judgment Comes Second, The Algorithm Rules – (John Tredennick)
    • State Court Judges’ Perspective on E-Discovery – (Sharon Nelson, John Simek)
    • Less Is More: When It Comes to Predictive Coding Training, “Fewer Reviewers the Better” Part Three – (Ralph Losey)
    •  Is Random the Best Road for CAR? Or is there a Better Route to Your Destination? (John Tredennick)
    • Judge Grimm’s Revised Discovery Order Expands Definition of Proportionality, Includes TAR – (Brittany Kauffman)
    • Are SMEs Really Required for TAR Training? (A Follow-Up on TAR 2.0 Experts vs. Review Teams) (John Tredennick)
    • Why Search Terms Are Worthy of Court’s Protection – (Christopher Boehning, Daniel Toal)
    • Less Is More: When it Comes to Predictive Coding Training, the “Fewer Reviewers the Better” – Part Two – (Ralph Losey)

    NOVEMBER 2013

    • Why Litigators Need to Learn Statistics (Statistical Sampling) – (Maureen O’Neill)
    • Data Analytics Steal the Show at DC Technology in the Law Symposium – (Sandra Serkes)
    • A Systems Approach to E-Discovery – (Herb Roitblat)
    • The Impact of IBM’s Watson on eDiscovery – (Ron Friedmann)
    • Your Lawyer is a Robot – The Globe and Mail – (Shelley White)
    • Blending Early Data Assessment and Predictive Coding for More Effective E-discovery – (LegalTalk Network)
    • The Implications Of Rule 26(g) On The Use Of Technology-Assisted Review –  (PDF) (Karl Schieneman, Thomas Gricks)
    • Less Is More: When it Comes to Predictive Coding Training, Fewer Reviewers the Better – (Ralph Losey)
    • How Document Viewing is Key to Effective eDiscovery in the Legal Market – Innovation Insights – (Ned Averill-Snell)
    • Q&A: Evolution of Predictive Coding Technology in Information Governance – (Ben Cole)
    • EDI-Oracle Study: Humans Are Still Essential in eDiscovery – (Monica Bay)
    • IBM Preps Artificial Intelligence in Cloud, and eDiscovery asks “Can We Have a Bite?” (Gregory Bufithis)
    • Using Technology Assisted Review in the Right Cases and in the Right Way – (John Eustice)
    • Subject Matter Experts: What Role Should They Play in TAR 2.0 Training? (J. Tredennick)
    • Legal Search Science – (Ralph Losey)
    • The Effectiveness of Technology Assisted Review – FindLaw – (Caitlin Murphy)
    • Tolson’s Three Laws of Machine Learning | eDiscovery101 – (Bill Tolson)
    • Technology: Predictive Coding and Total Time & Cost to ECA – (Bill Tolson)
    • Risk Sampling: The Key to a Successful Audit and Monitoring Program – (Mike Volkov)

    OCTOBER 2013

    • Is TAR Fight For Your Next Case? – (David Carns)
    • Slides from ‘TAR for the Real World: Practical Problems, Pragmatic Solutions’ – (@BobAmbrogi)
    • Three Online On-Demand Webinars on Computer-Assisted Review – (@OrcaTec)
    • Technology Assisted Review in the Age of Big Data – (@TheLawyerMag)
    • Discovery Evolutions Hold Promise for Greater Privacy Benefits for Litigants – (Lawrence Lynch)
    • Predictive Coding: Embracing the New – Law Society Gazette – (Costa Kypre)
    • Technology-Assisted Review: What You Need to Know – YouTube – (Law Practice Tips)
    • IT-Lex Conference: Predicting the Future of Predictive Coding – (Victor Li)
    • Predictive Coding in the Cyber Underbelly: Trawling the “Dark Markets” – Britton)
    • Is Technology-Assisted Review Creating More Transparency? | Xerox E-Discovery Talk – (Stuart La Rosa)
    • My Basic Plan for Document Reviews: The “Bottom Line Driven” Approach – Part Four – (@RalphLosey)
    • Technology Assisted Review Isn’t Perfect, but It’s Here to Stay – (Victor Li)
    • My Basic Plan for Document Reviews: The “Bottom Line Driven” Approach – Part Three – (@RalphLosey)
    • Da Silva Moore: Plaintiffs’ Petition for Writ of Certiorari on Question of Recusal Denied – (K&L Gates)
    • My Basic Plan for Document Reviews: The “Bottom Line Driven” Approach – Part Two – (@RalphLosey)
    • An Update: Peck, Parties and Predictive Coding – (@ComplexD)
    • Party Ordered to Disclose Where and How It Searched for ESI – (@RalphLosey)

    SEPTEMBER 2013

    • My Basic Plan for Document Reviews: The “Bottom Line Driven” Approach – Part One – (Ralph Losey)
    • Emerging Predictive Coding Case Law – Nine Summaries of Early Case Law on Computer-Assisted Review – (Michael Pitch)
    • EDRM’s Computer Assisted Review Reference Model:  Beyond the Test Drive – on Livestream (@OrcaTec)
    • Predictive Coding and eDiscovery in 2015 and Beyond – Presentation from LTNY 2013 – (Daniel Martin Katz)
    • Technology Assisted Review:  What Does TAR Really Mean – (Cynthia Courtney)
    • Information Governance: Technology Assisted Review (Or, Why You Need to Know About Zorfblatt) (Chris Surdak)
    • New Software Helps Lawyers Accomplish the ‘Impossible’ | VentureBeat –  (Christina Farr)
    • “District Court Upholds Use of Multimodal Assisted Review in Biomet Case” – (Deloitte)
    • Internal Investigations: The Gateway to Advanced Discovery Techniques – (Drew Lewis)
    • Relevancy Ranking in Predictive Coding – See Comment Section Consideration From Industry Expert – (Herb Roitblat)
    • Successful Predictive Coding In An Unfamiliar Linguistic Landscape – (Bret Burney)
    • Update: A Predictive Coding One-Question Provider Implementation Survey – (@ComplexD)
    • It’s the Math, Stupid! – Metrics, Measurements and Methodology in TAR – (Kris Vann)
    • 9 Ways to Reduce eDiscovery Costs – (Matthew Bills)
    • Judge Says “Dude, Where’s Your CAR?” – eDiscovery Case Law – (Doug Austin)
    • Predictive Coding: Insights from Federation of Defense and Corporate Counsel (FDCC) Annual Meeting – (Wystan Ackerman)
    • When eDiscovery Meets Big Data, Can Case Analytics Be Far Behind? (Dera Nevin)
    • Poor Plaintiff’s Counsel, Can’t Even Find a CAR, Much Less Drive One – (@RalphLosey)

    AUGUST 2013

    • Everything You Wanted to Know about Technology Assisted Review – eDiscovery Trends – (Doug Austin)
    • Does Technology-Assisted Review Help in Reviewing Productions? – (John Tradennick)
    • An Update: Peck, Parties and Predictive Coding – (@ComplexD)
    • ‘Da Silva Moore’: Judge Peck Urges Rejection of 3rd Complaint Re-do – (Monica Bay)
    • Handle Technology-Assisted Review With Care – (Gabriela Baron, Amanda Jones)
    • Introduction to Predictive Coding (PDF) (Herb Roitblat)
    • Predictive Coding’s Murky Waters; Ruling in In re Biomet Stirs Interesting Debate – (Christopher Yoshida)
    • Relevancy Ranking is the Key Feature of Predictive Coding Software  – (Ralph Losey)
    • Technology-Assisted Review: An Integral E-Discovery Tool | The Metropolitan Corporate Counsel – (Jon Lavinder)
    • There’s More to TAR Than Litigation – (Laura Kibbe)
    • eDiscovery: The Value of Predictive Coding in Internal Investigations – Nadel, Daniel McGuire, Erica Wenniger)
    • Why a Receiving Party Would Want to Use Predictive Coding? (Ralph Losey)
    • Technology-Assisted Review: The Role of Artificial Intelligence (PDF) – (Bobby Basile)
    • Of Production, Privilege, and Petabytes: Evolving Possibilities of TAR – (Kimberly Johnson)
    • Recent Cases Show Predictive Coding Hasn’t Entirely Replaced Earlier Technology – (Micheal Kozubek)
    • $3.1 Million #eDiscovery Vendor Fee Was Reasonable in a $30 Million Case – (Ralph Losey)
    • Measurement in eDiscovery – A Technical White Paper (PDF) (Herb Roitblat)

    JULY 2013

    • 5 Reasons In-House Counsel are Reluctant to Make the Predictive Coding Leap – (Joshua Rogaczewski, Yodi Hailemariam)
    • Predictable? — DOJ Approves Use of Predictive Coding in AB InBev-Grupo Modelo Merger Investigation – (Robert Brown)
    • Gordon v Kaleida: Plaintiff & Defendant Have Same Consultant – (Miro Casstta)
    • Can an E-Discovery Vendor Serve Two Masters? (Chris O’Brien)
    • Is Technology Assisted Review the Holy Grail of eDiscovery? (Tom Turner)
    • Update: Predictive Coding One-Question Provider Survey – From Active Learning To Support Vector Machine – (@ComplexD)
    • Further Adventures in Predictive Coding – (Herbert Roitblat)
    • The DESI V Workshop on Predictive Coding, Machine Learning, and eDiscovery Review (With Video) – (Greg Bufithis)
    • Is it OK for an eDiscovery Vendor to Work on Both Sides of a Case? – eDiscovery Best Practices – (Doug Austin)
    • Conor Crowley Updates Latest eDiscovery Trends – (Victor Li)
    • The Da Silva Moore Sideshow Seeks The Big Stage | Discovery Advocate – (Jonathan Forman)
    • Motion for Class Certification Filed in ‘Da Silva Moore’ Despite EDD Limits – (Victor Li)
    • An Update: Peck, Parties and Predictive Coding – (@ComplexD)
    • Predictive Coding, Pizza, and Presentations at the DESI V Workshop – (Jason Baron)
    • Da Silva Moore: Plaintiffs Petition for Writ of Certiorari on Question of Recusal – (K&L Gates)
    • Da Silva Moore Plaintiffs File SCOTUS Certiorari Petition | IT-Lex – (Samir Mathur)
    • None of Your Beeswax! (Or, Do I Have to Invite Opposing Counsel to my Predictive Ranking Party?) (John Tredennick)
    • ‘Da Silva Moore’ Goes to Washington – (Victor Li)
    • What We Talk About When We Talk About TAR – (Cynthia Courtney)
    • Does Bad OCR Make for Good TAR? (John Tredennick)
    • Analytics vs. Technology Assisted Review (TAR) – (Gianni Maiorano)
    • McDermott and DOJ Embrace Predictive Coding – (Geoffrey Vance, Alison Silverstein)
    • Judicial Acceptance of Predictive Coding Highlights Need for Counsel to Consider Its Use – (Akiva Cohen)
    • Predictive Coding Cooperation Experiment Gets Contentious – (Karl Schieneman)
    • Predictive Coding & The “Risk-Averse” Attorney: Top 3 eDiscovery & Compliance Use Cases (Part 2) – (Matthew Nelson)
    • Put Predictive Coding to Work to Save e-Discovery Costs (PDF) (Charles Schwartz, Daniel Bolia)
    • Information Discovery: Adventures in Predictive Coding – (Herbert Roitblat)
    • Predictive Coding, Storytelling and God: Narrative Understanding in e-Discovery – (Lawrence Chapin, Simon Attfield, Efe Okoro)

    JUNE 2013

    • Predictive Coding: Debunking a Sample of Myths about Random Sampling – (Herbert Roitblat)
    • The State of the Law on Predictive Coding – (Joe Skalski)
    • DOJ Approves Use of Predictive Coding in a Proposed Merger Document Review – (Julia Romero Peter)
    • Should Predictive Coding Protocols Come with Measures of Content Diversity – (Gerard Britton)
    • Predictive Coding:  The ‘Not Me’ Factor | Ball in Your Court – (Craig Ball)
    • Comparative Efficacy of Two Predictive Coding Reviews of 699,082 Enron Documents – (@RalphLosey)
    • Another Federal Court Considers Predictive Coding – (Joey Chindamo)
    • Motion to Compel Dismissed after Defendant Agrees to Conditional Meet and Confer – eDiscovery Case Law (Doug Austin)
    • Predictive Coding has its Detractors – (Richard Weiner)
    • Using Predictive Coding “Might” Require Negotiation between the Parties Involved – (Mike Hamilton)
    • Predictive Coding and Scientific Research – eDiscovery Law Today – (Ralph Losey)
    • Top 5 eDiscovery Risks for 2013 – (Mike Warnecke)
    • Predictive Coding at DESI V, the Oracle-EDI Study and Other TAR Sources – (@ChrisDaleOxford)
    • Technology Assisted Review Case Summary: In re Biomet – (Julie Romero Peter)
    • A Modest Contribution to the Science of Search: Report and Analysis of Inconsistent Classifications in Two Predictive Coding Reviews of 699,082 Enron Documents – (@RalphLosey)
    • Roitblat: Debunking a Sample of Myths about Random Sampling in Predictive Coding (PDF) (Herb Roitblat)
    • Is E-Discovery Due Process Argument Just Predictive Coding in Hiding? (Ron Friedmann)
    • Court’s Suggestion to Use Predictive Coding Leads to Dispute over Cooperation – (@BobAmbrogi)
    • ICAIL 2013 Papers On Standards for Advanced Search and Review Methods – (ICAIL 2013)
    • Opinion Highlights Questions Surrounding Proper Predictive Coding Protocols – Electronic Discovery Law – (K&L Gates)
    • Guest Blog: Quick Peek at the Math Behind the Black Box of Predictive Coding- (Jason Baron)
    • A Tutorial on Sampling in Predictive Coding (PDF) – (Herbert Roitblat)

    MAY 2013

    APRIL 2013

    • DUKE Conference on TAR – The Experts Convene – (Karl Schieneman)
    • CARRM: The Future of Computer Assisted Review – Legal Talk Network – (George Socha, Tom Palladino, Michele Lange)
    • Biomet: Lies, Damn Lies… and Economics Behind Predictive Coding Disputes (Entrepreneurs Take Note) (Gerard Britton)
    • What We Talk About When We Talk About TAR – (Cynthia Courtney (@LegalIT)
    • Making Sure Your Predictive Coding Solution Doesn’t Cost More… – (Matt Miller)
    • There’s No Need to Redo a Reasonable Technology-Assisted Review Process – (Stuart LaRosa)
    • In Praise of Proportionality: Judge OKs Predictive Coding After Keyword Search – (Bob Ambrogi)
    • Plaintiffs’ Objections to Defendant’s Use of Keyword Search before Predictive Coding Rejected – eDiscovery Case Law – (Doug Austin)
    • Deploying Trainers in Technology-assisted Review (TAR) (Jen Wightman)
    • Predictive Coding’s Erroneous Zones Are Emerging Junk Science – (Bill Speros)
    • The Next Step for Technology-Assisted Review: Unlocking the Black Box – (Randall Burrows)
    • Reasonable vs. Near Perfection: Court Rules for Tiered Predictive Coding Approach – (Mike Hamilton)
    • In re Biomet: 2 x 2 = 5? (@ITLexOrg)
    • In re: Biomet – Doing the Math on Court Approved Multimodal Review – (@ITLexOrg)
    • Proportionality and Predictive Coding: A Hip Combination | Discovery Advocate – (Karin Scholz Jensen)
    • Federal Court Authorizes Predictive Coding in Multi-District Prior to Centralization Order – (Bingham Greenebaum Doll)
    • Technology-Assisted Review and Biomet: Approaches And Critiques – (@ComplexD)
    • What Is The Maximum Recall In Re Biomet? (William Webber)
    • Indiana Federal Court OKs Jump-Start on Predictive Coding – (Monica Bay)
    • Proportionality: Court Declines to Require Defendant to Redo Discovery Utilizing Only Predictive Coding – (K&L Gates)
    • The “Sedona Bubble” and the Top 3 TAR Trends of 2013 – (Matthew Nelson)
    • In re: Biomet – Doing the Math on Court Approved Multimodal Review – (@ITLexOrg)
    • Reinventing the Wheel: My Discovery of Scientific Support for “Hybrid Multimodal” Search – (@RalphLosey)
    • Math and Statistics for Lawyers When Using Technology-Assisted Review – (Eric Robinson)
    • Borg Challenge: The Complete Report – (@RalphLosey)
    • $2.8 Million Award for Predictive Coding Expenses in a Trade Secret Case | E-Discovery Law Today (Ralph Losey)
    • Video:  Borg Challenge: Part Five Where I Summarize My Findings – (@RalphLosey)
    • Appeals Court Upholds Decision Not to Recuse Judge Peck in Da Silva Moore – eDiscovery Case Law – (Doug Austin)
    • An Update: Peck, Parties and Predictive Coding – (@ComplexD)
    • Da Silva Moore: Second Circuit Denies Petition for Writ of Mandamus Compelling Recusal of Judge Peck – (K&L Gates)
    • Judge Peck’s Refuse to Recuse in ‘Da Silva Moore’ Remains After Appeal – (Monica Bay)
    • Is Predictive Coding the Answer to Reducing the Costs of eDisclosure? The Lawyer – (James Kent)
    • Second Circuit Vindicates Judge Peck and Judge Carter in Da Silva Moore –
    • Mandating Use of Predictive Coding in Electronic Discovery: An Ill-Advised Judicial Intrusion – (Tonia Murphy)
    • Evolving Judicial Attitudes Towards Predictive Coding Suggest It May Be Time To Retire The Defensibility Question – (Akiva Cohen)
    • Video: How Good Is Your Predictive Coding Poker Face? (Part Two) – (Matthew Nelson)
    • Borg Challenge: Part One of My Experimental Review of 699,082 Enron Docs
    • Predictions on Predictive Coding – (Robert Byman)
    • Sampling and eDiscovery with Herb Roitblat (Series of Posts) – (@OrangeLT)
    • How Good Is Your Predictive Coding Poker Face? (Video Series – Part One) (Matthew Nelson)

    MARCH 2013 

    FEBRUARY 2013 

    • Avoiding Risk – Get Your Client to “Buy-In” to Predictive Coding – (Peter Buckley)
    • Use of Predictive Coding in Regulatory Enforcement Proceedings – Bloomberg Law – (Jennifer Kennedy)
    • Use of Technology-Assisted Review and Costs-Shifting in US Patent Case has UK Parallels – (Chris Dale)
    • Must Losing Plaintiff Pay Defendant $2.8M for Predictive Coding of One Million Docs? Court Says Yes – (Doug Austin)
    • Predictive Coding Helps Companies Reduce eDiscovery Costs – (Bob Ambrogi)
    • To “What Are Best Practices?” In 12 Months – (Warwick Sharp, Jay Leib, Tom Groom)
    • Predictive Coding: What It Is And What You Need To Know About It – Aguiar, Jonathan Friedman)
    • Considering Machine Learning: Three References – (@ComplexD)
    • Technology-Assisted Review Models: Let’s Move Forward – (Jen Wightman)
    • Podcast:  Predictive Coding: Grossman-Cormack Glossary of Technology-Assisted Review – (Karl Schieneman)
    • Shifting eDiscovery Fees, Judge Orders Patent Case Loser to Pay $2.8M Predictive Coding Tab – (Robert Hilson)
    • Predicting Discovery? Initial Results of 120-Second Provider Predictive Coding Survey – (@ComplexD)
    • Technology Assisted Review is NOT New … Just Improved – (Kevin Leser)
    • Focusing on Substance over Mathematics in a Predictive Coding Workflow –  (Erik Post, Jim Vint)
    • Over $12 Million in Attorney Fees Awarded in Patent Case Involving Predictive Coding – (Matthew Nelson)
    • Hasten Slowly | Millnet – (Charles Holloway)
    • Note to Litigants: When Costs Shift, TAR Costs May Shift with Them – (Jeff Kangas)
    • Measuring and Validating the Effectiveness of Relativity Assisted Review – (David Grossman)
    • LPOs ‘Weaponizing’ Predictive Coding for Own Use, Says Expert Kevin Colangelo – (ACEDS)
    • Technology-Assisted Review: What We Learned: Legal Tech NY 2013 – (Richard Stout)
    • Journey into the Borg Hive: Part Nine – (Ralph Losey)
    • Technology Assisted Review: A Spectrum of Choices – (Cat Casey)
    • Global Aerospace Case Highlights Need For Predictive Coding Education – (Karl Schieneman)
    • Will eDiscovery Swallow The Judicial System? (William Ruskin)
    • Survey of GC and CIOs Predicts a Major Role for Predictive Technology – (Bob Ambrogi)
    • The New Axiom of Computer-Assisted Review (PDF) (Jay Lieb)
    • LPOs ‘Weaponizing’ Predictive Coding for Own Use, Says Expert Kevin Colangelo – (ACEDS)
    • Technology-Assisted Review through the Lens of Downton Abbey – (Peg Duncan)
    • eDSG Poll of GCs and CIOs on Predictive Technology Use – (Charles Skamser)
    • Predictive Coding ROI Outpaces Other Processes Even As Technology Costs Rise – Wilmer Hale’s Steven Berrent – (LXBN)
    • Information Governance Will Replace Predictive Coding As Biggest Trend in eDiscovery – Judge Peck – (LXBN)
    • Predictive Ranking: Technology Assisted Review Designed for the Real World – (Jeremy Pickens)

    JANUARY 2013

    • Top 10 eDiscovery Developments and Trends in 2012 : Technology Law Source – (Jay Yurkiw)
    • Updated Grossman-Cormack TAR Glossary Now on EDRM – (George Socha)
    • Delaware Ruling Gives Judicial Push to Predictive Coding Technology – (Michael Kozubek)
    •  Is 31,000 Missed Relevant Documents an Acceptable Outcome? – eDiscovery Case Law – (Doug Austin)
    • GC Focus | 2012: The Year of Technology-Assisted Review – (Shahzak Bashir)
    • Technology-Assisted Review Increases Efficiencies, Drives Cost Savings – (Eric Robinson)
    • Global Aerospace Predictive Coding Results Approved by Judge – (Chris Dale)
    • Perceived Risks Associated with Technology-Assisted Review – (Eric Robinson)
    • Is Predictive Coding better than Human Document Review? (Debra Cassens Weiss)
    • My Key Word Searches are Better than Your Predictive Ranking Technology – (John Tredennick)
    • First Case for Technology Assisted Review to be Completed – eDiscovery Trends – (Doug Austin)
    • Technology-Assisted Review: What are YOU waiting for? (Eric Robinson)
    • Predictive Coding in ‘Global Aerospace’ Case Reaches Conclusion – (Evan Koblentz)
    • Some Predictive Coding Resources For UK Lawyers – (Chris Dale)
    • Dispelling TAR Myths #1 – What Relevancy Ranking Means – (Sonya Sigler)
    • 2012 Year-End Electronic Discovery and Information Law Update – (Gibson Dunn)
    • 12 Tips To Get The Most Out of Technology-Assisted Review (“TAR”) (Sandra Serkes)
    • Barney It Down: Reviewing the Basics of Predictive Technologies within eDiscovery – (Scott Giordano)
    • What is Predictive Coding?: Including eDiscovery Applications – (Michael LoPresti)
    • 1.6M Documents Released: EDI-Oracle Study Updates will be on EDD Update – (Patrick Oot)
    • EDI Oracle Computer Assisted Review Study – (PR Web)

    DECEMBER 2012

    • Taking Predictive Discovery Out of the Black Box – (Chris Dale)
    • Establishing A Defensible Approach To Technology-Assisted Review – (Stuart LaRosa)
    • Effects of Automated Technologies on Preservation and Review – (Vincent Syracuse, Paul Sarkozi, Matthew Sinkman)
    • Applying Science to the Validation of Technology-Assisted Review – (Chris Dale)
    • Technology-Assisted Review: Ask and You Shall Receive – (Kroll Ontrack)
    • TAR: Too Soon For Prime Time? (Howard Reissner)
    • Top Six Tech Issues of 2012 for In-House Counsel – (Catherine Dunn)
    • Dueling Predictive Coding for Dummies Books Part Deux – (Sean Regan)
    • Georgetown Part Two: New Rules Are Coming! (Ralph Losey)
    • Baby, You Can Drive My CARRM – eDiscovery Trends – (Doug Austin)
    • Technology Assisted Review: Leveraging Advancements to Improve Efficiencies – (Maura Grossman, Carman Oveissi Field)
    • Amazing Forensic Tech Behind Next Apple, Samsung Legal Dust-Up – (Chris Dannen)
    • Bridging the Gap in eDiscovery: The Emergence of Conceptual Semantic Search –  (Jeffrey Parkhurst)
    • Lawyer for eDiscovery Company Predicts Predictive Coding Will Become an Ethical Obligation – (Debra Cassens Weiss)
    • EDRM Publishes Computer Assisted Review Model (CARRM) Framework for eDiscovery – (George Socha)
    • Recommind Predicts Predictive Coding Will Be An Ethical Requirement – (Sharon Nelson)
    • Ralph Losey on the Georgetown TAR / CAR / Predictive Coding Panels – (Chris Dale)
    • Predictive Technologies May Avert Potential Data Archiving Trainwreck – (Wyatt Cash)
    • Two Rival Predictive Coding Books: Doubledown for Dummies – (Sharon Nelson)
    • EDRM Adds Grossman-Cormack TAR Glossary – The Electronic Discovery Reference Model – (George Socha)
    • Georgetown Part One: Most Advanced Students of eDiscovery Want a New CAR for Christmas –  (Ralph Losey)
    • Technology-Assisted Review From the Plaintiffs’ Side – (Henry Kelston, Ariana Tadler, Paul McVoy)
    • Predictive Coding Leads Georgetown E-Discovery Institute – (Monica Bay)
    • Standing Back From The Delaware Predictive Coding Case – (Chris Dale)
    • A Review of Two Predictive Coding “Dummies®” Books – (Sharon Nelson)
    • Orange Hot Pants and Predictive Coding – A Match Made in Delaware – (Drew Lewis)
    • Hooters! You’re Ordered to Use Technology-Assisted Review – (Sheila Mackay)
    • Predictive Coding 101 & the Litigator’s Toolbelt – (Matthew Nelson)
    • Predictive Technologies May Avert Potential Data Archiving Trainwreck – (Wyatt Cash)

    NOVEMBER 2012

    • Predictive Coding Comes of Age – (Quinn Emanuel Urquhart & Sullivan)
    • Is Predictive Coding a Cure for Out-of-Control Discovery Costs? (PDF) (Thompson Hine)
    •  Analytics Across the Enterprise: From eDiscovery to Second Requests – (Charles Skamser)
    • The Grossman-Cormack Glossary of Technology Assisted Review – eDiscovery Resources – (Doug Austin)
    • Predictive Coding Metrics are for Weenies – Part IV – (Karl Schieneman)
    • Part Three: Like it or Not, Predictive Coding is Here and Judges Want you to Use it – (Cat Casey)
    • Escape From Babel: The Grossman-Cormack Glossary – (Ralph Losey)
    • From Law Clerk to First Chair: Effective Positioning of TAR – (Stephanie Maw)
    • The NHCAA, Jackson Pollock, and Predictive Coding – (Kathleen Aller)
    • Louisiana Order Dictates That the Parties Cooperate on Technology Assisted Review – (Doug Austin)
    • ‘Test the Rest’: Sampling for eDiscovery Quality Control – (Chuck Kelner)
    • Delaware Court: Surprise! You Will Now Use PredictiveCoding – (Pooja Nair)
    • Part Two: Like it or Not, Predictive Coding is Here and Judges Want you to Use it – (Cat Casey)
    • The ROI of Predictive Coding – (Bill Tolson)
    • US District Judge Carter Rejects Recusal of Peck in Hot Predictive Coding Case – (ACEDS)
    • Q&A With Predictive Coding Guru, Maura R. Grossman, Esq. – (Matthew Nelson)
    • Patently Unclear – (Craig Ball)
    • Hooters Law Suit Must Use Predictive Coding from Same Vendor – (Anna Biblowitz)
    • Da Silva Moore: Judge Carter Denies Motion for Recusal or Disqualification – (K&L Gates)
    • Judge Carter Refuses to Disqualify one of SDNY’s “Experts in eDiscovery” – More on Da Silva Moore – (Gil Keteltas)
    • Judge Carter Refuses to Recuse Judge Peck in Da Silva Moore – eDiscovery Trends – (Doug Austin)
    • Moving TARget: The Hunt for a More Cost Effective and Efficient Review – (Christopher Yoshida)
    • Mandatory Predictive Coding? What EORHB, Inc. v. HOA Holdings, LLC Could Mean for eDiscovery – (Linda Sharp)
    • EDD Update: USPTO Grants H5 Patent for Its TAR Process – (Sean Doherty)
    • Without Request, Delaware State Judge Orders Use of Predictive Coding in Complex Case – (Robert Hilson)
    • Judge Peck’s Decision Not to Recuse Himself in ‘Da Silva Moore’ Upheld – (Evan Koblentz)
    • Update: Peck, Parties and Predictive Coding – (@ComplexD)
    • Recusal Motion in Da Silva Moore Case Denied – (Philip Favro)
    • Review Acceleration: Getting the Most from Technology-Assisted Review – (Hope Swancy-Haslam)
    • Chancery Court Endorses Predictive Coding – (Bracewell & Giuliani)
    • Judge Orders Parties to Keep it “Kleen” – eDiscovery Law Review – (Dylan Alper)
    • The Grossman-Cormack Glossary of Technology Assisted Review – (Maura Grossman, Gordon Cormack)
    • Like it or Not, Predictive Coding is Here and Judges Want you to Use It – (Cat Casey)
    • Judicial Activism: Delaware Judge Orders Both Sides To Use Predictive Coding – Dale)
    • EDD Update: Throwing a Wrench in the Document Review Machine – (Monica Bay)
    • 7 Expectations To Set Your Team Up For Computer-Assisted Review – (Jay Leib)

    OCTOBER 2012

    • Judicial Activism with Predictive Coding – “Just”, “Speedy” and “Inexpensive” eDiscovery – (Karl Schieneman)
    • Discovery of Discovery: Sampling Practice and Resolution of Discovery Disputes (PDF) – (Nick Landsman)
    • Complex Case Law eDiscovery: Is Predictive Coding a Panacea? (Shannon Kirk)
    • Both Sides Instructed to Use Predictive Coding or Show Cause Why Not – (Doug Austin)
    • TAR: Five Facts in a Flash – (Kroll Ontrack)
    • Delaware Chancellery Court Sua Sponte Orders Parties to Use Predictive Coding – (Wendy Curtis, Jeffrey McKenna)
    • A Delaware Judge and Predictive Coding:  Comments from Ralph Losey, Craig Ball and Dominic Jaar – (Ralph Losey)
    • Surprise Ruling by Delaware Judge Orders Both Sides To Use Predictive Coding – (Ralph Losey)
    • Predictive Coding Metrics are for Weenies – Part I – (Karl Schieneman)
    • Judicial Activism Taken to New Heights in Latest EORHB (Hooters) Predictive Coding Case – Nelson)
    • Court Instructs Parties to Utilize Predictive Coding, Requires Show of Cause to Avoid It – (K&L Gates)
    • Predictive Coding in Unpredictable Order from US Chancery Judge – (David Sharpe)
    • Are Corporations Ready To Be Transparent And Share Irrelevant Documents With Opposing Counsel To Obtain Substantial Cost Savings Through The Use Of Predictive Coding? (Ronni Solomon)
    • Predictive Coding: Transparency, Metrics And Ease Of Use – (Ed Burke, Mary Ann Benson)
    • 100 Percent Chance You’ll Learn Something From These Sampling Experts – (JIm Wagner)
    • Federal Judicial Acceptance of Predictive Coding Beyond Da Silva Moore – (Mike Hamilton)
    • The “E’s” of Predictive Coding – Part Two – (Karl Schieneman)
    • Inconsistent Responsiveness Determination in Document Review: Difference of Opinion or Human Error? (Maura Grossman, Gordan Cormack)
    • 29 Ways To Say “Technology Assisted Review”  – (@ComplexD)
    • Does Your CAR (Computer Assisted Review) Have a Full Tank of Gas? – (Ralph Losey)
    • Court Focuses on Cooperation & Proportionality to Resolve Discovery Disputes – (K&L Gates)
    • Legal Precedents Put Computer Assisted eDiscovery on Course to Broader Enterprise Acceptance – (Charles Skamser)
    • The “E’s” of Predictive Coding – Part One – (Karl Schieneman)
    • Predictive Coding – From the Outside In… – (Drew Lewis)
    • Attorneys Admonished by Judge Nolan Not to “Confuse Advocacy with Adversarial Conduct” – (Ralph Losey)
    • Kleen Products Ruling Confirms Significance of Cooperation and Proportionality in eDiscovery – (Philip Favro)
    • Computers vs. Humans? Putting the TREC 2009 Study in Perspective – (Steve Green, Mark Yacano)
    • Technology-Assisted Review: Four Key Questions – (Joe Garber)
    • Every Good Document Review Starts With Human Expertise – (Howard Reissner, Ian Hochman)
    • Counsel’s Top Predictive Coding Concerns; Part 3 – Fear of Inadvertent Productions – (Bill Tolson)
    • Computer Assisted Review | Electronic Discovery Best Practices – (Ralph Losey)

    SEPTEMBER  2012

    • Predictive Coding: Time, Cost and Accuracy in eDiscovery: Discussion with Howard Sklar – (Lauren Everhart)
    • The Machine Learning / Predictive Coding Silver Bullet – (Tim Leehealey)
    • Analysis of the Official Report on the 2011 TREC Legal Track – Part Three – (Ralph Losey)
    • Getting It Right: Training And Certification In Predictive Coding – (Howard Sklar, Michael Potters)
    • What Lawyers Must Know About Technology Assisted Review – (Sandra Burch)
    • Curtail Rising eDiscovery Costs With Predictive Coding – (Peter Buckley)
    • Actos Litigation Uses Predictive Coding Technology to Sort Documents (Linda Grayling)
    • Analysis of the Official Report on the 2011 TREC Legal Track – Part Two – (Ralph Losey)
    • Litigation: Predictive Coding’s Grand Debut – (Jay Conlin, Andrew Pieper)
    • Technology Review: A FrameWork for Managing People, Technology and Processes – (Lynn Frances)
    • Predictive Coding Emerges as eDiscovery’s Data Salvation – (Maureen Duffy)
    • From Technology Assisted Review To Twitter: What Clients, Law Firms and Vendors Need to Know – (David Horrigan)
    • Trend Towards Adoption Of Predictive Coding: The Good, The Bad, And The Ugly (PDF) – (Wendy Curtis, Jeffrey McKenna)
    • Technology Assisted Review: Leveraging Advancements to Improve Efficiencies (Video) (Maura Grossman, Carmen Field)
    • Analysis of the Official Report on the 2011 TREC Legal Track – Part One – (Ralph Losey)
    • Machine Learning Process Explained – (Cynthia Murrell)
    • Got TAR? – (Craig Ball)
    • Understand Predictive Coding Options – (Joshua Fuchs, Benjamin Wolinsky)
    • An Elusive Dialogue on Legal Search: Part Two – Hybrid Multimodal Quality Controls – (Ralph Losey)

    AUGUST 2012

    • Top Predictive Coding Concerns: Part 2 – It’s Not Well Suited for “Needle in Haystack” Investigations – (Bill Tolson)
    • The Next Big Predictive Coding Case that Wasn’t – (Bob Ambrogi)
    • Predictive Coding Best Method for Detecting ‘Smoking Gun’ Documents – (Twilla Case)
    • EDI, Oracle Launch Computer-Aided Document Review Study – (Monica Bay)
    • Sampling Enters the Mainstream Lexicon of eDiscovery Practitioners – (Sheila Mackay)
    • An Elusive Dialogue on Legal Search: Part One where the Search Quadrant is Explained – (Ralph Losey)
    • Kleen Products Predictive Coding Epitaph – (Karl Schieneman)
    • In Kleen Products Litigation, Parties Stipulate that Predictive Coding is Not Required At This Time – (K&L Gates)
    • Kleen Parties Resolve Predictive Coding Quarrel – For Now – (Maureen O’Neill)
    • eDiscovery Case Law: No Kleen Sweep for Technology Assisted Review – (Doug Austin)
    • Court Sidesteps Issue of Mandated Technology-Assisted Review with Parties’ Stipulation in Kleen Products – (Brian Esser)
    • Clean Sweep in Kleen Products PredictiveCoding Battle? Not Exactly – (Matthew Nelson)
    • Kleen Case Not Using Predictive Coding – (BLLAWG)
    • Predictive Coding in eDiscovery – (Frederick Kopec)
    • Rules-Based Coding Avoids Risks And Landmines In Predictive Coding – (Mary Mack)
    • Plaintiffs Drop Demand for Computer-Assisted Review in “Kleen” Case – (Andrew Bartholomew)
    • Kleen Products LLC Withdraws Request to Redo Production – (Bill Tolson)
    • ‘Kleen’ Plaintiffs Withdraw Demand for Predictive Coding – (Sean Doherty)
    • Plaintiffs in High-Profile ‘Kleen’ Case Drop Demand for Predictive Coding – (Robert Hilson)
    • Another View of TAR – (Cynthia Murrell)
    • eDiscovery Best Practices: For Successful Predictive Coding, Start Randomly – (Doug Austin)
    • Top Ten Best Practices In Predictive Coding | The Metropolitan Corporate Counsel – (Warwick Sharp)
    • Computer Assisted Review – Case Study – (Cat Casey)
    • Predictive Coding Watch: ‘In Re: Actos’ – (Michael Roach)
    • Big Data’s Evolving Role in eDiscovery: What Is Predictive Coding? – (David Hill)
    • eDiscovery Trends: Use of Internet-Based Tools, Predictive Coding, Up in 2012, Says ABA – (Doug Austin)
    • Predictive Coding: What’s New and What You Need to Know – (Christopher Spizzirri)
    • Predictive Coding v. Boolean Search: Out with the Old, In with the New? (Linda Sharp)
    • How to Get Court Approval for Predictive Coding – (Peter Buckley, Scott Vernick)
    • Super Human Information Technology: What’s in a Name? (Bill Tolson)
    • The Malkovich-ization of Predictive Coding in eDiscovery – (Dean Gonsowski)
    • Actos Case TAR Protocol Order – Equivio’s Relevance in Action? (Greg Buckles)
    • The Emergence of a Technology Assisted eDiscovery Lifecycle – (Andrew Bartholomew)
    • Kleen-ing up eDiscovery – (Howard Sklar)
    • Predictive Coding – Interview with Senior Master Whitaker – (Chris Dale)
    • Who Are The Technology Providers For Predictive Coding? (@ComplexD)
    • Day Ten of a Predictive Coding Narrative: Post Hoc Test of Hypothesis of Insignificant False Negatives – (Ralph Losey)
    • Shrink it Down: Technology Assisted Review in Audio Discovery – (Jeff Schlueter)
    • Use of Predictive Coding and the Cloud in eDiscovery Rose in 2012, Survey Says Ambrogi)
    • Valora Technologies CEO Responds to Craig Ball’s LTN Article “Next Level” Technology Assisted Review – (Sandra Serkes)
    • Guest Comment: Power of Predictive Coding – Philadelphia Business Journal – (Peter Buckley, Scott Vernick)
    • Are Seed Sets the New Keyword, Part III: Transparency is Good – (Howard Sklar)
    • TAR Takes Steps Toward Acceptance at Carmel Valley eDiscovery Retreat – (Kris Rzepkowski)
    • Inn Re: Actos eDiscovery Order – An Example of an eDiscovery Order Handling Predictive Coding – (RVM)
    • New TAR Order: In re Actos Products Liability Litigation (PDF) (W.D. La July 27, 2012)
    • Tangible Examples Of Technology-Assisted Review – (Barry Murphy)
    • Keyword Search and Technology-Assisted Review: Judge Scheindlin’s Recent Opinion – (Shelia Mackay)
    • Lawyers See Benefits of Computer Coding, with Caveats – (Erin Geiger Smith)
    • Train, Don’t Cull Using Keywords | Ball in your Court – (Craig Ball)
    • Day Nine of a Predictive Coding Narrative: A Scary Search for False Negatives (And More) – (Ralph Losey)
    • Recommind and Fulbright Panel Debunks Predictive Coding Myths – (Chris Dale)
    • Taking Technology-Assisted Review to the Next Level – (Craig Ball)
    • Are Keywords Obsolete? (RVM)

    JULY 2012

    • Are Seed Sets the New Keyword, Part II: You Can Have My Seed Set – (Howard Sklar)
    • Carmel Valley eDiscovery Judicial Panel on Predictive Coding – (Karl Schieneman)
    • Taking Technology-Assisted Review to the Next Level – (Craig Ball)
    • Predictive Coding, eDiscovery, and Me – (Mark Dubois)
    • Days Seven and Eight of a Predictive Coding Narrative – (Ralph Losey)
    • Why Half Measures Aren’t Enough in Predictive Coding – (Chitrang Shah)
    • Why (Some) Lawyers Don’t Like Technology-Assisted Review – (Dennis Kiker)
    • Court Acceptance of Predictive Coding? Still a Waiting Game – (Michael Hamilton)
    • The Latest Update: Peck, Parties and Predictive Coding – (@ComplexD)
    • Da Silva Moore: Defendant Files Opposition to Plaintiffs’ Objection to Denial of Motion for Recusal or Disqualification – (K&L Gates)
    • Beyond Prediction: Technology-Assisted Review Enters the Lexicon – (Richard Acelio)
    • Judge Scheindlin advises Keyword Search Inadequate, Recommends Predictive Coding as a Best Practice – (Bill Tolson)
    • Predictive Coding – Clawing Back Privileged Documents – (Hayes Hunt, Jillian Thornton)
    • The Cowen Group Q3 Kick Off In New York City – (Barry Murphy)
    • Case in Point for Monday, July 23rd, “TARpit” (Tom Fishburne)
    • Predictive Coding on the Move – (Chris Dale)
    • Days Five and Six of a Predictive Coding Narrative: Deep into the Weeds and a Computer Mind-meld Moment – (Ralph Losey)
    • Increasing Judicial Acceptance of Computer-Assisted Document Review – (White & Case)
    • “Take it e-sy” : Electronic Discovery Law- Julie Anne Halter – (K&L Gates)
    • Judge Scheindlin Says “No” to Self-Collection, “Yes” to Predictive Coding – (Doug Austin)
    • Panel Debunks Predictive Coding Myths – (Monica Bay)
    • Is Predictive Coding a Threat to Jobs? (Talia Page)
    • Kleen Case May Have Another Evidentiary Hearing on Search Methodologies (PDF ) (Via Philip Favro)
    • Predicting Enterprise TAR: Why Smart CIOs and GCs Should Be Talking To Each Other – (Gerard Britton)
    • Are Seed Sets the New Keyword? (Howard Sklar)
    • Trimming Legal Costs and Jobs: A Predictive Coding Unintended Consequence? (Whitney Grace)
    • Firms and Terms: A Snapshot Of Technology Assisted Review Providers And Terminology – (@ComplexD)
    • eDiscovery Trends: TREC Study Finds Technology Assisted Review More Cost Effective – (Doug Austin)
    • Assisted Review Technologies: eDiscovery’s ‘Brave New World’ of Predictive Coding and TAR (451 Research Subscribers) (David Horrigan)
    • Days Three and Four of a Predictive Coding Narrative: Where I Find that the Computer is Free to Disagree – (Ralph Losey)
    • Technology-Assisted Review Boosted in TREC 2011 Results – (Evan Koblentz)
    • Shifting the eDiscovery Paradigm with Defensible Data Reduction –  – (Andrew Bartholomew)
    • Text REtrieval Conference (TREC) 2011 Proceedings – (NIST)
    • Robots Are Not Replacing eDiscovery Lawyers – (Jason Krause)
    • Predictive Coding Gaining Popularity in Complex Litigation – Dinsmore & Shohl LLP – (Grahmn Morgan)
    • Making Sense of ‘Kleen Products’: Is it Really about Predictive Coding? (Bob Ambrogi)
    • Plaintiffs v. Peck – A Worthy Addition to Your Summer Reading List – (Leah R. Glasofer)
    • Da Silva Moore: Plaintiffs Object to Denial of Motion for Recusal or Disqualification – (K&L Gates)
    • Peck, Parties and Predictive Coding – Consolidated Key Document File Update (July 9, 2012) – (@ComplexD)
    • Expanding TAR to become Predictive Discovery – (Greg Buckles)
    • Day Two of a Predictive Coding Narrative: More Than A Random Stroll Down Memory Lane – (Ralph Losey)
    • Predictive Coding – Measurement Challenges – (Venkat Rangan)
    • Class Certification Granted in ‘Da Silva Moore’ – (Mark Hamblett)
    • “One Ring to Rule Them All?” eDiscovery Search Methodology in Patent Litigation – (Wendy Akbar)
    • How One Judge Sees eDiscovery – (Whitney Grace)
    • Survey Shows Surge in eDiscovery Work at Law Firms and Corporations – (Monica Bay)
    • What is the Turing Test for Computer-Assisted Review? (kCura)
    • ‘Lawyerbots’ Offer Attorneys Faster, Cheaper Assistants – (Brittany Fitzgerald)
    • Predicting the Future of Predictive Coding – (Hayes Hunt, Jillian Thornton)
    • London Judicial Panel Points to Future of Technology Assisted Review – (Chris Dale)
    • Day One of a Predictive Coding Narrative: Searching for Relevance in the Ashes of Enron – (Ralph Losey)

    JUNE 2012

    • A Discovery: Study Tech-Aided Review Before It’s an Ethics Issue – (Joe Dysart)
    • The Best Place to Perform Technology Assisted Review (TAR) (Charles Skamser)
    • Case Study: All In The Mix | Millnet – (Charles Holloway)
    • Going “All Out” for Predictive Coding and Vendor Cost Savings – (Ralph Losey)
    • A Solution to the High Cost of eDiscovery: Technology-Assisted Review – (Michael Pontrelli)
    • Litigators on a Journey of eDiscovery (PDF) (Jonathan Ames)
    • Judge Peck: Annoyance Is Not Enough to Warrant Recusal in Da Silva Moore – (Amy Lynn Maxwell)
    • Championing” the Preservation of Keywords in eDiscovery – (Chad McManamy)
    • Opening the Doors of Predictive Coding – (Greg Mucarella)
    • Technology Assisted Review – “Seed Set” vs. Complex Queries – (Kevin Nichols)
    • Judge Refuses Recusal in Da Silva Moore – (Thomas Jones)
    • Learning and Teaching About Predictive Coding Are Not Bases for Recusal – More on Da Silva Moore – (Gil Keteltas)
    • The Digital Advantage: TAR – Is Your Seed Sound? (Mark Walker)
    • Rejecting Da Silva Moore Effort To Remove Him From Case, Peck Writes 56-Page Opinion To Say He Will Stay – (ACEDS)
    • Judge Refuses Recusal in Da Silva Moore : E-Discovery Law Review – (Thomas Jones)
    • eDiscovery Case Law: Judge Peck Denies Recusal Motion in Da Silva Moore – (Doug Austin)
    • Jason Baron on Computer-Assisted Review – Bravo! (Sharon Nelson)
    • Perceived Value of Technology Assisted Review (TAR) (Charles Skamser)
    • Predictive Coding Wins Major Case – (Whitney Grace)
    • Update: Judge Andrew Peck Refuses Recusal in ‘Da Silva Moore’ – Order (Monica Bay)
    • After Court Decisions, Clients Mull Swapping Lawyers for Machines – (Joe Pallazolo)
    • Going Where Few Judges Have Gone Before: Emerging Case Law On Software-Assisted Review – (Jason Baron)
    • Judge Peck Comes Out Fighting And Denies Da Silva Moore Recusal Motion – Dale)
    • Third Millnet eDisclosure Podcast on Predictive Coding – (Chris Dale)
    • One More Update From June 15, 2012 – Peck, Parties and Predictive Coding –
    • 7th Circuit Pilot Program on eDiscovery – (Ralph Losey)
    • Predictive Coding: Dozens of Names, No Definition, Lots of Controversy – (Sharon Nelson, John Simek)
    • The Human Side to Using Predictive Coding in eDiscovery – (Jonathan Easton)
    • Judge OKs Use of Predictive Coding to Cut eDiscovery Document Review Group from 2 Million to 5,000 – (Martha Nell)
    • The New Proportionality – (Howard Sklar)
    • Where Angels Fear To Tread: Daubert, FRE 702 and #eDiscovery – (Philip Favro)
    • Where Does the Money Go? RAND Provides Some Answers – (Doug Austin)
    • Pros And Cons Of Computer-Assisted Review (PDF) (David Breaux, Adrian Fonticella)
    • Update: Peck, Parties and Predictive Coding (1,432 Pages With Index) (@ComplexD)
    • Da Silva Moore: Defendant Opposes Plaintiffs’ Objections to May 7 Discovery Rulings – (K&L Gates)
    • Kleen Products Predictive Coding Update – Judge Nolan – (Matthew Nelson)
    • The Rise of Technology-Assisted Review (TAR) (Barry Murphy)
    • Judge Peck Stays Defendant’s ESI Production in da Silva Moore Pending Resolution of Several Motions – (Phillip Duffy)
    • Judge Peck: Cloud For Enterprises Not Cost-Effective Without Efficient eDiscovery Process – (John Patzakis)
    • What is a ‘Reasonable Search’? (Howard Sklar)
    • 5.16.12 New Order Update: Peck, Parties and Predictive Coding (1320 Pages Consolidated w/Index) (@ComplexD)
    • Judge Peck Stays Defendant MSL Production in ‘Da Silva Moore’ – (Monica Bay)
    • eDiscovery Case Law: Judge Peck Stays Defendant’s Production in Da Silva Moore – (Doug Austin)
    • eDiscovery Case Law: Defendant Responds to Plaintiffs’ Motion for Recusal in Da Silva Moore – (Doug Austin)
    • Judge Peck Puts Freeze On Predictive Coding Protocol in Da Silva Moore Case – (Robert Hilson)
    • Are Your Samples Random? Are You Just Getting Random Results? (Mark Walker)
    • Da Silva Moore: Plaintiffs File Reply in Support of Motion for Recusal or Disqualification – (K&L Gates)
    • Will Predictive Coding Live Up to the eDiscovery Hype? (Philip Favro)
    • Blogging, Proportional Review and Predictive Coding – (Ralph Losey)
    • Da Silva Moore Plaintiff’s Accuse Judge Peck of ‘Naked Retaliation’ – (ACEDS)
    • Are Predictive Coding Disclosures Required? A Proportional Answer – (Gerard Britton)
    • Podcast: Top 10 Tips for Learning Predictive Coding and Forbes Legal Hydra Article – (Karl Schieneman)
    • Da Silva Moore’ Plaintiffs Continue Discovery Objections – (Sean Doherty)
    • Da Silva Moore Opponents Rally to Peck’s Defense – (ACEDS)
    • Do Litigators Need to Understand Predictive Coding Theory? (Charles Skamser)
    • Manual vs. Technology-Assisted Review in eDiscovery: You Can Play Too! (PLG, University of Waterloo)
    • Are You Ready for the Next Step in Document Review Technology? (Michelle L’Hommedieu)
    • An Introduction to Statistical Sampling in Electronic Discovery – (Apersee)
    • Technology Assisted Review, Concept Search and Predictive Coding: The Limitations and Risks – (Johannes Scholtes)
    • Peck Wins By Submission; Parties Get Shot At Title Fight – (eLessons Learned)
    • Move Over Humans, 21st Century Document Review Has Arrived – (William Essig, Lawrence Del Rossi)
    • Technology-Assisted Predictive Modeling and Auto-Classification in Records Management (PDF) (Jason Baron, Dave Lewis)
    • A Viable Alternative to Predictive Coding – (Jonathan Easton)
    • The Names and Faces of “Technology Assisted Review” (@ComplexD)
    • Four Lessons Counsel Can Learn About Da Silva Moore and Predictive Coding | Quarles & Brady – (Steven Hunter)
    • Ride The Lightning: More on Da Silva Moore and Judge Peck – (Sharon Nelson)
    • Two Hits and No Strikes for Computer-Assisted Review – (Jon Resnick)
    • Judge Carter’s DaSilva Decision: Cleared for Takeoff? (Maureen O’Neil)
    • 3 Drawbacks To Predictive Coding – (Sandra Serkes)
    • Scattershot Innuendo and Muck – The Plaintiffs Respond To The Recusal Motion in Da Silva Moore – (Chris Dale)
    • Combatting Bias in Predictive Coding Adoption: In the Courts and in Practice – (Gerard Britton)
    • Defendants in ‘Da Silva Moore’ Oppose Motion to Recuse Judge – (Michael Roach)
    • Three Things to Ask to Make Sure You’re Getting Predictive Coding (Howard Sklar)
    • VA State Court Orders Predictive Coding Over A Party’s Objections In High Stakes Case – (Robert Hilson)
    • The Real Winners In Technology-Assisted Review Are… (Barry Murphy)
    • Score One for Peck – (Linda Sharp)
    • Does Predictive Coding Spell Doom for Entry-Level Associates? (Erica Birg)
    • Updated 5/2/12 – Consolidated Filings (812 Pages) Peck, Parties and Predictive Coding – (@ComplexD)
    • Defendant Files Response to Plaintiffs’ Motion for Recusal – (K&L Gates)
    • Take Two: Reactions to ‘Da Silva Moore’ Predictive Coding Order (Evan Koblentz)
    • Global Aerospace v. Landow Aviation – Audio of Judge Chamblin’s Order Approving Predictive Coding – (Trustpoint International)
    • The Buzz on Predictive Coding – Global Aerospace Inc., et al. v. Landow Aviation LP, et al. (PDF) (Redgrave LLP)
    • Considered, Deferred, Denied | @Millnet – (Charles Holloway)
    • The Why & How of Predictive Coding – (James Moeskops, Chris Dale)

    APRIL 2012

    • Computer-Assisted Review: Reducing Risk For The CPS – (Howard Sklar)
    • Top Ten Considerations When Evaluating Technology-Assisted Document Review Technology – (Pradeep Victor)
    • Judicial Test Pilot – (Josh Gilliland)
    • Judge Carter Adopts Magistrate Judge Peck’s Order Endorsing Use of Predictive Coding (PDF) (Paul Weiss)
    • Nod to Predictive Coding in ‘Da Silva Moore’ Stirs Caution, Excitement – (Evan Koblentz)
    • District Judge Upholds Peck on Predictive Coding, Says Recusal Of Magistrate Judge May Endanger Ruling – (ACEDS)
    • Open Questions About Carter’s Upholding of Peck – (Evan Koblentz)
    • Predictive Coding Software Sifts Through Documents Better (Luis Salazar)
    • Peck Decision on Use of Predictive Coding Upheld in N.Y. Federal Court – (Mark Hamblett)
    • District Court Judge Adopts Orders Approving Use of Predictive Coding, Denies Plaintiffs’ Objections – (K&L Gates)
    • Da Silva Moore, Global Aerospace, Kleen Products: Hyped Triumvirate, But Dispositive Opinion Yet To Come – (Brandon Hollinder)
    • First State Court Issues Order Approving the Use of Predictive Coding – (Matthew Nelson)
    • Another eDiscovery Milestone: State Judge Orders Predictive Coding – (Allison Frankel)
    • Federal Court Affirms Judge Peck’s Predictive Coding Order (Bob Ambrogi)
    • Peck, Parties and Predictive Coding – (Updated 4/26/2012) – (@ComplexD)
    • Virginia State Court Judge Allows Defendants to Use Predictive Coding – (K&L Gates)
    • Judge Carter OKs Peck’s Predictive Coding Decision in ‘Da Silva Moore’ – (Evan Koblentz)
    • Judge Carter Upholds Judge Peck’s Predictive Coding Order in Da Silva Moore Case – (PDF) (ACEDS)
    • eDiscovery BREAKING Case Law: Judge Carter Upholds Judge Peck’s Predictive Coding Order – (Doug Austin)
    • Predictive Coding – An Interview With James Moeskops Of Millnet – (Chris Dale)
    • Big Data Meets Computer-Assisted Review – (Jay Lieb)
    • Is the Third Time the Charm for Technology Assisted Review? (Doug Austin)
    • Experts Debate The Ins and Outs Of Technology-Assisted Review – (Alex Vorro)
    • Smart Scope and Smarter Tools Help Cut E-Discovery Costs – (Craig Smith)
    • Defensible Disposal and Predictive Coding Reduces (?) eDiscovery by 65% – (Bill Tolson)
    • Major State Court Ruling Issued on Predictive Coding – Use Approved Over Opponents’ Objections – (OrcaTec)
    • Second Ever Order Entered Approving Predictive Coding – (Ralph Losey)
    • Va. Judge Orders Predictive Coding Over Plaintiff Objections – (Evan Koblentz)
    • Document Review in 2025: eDiscovery To Infinity And Beyond (Kara Kirkeby, Jodi Vickerman)
    • “Where The Money Goes” – A Report By The Rand Corporation | eDiscovery Team – (Ralph Losey)
    • Federal Court Approves Use Of  “Predictive Coding” | Metropolitan Corporate Counsel – (Brendan Schulman, Samantha Ettari)
    • Plaintiffs Move To Recuse Peck In Predictive Coding Case, Now Suggesting Financial Link To Recommind – (ACEDS)
    • Plaintiffs Trying To Get Judge Peck Bounced from Landmark Predictive Coding Case – (Christopher Danzig)
    • Leading Federal Court Decision Opens Doors to Wider Use of Computer-Assisted Review – (Deanna Blomquist, Aaron Van Oort)
    • Predictive Coding Watch: ‘Kleen Products’ in Illinois – (Michael Roach)
    • Plaintiffs File Formal Motion for Recusal or Disqualification in Da Silva Moore – (K&L Gates)
    • One Size Doesn’t Fit All in Predictive Coding – (Matt Miller)
    • eDiscovery Dispute Yields Formal Recusal Request in ‘da Silva Moore’ – (Sean Doherty)
    • A is for Apple Appeal: Peck’s Approval of Computer-Assisted Review Under Review – (eLessons Learned)
    • Kleen Products vs Da Silva Moore: Measurement vs Method – (Greg Buckles)
    • Redefine Transparency in Predictive Coding: Shoot for Validity – (Gerard Britton)
    •  The Other Technology Assisted Review Case – (Doug Austin)
    • Plaintiffs Ask Judge Nan R. Nolan to Go Out On Limb In Kleen Products Predictive Coding Case – (Matthew Nelson)
    • The ‘Other’ Predictive Coding Case Shows Vastly Different Judicial Fact-Finding Approach – (Robert Hilson)
    • 4 Lessons Counsel Can Learn from Da Silva Moore – (Steven Hunter)
    • Da Silva Moore + Kleen = It’s All About the Math – (Karl Schieneman)
    • Predictive Coding — Cost Savings If Investment Is Made | Lowenstein Sandler (PDF) – (Nicole Albano, Ryan Cooper)
    • Information Governance and Predictive Coding – (Bill Tolson)
    • What’s the Difference Between Automated Review and PredictiveCoding? (Valora Technologies)
    • eDiscovery Case Law: Friday the 13th Is Unlucky for Judge Peck – (Doug Austin)
    • More in Da Silva Moore: Magistrate Judge Peck Responds to Request for Recusal – (K&L Gates)
    • Computer Assisted Review: Technology to Help Navigate the Murky Waters of eDiscovery | Sedgwick LLP – (Nicholas Weiss)
    • Equivio Spells out Predictive Coding Basics on ESIBytes Podcast – (Chris Dale)
    • The Battle of Boolean Searches versus Sampling and Predictive Coding and Attacking Expert Witnesses – (Karl Schieneman)
    • Technology-Assisted Document Review: Is It Really Defensible (PDF) – (Dennis Kiker, Daryl Shetterly, William W. Belt)
    • eDiscovery Case Law: Judge Peck Responds to Plaintiff’s Request for Recusal – (Doug Austin)
    • ‘Da Silva Moore’ Plaintiffs Request Recusal for Judge Peck – (Sean Doherty)
    • Court Affirms Technology-Assisted Review — Now What? (Webinar Recording) (Xerox XLS)
    • Try It, You’ll Like It (Or Not) – (Sean Doherty)

    March 2012

    • PredictiveCoding: 5 Things You Should Know (PDF) – (David Kessler, Florinda Baldridge)
    • Much Ado About (Predictive Coding) Definitions – (Craig Carpenter)
    • Predictive Coding: A Rose by Any Other Name – (Sharon Nelson, John Simek, Dan Gallivan)
    • Training of Predictive Coding Systems Fosters Debate – (Evan Koblentz)
    • Global eDiscovery & Da Silva Moore Technology Assisted Review Case Overview – (Michele Lange, Jim Daley)
    • eDiscovery Case Law: Da Silva Moore Plaintiffs Question Predictive Coding Proposal, Judge Peck’s Activities (Doug Austin)
    • Predictive Tagging: It’s A Process, Not A Panacea – (Bill Mariano)
    • Predictive Coding And Patented Workflow: A Defensible #eDiscovery System – (Howard Sklar)
    • Roitblat Publishes Critique: Argument in Da Silva Moore Case Isn’t About Predictive Coding – (PR Web)
    • Putting the Duh in Da Silva Moore – (Craig Ball)
    • What’s the Right Call on Computer Assisted-Review? (Jon Resnick)
    • Predictive Coding Based Legal Methods for Search and Review – (Ralph Losey)
    • OrcaTec’s Herb Roitblat Gets The Measure of Da Silva Moore Plaintiffs – (Chris Dale)
    • Validating Predictive Coding, Da Silva Moore Case and Other Current Issues – (Karl Schieneman, Herb Roitblat)
    • Da Silva Moore Plaintiffs Slash and Burn their Way Through eDiscovery – (Herb Roitblat)
    • Should the ‘Daubert’ Standard Apply to Predictive Coding? We May Know Soon – (Bob Ambrogi)
    • Predictive Coding on Trial: Knives Out – (Katey Wood)
    • Da Silva Moore Fast Becoming Landmark eDiscovery Case – (Barry Murphy)
    • Update – Plaintiffs Attack Judge Peck’s Da Silva Moore Predictive Coding Order Again – (Brandon Hollinder)
    • Da Silva Moore Plaintiffs File Reply Brief In Support of Objections to Discovery Rulings – (K&L Gates)
    • Do Novel Document Review Methods Demand Disclosure? (Robert Trenchard, Steven Berrent)
    • Endorsement, Evidence and Impartiality: Predictive Coding, Take 2 (BLLAWG)
    • A Golden Opportunity for Predictive Coding – (BLLAWG)
    • Court Recognizes Computer-Assisted Review as Acceptable Way to Search for Relevant Electronic Documents – (Patton Boggs)
    • Predictive Coding Is a New Tool in the eDiscovery Toolbox – (Philip Cohen, Lauren Harrison)
    • Judge Peck’s Da Silva Moore Opinion Will Continue to Be Influential Despite Objection – (Brendon Hollinder)
    • Not So Fast on Computer Assisted Review – (Doug Austin)
    • New Methods for Legal Search and Review – (Ralph Losey)
    • Shedding Light on the Predictive Coding Black Box – (James Hanft)
    • Judge Carter Grants Plaintiff’s Request To File Opposing Brief Re: da Silva Moore (PDF) (Sirham Nurhussein)
    • Will Approval of Computer-Assisted Document Review Spur Acceptance in Antitrust Investigations? (Jones Day)
    • What is this Predictive Coding thing Anyway? (Chuck Rothman)
    • Fulbright Focuses on Transparency in Predictive Coding Review – (Chris Dale)
    • Judge Peck Provides a Primer on Computer-Assisted Review – (John Tredennick)
    • LegalTech New York Interview of Dean Gonsowski on Predictive Coding – (Ralph Losey)
    • The Blogosphere Reacts to Judge Peck’s Ruling on Predictive Coding – (Bob Ambrogi)
    • Federal Judge Approves Predictive Coding Technology for eDiscovery (PDF) – (GreenbergTraurig)
    • Judge Peck’s Predictive Coding Opinion – Reporting The Reaction – (Chris Dale)
    • Overview of the TREC 2010 Legal Track (PDF) (Gordon Cormack, Maura Grossman, Bruce Hedin, Douglas Oard)
    • Before They Were Famous Video – Maas, Whitaker, Peck and Waxse On Predictive Coding – Dale)
    • Landmark E-Discovery Decision Recognizes the Appropriateness of Predictive Coding Review – (Squire Sanders)
    • eDiscovery Case Law: Computer Assisted Review Approved by Judge Peck in New York Case – (Doug Austin)
    • Computer-Assisted Review Approved – (Rebecca James)
    • Peck, Parties and PredictiveCoding – (@ComplexD)
    • The eDiscovery Opinion We’ve Been Waiting for Has Arrived – (Jon Resnick)

    February 2012

    • Use of Computer-Assisted Coding Is Endorsed to Comb Through Huge Number of Documents – (Mark Hamblett)
    • Judge Peck Opens The Way For Mainstream Adoption Of Predictive Coding – Sharp)
    • Judge Peck’s PredictiveCoding Game-Changer (Craig Carpenter)
    • In A Milestone for Predictive Coding, Judge Peck Says, ‘Go Ahead, Dive In!’ (Bob Ambrogi)
    • Federal Court Approves Use of “Computer-Assisted Review” to Find and Produce Relevant ESI in Discovery – (Jay Yurkiw)
    • Predictive Coding ’s Silver Blaze: The Dogs Who Didn’t Bark In The Night-Time – (Chris Dale)
    • Computerized Document Review Defensible at Last? (Ron Friedmann)
    • eDiscovery Case Law: Predictive Coding Considered by Judge in New York Case – (Doug Austin)
    • eDiscovery Trends: “Assisted” is the Key Word for Technology Assisted Review – (Doug Austin)
    • Judge Peck Issues Opinion on Computer-Assisted Review – (Monica Bay)
    • Computer-Assisted Review “Acceptable in Appropriate Cases,” Says Judge Peck – (Matt Nelson)
    • Plaintiffs Object to Predictive Coding Order, Argue Lack of Transparency in eDiscovery Process – (Philip Favro)
    • Federal Judges Consider Issues That Could Shape Predictive Coding Future – (Matt Nelson)
    • An Interview with The Honorable Andrew J. Peck – Part Two | eDiscovery Journal – (Mikki Tomlinson)
    • Is Judge Peck the First to Require a Predictive Coding Protocol for Automated Doc Review? (Martha Neil)
    • The Honorable Andrew J. Peck on the Record with Predictive Coding: Early Headlines Get it Wrong! (Mikki Tomlinson)
    • Predictive Coding Addressed in Detail at Hearing, Parties Ordered to Submit Draft Protocol – (K&L Gates)
    • An On-the-Record Colloquy about Predictive Coding With Judge Peck (Bob Ambrogi)
    • Doar Experts Advise Plaintiffs in Hearing before Magistrate Judge Peck on the Use of  Predictive Coding – (Business Wire)
    • Technology on Trial: Predictive Coding – (Sean Doherty)
    • Cranking Up the Buzz on InfoGovernance, Predictive Coding – (David Snow)
    • Technology Assisted Review – Advice from the Experts – (BLLAWG)
    • Ralph Losey of Jackson Lewis on Predictive Coding and Transparency in E-Discovery –

    Additional ComplexDiscovery Resources on Technology-Assisted Review

    Click here to provide additions, corrections and/or updates.

    Source:  Public Domain Information


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