Guest Details

Martha Louks Managing Director, Discovery Technology ServicesMcDermott Will & Emery

EPISODE OVERVIEW:

A Relativity Master with five certifications, Martha has led discovery technology initiatives for 15+ years, including predictive‑coding protocols used in the DOJ’s AB InBev–Grupo Modelo merger review.

Daniel Gold and Brandon Mack speak with Martha Louks about the evolution of discovery from paper to email, mobile, conversational data, TAR, and now generative AI. Martha explains why modern evidence is “data, not documents,” how platforms struggle with Slack, texts, and chatbot conversations, and why GenAI still requires TAR‑style validation. She also breaks down misconceptions about AI, where automation helps, where human judgment remains essential, and how review roles will evolve over the next five years.

KEY POINTS:

• Discovery is now data‑centric. Slack, texts, and chatbot conversations don’t fit TIFF‑based “documents,” making timeline analysis across sources difficult.

• GenAI is still TAR. Validation, sampling, and defensibility remain mandatory.

• AI helps with high‑volume tasks, not precision work. Fact extraction and timelines benefit; briefs and legal arguments require strict verification.

• Human review isn’t disappearing. Privilege, QC, and substantive analysis still require lawyers.

• Costs shift, not vanish. AI reduces review volume but increases tech spend; rising data volumes offset savings.

• Future success requires flexibility. Strong fundamentals, curiosity, and skepticism matter more than ever.

• Reframe review around activity and timelines, not static documents.

• Use GenAI for fact extraction, timelines, early case assessment, and eliminating non‑responsive material.

• Apply TAR‑style validation to all GenAI workflows.

• Adopt AI internally without creating unnecessary adversarial fights over protocols.

• Train review teams to elevate their work—privilege, issue analysis, structured data extraction.

• Combine classification, TAR, and GenAI depending on task and cost model.

• Encourage new professionals to stay flexible, process‑minded, curious, and skeptical.

TIMECODES:

00:00 – Introduction & Guest Background00:48 – Martha’s Career Across Paper, Email, Mobile, TAR, GenAI01:36 – Which Transitions Changed Lawyer Thinking01:54 – From Paper to Databases02:52 – Early ESI & Deduplication Skepticism03:31 – TAR Adoption & Validation04:14 – Faster GenAI Adoption04:50 – Rise of Legal Technologists05:43 – AI Hype vs. Reality07:22 – Data vs. Documents08:22 – Why TIFF Still Dominates09:00 – Activity Tracking Across Sources09:46 – Chatbot Conversations & Timeline Problems10:39 – AI Misconceptions11:20 – Precision vs. High‑Volume Work12:09 – Cost of Verification12:58 – Marketing Hype13:46 – Fear‑Based Sales Cycles14:34 – Margin of Error & Reviewer Expectations15:12 – Where AI Is a “No‑Brainer”15:58 – Timelines & Fact Extraction16:21 – GenAI as TAR17:18 – TAR Principles That Still Apply18:03 – Humans vs. Technology18:51 – Should AI Do First‑Pass Review?19:57 – Collaboration Barriers & Sedona Principle 620:55 – “Say Less, Do More”21:43 – Evolution of Review Roles22:31 – Privilege Review & Human Oversight23:18 – Structuring Documents with Prompts24:05 – Bibliographic‑Style Coding via AI24:58 – Costs & Token Usage25:49 – Rising Data Volumes26:37 – Combining Tools27:43 – Litigation Team of 203128:03 – Advice for New Professionals28:56 – Closing Remarks

QUOTE:

“Be flexible. The fundamentals remain the same, but every six months we see new data formats. You need strong core principles—and a healthy dose of skepticism.” — Martha Louks

EPISODE OVERVIEW:

In this special mid‑year recap, Daniel and Brandon revisit the ten conversations recorded so far in Season 2—judges, a dean, a chief justice, forensic experts, researchers, and in‑house strategists—and place their insights directly against the federal case law emerging in the first half of 2026. Throughout the season, five recurring questions surfaced around generative AI, prompts, privilege, validation, and the limits of the rules. Now, with courts issuing opinions on those exact issues, the hosts examine where guest predictions aligned with judicial outcomes and where new fault lines are forming.

This episode is both a highlight reel and a reckoning: a synthesis of expert commentary and real‑world rulings that reveal how quickly the legal system is responding to AI‑driven change—and what practitioners should expect in the second half of 2026.

KEY TAKEAWAYS:

• The rules still hold. Judges Kim and Rodriguez stressed that technology does not displace the Federal Rules; courts continue applying relevance, reliability, and prejudice. SDNY echoed this in U.S. v. Hepner, noting AI’s novelty “does not exempt it from longstanding principles.”

• Prompts are splitting courts. Practitioners argued prompts are classic opinion work product. Courts agreed when lawyers use enterprise tools (Concord Music), but rejected privilege when clients used public AI platforms (Hepner).

• GenAI review is TAR. Dr. Jeremy Pickens emphasized that GenAI workflows mirror TAR 1.0, meaning validation discipline—control sets, measurement, plain‑English defensibility—still applies.

• Data location matters. The District of Kansas barred uploading even non‑confidential discovery into open‑loop AI tools, finding deletion “impossible as a practical matter.”

• Human oversight remains essential. Across guests and courts, the through‑line is clear: AI is powerful, but lawyers must supervise, verify citations, and explain processes plainly.

  
  

  ACTION ITEMS:

• Treat prompts and AI workflows as discoverable artifacts requiring documentation and defensibility.

• Validate GenAI review using traditional TAR methods—control sets, sampling, and expert explanation.

• Avoid uploading discovery into public AI tools; use enterprise platforms with contractual protections.

• Supervise AI outputs like junior associate work—review, correct, and verify before filing.

• Track emerging case law; courts are drawing bright lines around privilege, waiver, and data handling

  
  

CHAPTERS AND TIMECODES:

00:00 – Cold Open: Season Themes00:32 – Introduction & Episode Setup01:56 – Methodology: Quotes + Case Law02:49 – Topic 1: “The Rules Still Hold”03:18 – Judge Kim on Rules as Anchor03:47 – Judge Rodriguez on Hallucinations05:28 – Forensics View: Reliability & Evidence06:18 – SDNY’s Hepner Decision07:47 – Why Judges Still Worry08:36 – Topic 2: Prompts, Privilege & Work Product09:03 – Keeling: Prompts = Opinion Work Product10:29 – Davis: Prompts Are Forensically Reachable11:10 – Gaudet: Duty to Supervise12:16 – Courts Split: Hepner, Warner, Morgan 14:41 – Concord Music: Attorney Prompts Protected15:35 – Adoption Risks & Waiver16:53 – Topic 3: Validation & Defensibility17:20 – Pickens: GenAI = TAR 1.018:33 – Germ Theory & Control Sets20:18 – Keeling: TAR Validation Still Applies21:33 – Amberson: Vetting & Bias Controls23:40 – Judge Kim: Plain‑English Reliability24:53 – Topic 4: Data Location & Protective Orders25:17 – Kansas: Ban on Open‑Loop AI Tools26:30 – Irretrievable Model Training Risk27:12 – Closing Reflections & Season Outlook

COMPELLING QUOTE:

“The anchor holds the ship. It doesn’t steer it.”

Guest Details

Bridget Mary McCormack: President & CEO, American Arbitration Association & ICDRFormer Chief Justice, Michigan Supreme Court

Episode Overview

Bridget Mary McCormack joins Daniel Gold and Brandon Mack for a candid conversation about modernizing courts, expanding access to justice, and how AI is reshaping both public and private dispute resolution. Drawing on her decade on the Michigan Supreme Court—including four years as Chief Justice—McCormack explains why state courts must operate as system designers, not just adjudicators. She describes Michigan’s rapid shift to remote proceedings during COVID‑19, the state’s proportionality‑based discovery reform, and the importance of designing processes around the people who actually use the courts—especially the 75% of civil litigants who appear without lawyers.

Now leading the AAA, McCormack discusses how the organization is deploying AI to improve user experience, support self‑represented parties, and build new dispute‑resolution options. She emphasizes transparency, auditability, and fairness as essential guardrails, while also challenging long‑held assumptions about what must remain unchanged in the justice system.

Key Takeaways

• Nothing is too sacred to re‑examine. Courts must avoid assuming any process “can never change,” or they risk failing the people they serve.

• Remote proceedings improved access. Michigan saw significantly lower default rates for self‑represented litigants once remote options became available.

• AI is expanding access, not shrinking it. Both courts and the AAA are seeing major increases in filings from self‑represented parties as AI tools help people understand and pursue valid claims.

  
  

Action Items

• Build systems that prioritize user needs, not institutional habits.

• Use AI to reduce barriers for self‑represented parties while maintaining transparency and auditability.

• Treat modernization as continuous, not episodic—technology evolves too quickly for five‑year plans.

Chapters with Timecodes

00:00 – Introduction01:16 – McCormack’s Background & Court Modernization02:47 – State Supreme Courts as System Designers04:40 – What Should Never Change? (“Nothing.”)06:29 – Michigan’s Discovery Reform07:56 – State‑Level Discovery Challenges08:15 – Designing Reform with User Input10:05 – Hearing from Pro Se Litigants12:55 – COVID‑19 & Remote Proceedings14:40 – Data on Defaults & Access16:16 – Children & Higher‑Quality Remote Testimony18:01 – Why Mandatory In‑Person Is “User‑Hostile”19:39 – AI & Increased Filings21:55 – State Courts’ Volume Challenges23:17 – Updating the Justice “Operating System”23:39 – AI as New Dispute‑Resolution Options24:53 – Human vs. AI “Hallucinations”26:19 – Why She Chose the AAA27:46 – AAA’s Scale & Innovation Capacity29:37 – Evaluating AI Workflows30:06 – AAA’s AI Strategy31:49 – Innovation Pipeline & Lessons Learned32:34 – AI‑Assisted Arbitration35:01 – Procedural Fairness & Transparency37:22 – Which Decisions Must Remain Human40:13 – When Parties Might Choose Automation43:18 – Six‑Week Innovation Cycles46:11 – Future Legal Frameworks

Compelling Quote

“The courts are for the people. They’re not for the judges… They want to solve their problems. They’re not really in the market for us.” — Bridget Mary McCormack

Episode Overview

In this wide‑ranging and energizing conversation, Dean Lou Mulligan joins hosts Daniel Gold and Brandon Mack to explore the evolving landscape of legal education, the role of technology in modern practice, and the values that must anchor the next generation of attorneys. Drawing from a career that spans clerking on the Tenth Circuit, briefing U.S. Supreme Court cases, leading major MDLs, and now steering UMKC Law, Dean Mulligan offers a candid look at how law schools are adapting to e‑discovery, AI, and shifting professional expectations.

The episode examines why e‑discovery education remains uneven across the country, how AI is reshaping both pedagogy and access to justice, and why discernment, compassion, and professionalism remain irreplaceable—even in an era of rapid automation. Throughout, Dean Mulligan emphasizes the mission‑driven nature of today’s students and the profound responsibility legal educators share in preparing them for a profession undergoing historic transformation.

• E‑discovery is moving from niche to core: Stronger law schools increasingly treat e‑discovery as part of the essential civil‑litigation track, though national adoption remains “uneven and evolving” .

• AI is transforming legal education and access to justice: UMKC now offers 28 courses with meaningful AI components and is building tools for pro se litigants, including eviction and expungement assistance.

• Human judgment remains the lawyer’s irreplaceable value: Even as AI accelerates research, lawyers must still “read the statute… read the relevant cases… [and] bring judgment, professionalism, compassion” .

• Integrate AI responsibly: Use AI for efficiency, but always verify primary sources, Shepardize, and apply legal judgment before relying on outputs.

• Expand access to justice: Consider how AI tools can help underserved populations navigate routine legal processes.

• Advise students and junior attorneys intentionally: Tailor training to their intended practice areas—litigation, transactional, regulatory—rather than assuming a one‑size‑fits‑all technology curriculum.

00:00 – Welcome & Episode Introduction01:30 – UMKC Law’s Partnership with NELI02:37 – Dean Mulligan’s Personal and Professional Journey04:10 – From Clerkships to Academia to Deanship05:14 – The Purpose and Impact of Legal Education07:25 – How Law Schools Teach (or Don’t Teach) e‑Discovery08:15 – National Landscape: Uneven but Evolving09:13 – E‑Discovery as Core Litigation Curriculum10:30 – Teaching Technology Tools in Law School11:18 – Competency, Professional Identity & the ABA’s Role14:01 – Why Not All Students Need Deep E‑Discovery Training16:11 – Advising Students Toward Their Career Paths17:12 – AI’s Growing Role in Legal Education18:33 – National Trends: Courses, Credentials & Equity19:35 – UMKC’s 28 AI‑Integrated Courses20:33 – AI in Clinics & Experiential Learning21:23 – Challenges of Curriculum Agility22:16 – CLE Programming & AI Weekends23:04 – Providing Every Student a Legal AI Tool23:53 – AI Tools for Pro Se Litigants (Eviction & Expungement)24:42 – AI as an Equity Engine25:31 – Cognitive Skills, Research Habits & AI Limitations28:20 – Teaching Students to Verify AI Outputs30:03 – AI, Billing Models & the Future of Legal Work32:34 – AI as Market Expansion for Legal Services34:27 – Access to Justice & Strengthening Rule of Law35:36 – What Excites Dean Mulligan About the Next Generation38:10 – The Enduring Importance of Judgment & Compassion39:40 – AI as the Great Equalizer in Legal Access41:21 – Law as a Human Service Profession43:24 – Closing Reflections & Invitation to NELI Conference

Compelling Quote

“At the end of the day, law is a human profession… providing services to humans. And all those folks have ends and have value and have children and wants and dreams.” — Dean Lou Mulligan

Guest: Professor Jonah Perlin

Legal Writing Professor & Ethics Scholar, Georgetown LawHost of The Howard Lawyer podcast

Professor Jonah Perlin joins Daniel and Brandon for a wide‑ranging conversation on how generative AI is reshaping legal practice, legal education, and the economics of the profession. Drawing on his background as a litigator, clerk, and scholar, Perlin argues that AI is not a revolution but the latest step in a long line of technological shifts. He explains why the billable hour is unlikely to disappear, how confidentiality has evolved into a duty of security, and why critical thinking—not drafting—is the lawyer’s true competitive advantage.

• AI is evolutionary, not exceptional. Past predictions about technology killing the billable hour or transforming lawyering never fully materialized; AI is another turn of the wheel.

• The billable hour will adapt. Through his CHARGE equation, Perlin shows that reduced hours don’t doom the model—rates, reductions, and expenses also shape compensation.

• Critical thinking and security define modern lawyering. AI handles routine tasks; lawyers must excel at judgment, empathy, and safeguarding client data.

• Redesign assessments and training to measure comprehension and critique, not tasks AI can perform.

• Treat confidentiality as a duty of security, requiring ongoing cybersecurity literacy.

• Build pricing narratives that explain how AI‑enhanced work delivers concentrated value.

• Invest in human‑centric skills—judgment, empathy, strategic thinking.

• Prepare for structural shifts as historical billing data becomes less predictive.

Chapters & Timecodes

00:00 – Introduction & Guest Welcome

03:15 – AI as the Next Turn of the Wheel

06:45 – Confidentiality Becomes Security

08:30 – How AI Is Changing Legal Education

12:20 – Historical Parallels in Tech Adoption

15:45 – The Assessment Challenge

18:10 – Are We Losing Core Skills?

22:00 – The CHARGE Equation & Billable Hour Survival

26:30 – Challenging the AI Efficiency Narrative

30:15 – Why AFAs Haven’t Taken Over

34:00 – The Real Threat: Devaluation of Legal Work

38:45 – Critical Thinking as the Human Advantage

42:30 – Obsolescence of Historical Billing Data

45:00 – How Legal Practice Evolves Over Decades

48:30 – Optimism About the Profession’s Future

51:00 – Closing Remarks

“The real danger isn’t efficiency—it’s clients deciding your work is no longer valuable.”

Guest: Mike Gaudet

Senior Managing Director, Digital Investigations & eDiscovery, JS Held

Mike Gaudet joins Daniel and Brandon to discuss how modern investigations are being reshaped by massive data growth, mobile devices, and the rapid rise of AI. With 20+ years of experience and a computer science background, Mike explains why today’s matters require both technical depth and cross‑functional collaboration. He also shares how natural language search, RAG databases, and GenAI‑driven triage are transforming early case assessment and dramatically reducing costs.

• Data sources have exploded. Companies may have hundreds of thousands of data sources; a single phone can contain 100+ apps and terabytes of data.

• AI is a force multiplier. Treat AI like a junior associate—give it context, supervision, and case‑specific grounding through RAG databases.

• Cross‑functional teams win. Combining eDiscovery, forensics, fraud analytics, and industry expertise produces faster, more complete investigations.

• Bring technical experts into interviews early to identify all data sources, including shadow IT.

• Preserve broadly, then use AI‑driven triage to determine which custodians actually matter.

• Triage mobile data before loading full device images into review platforms.

• Adopt natural language search and RAG‑based workflows for early case assessment.

• Maintain a duty to supervise AI outputs just as you would a junior attorney.

Chapters & Timecodes

00:00 – Introduction 01:15 – Meet Mike Gaudet 02:30 – From IBM to eDiscovery 05:45 – Learning the Legal World 07:00 – The Data Explosion (500,000+ sources) 09:30 – Mobile Devices Become Key Evidence 11:00 – Structured Data & Fraud Investigations 13:15 – Legacy Systems & Historical Data 14:30 – Shadow IT & Work‑From‑Home Challenges 16:45 – GPT’s Leap & AI’s Role in eDiscovery 18:30 – Duty to Supervise AI 20:00 – Mobile Collection Strategies & Privacy 22:00 – SEC Off‑Channel Communications 24:00 – Professional Services vs. Legacy Vendors 26:00 – GenAI for Cost Reduction (Custodian Reduction Example) 28:00 – Natural Language Search (80% Net‑New Docs) 30:00 – RAG Databases Explained 32:00 – Hybrid AI Workflows & Cost Management 34:00 – Cross‑Functional Collaboration Example 36:00 – Industry Expertise & IP Cases 38:00 – Future of AI‑Powered Investigations 40:00 – Why JS Held Supports NELI

“That’s all I have to do?… And then you could see the light bulb go off on her head.”

Guest: Dr. Jeremy Pickens

Managing Director of Applied Science, Elevate

Episode Overview

In this masterclass‑level conversation, Dr. Jeremy Pickens—one of the most respected information retrieval scientists in e‑discovery—joins Daniel and Brandon to explore the intellectual foundations and future trajectory of search, relevance, and AI in legal practice. Jeremy’s work has shaped the evolution from keyword search to TAR 1.0, to continuous active learning (CAL), and now to the GenAI era. If you’ve used active learning in any modern review platform, you’ve likely benefited from his research.

The discussion ranges from polyphonic music retrieval to tokenization, from ancient Greek philosophy to the cold‑start problem in TAR, and from contextual diversity to the challenges of evaluating AI systems. Jeremy brings a rare blend of deep technical rigor and practical sensibility, offering a perspective that helps legal professionals understand not just what works, but why it works.

Key Takeaways

• Patterns matter more than keywords. Jeremy’s early work in polyphonic music retrieval mirrors the complexity of legal documents—both require identifying structural patterns, not just surface‑level signals.
  (“Finding those connections historically over time… is very similar to the storytelling and pattern finding we want to do in e‑discovery.”)
• Feature extraction is as important as the algorithm. Tokenization, stemming, and sub‑word representations can make or break a machine learning model’s ability to recognize meaning across documents.
• Outcome‑driven evaluation beats checkbox shopping. Lawyers should focus on how well a system performs on real data—not on whether it claims to use a particular algorithm or technique.

Action Items for Legal Teams

• Evaluate platforms using simulations, not demos. Ask vendors to run your data through their system to measure recall, precision, and learning speed.
• Understand the basics of tokenization. Even a high‑level grasp helps practitioners make better decisions about search and review workflows.
• Adopt CAL for early signal exploitation. Even a single coded document provides useful information—there’s no need for massive seed sets.

Chapters & Timecodes

00:00 – Introduction
Daniel and Brandon introduce Dr. Jeremy Pickens and his impact on the field.

00:03:04 – Jeremy’s Philosophy: Being “Part of the Flow”
Why ideas in e‑discovery evolve collectively, not individually.

00:04:55 – From Polyphonic Music to Legal Documents
How musical pattern analysis informed Jeremy’s approach to information retrieval.

00:08:34 – Short Messages, Semantic Boundaries, and IR Challenges
Why Slack, Teams, and SMS require smarter segmentation techniques.

00:11:03 – Feature Extraction 101
Tokenization, stemming, n‑grams, and why they matter for TAR.

00:14:53 – Sub‑Word Tokenization and OCR
How character‑level patterns help overcome noisy text.

00:17:48 – What Practitioners Should Ask Vendors
Why checklists fail—and what outcome‑driven evaluation looks like.

00:20:34 – The Importance of Frequent Model Updates
How recalculating rankings every two minutes improved precision by up to 20%.

00:22:40 – Why Simulations Are the Missing Piece
Jeremy explains why the industry needs better evaluation frameworks.

00:24:40 – Contextual Diversity: Finding What You Don’t Know
How algorithms identify unexplored pockets of documents.

00:28:56 – Solving the Cold‑Start Problem
Why CAL can begin learning from the very first document.

00:30:01 – Greek Philosophy and TAR
Parmenides vs. Heraclitus as a metaphor for TAR 1.0 vs. TAR 2.0.

Compelling Quote

“You don’t know what you don’t know… and the machine can look globally across the entire collection to find what you’ve never seen before.”

Guest: Amy Abramson

Director, Litigation Solutions & Go‑To‑Market, UnitedLex

Episode Overview

In this insightful conversation, Amy Abramson—a longtime leader at UnitedLex and a driving force behind some of the largest and most complex MDLs in the country—joins Daniel and Brandon to explore how e‑discovery strategy, culture, and technology are evolving together. With more than a decade at UnitedLex, Amy brings a rare blend of legal, operational, and business expertise to the discussion.

The episode dives into how modern discovery has shifted from brute‑force review to evidence‑based strategy, why culture and partnership matter in high‑stakes litigation, and how organizations can modernize their legal operations without losing sight of risk, efficiency, or long‑term goals. Amy also shares candid insights on AI adoption, workflow design, data reuse, and why UnitedLex continues to invest in the NELI community.

Key Takeaways

• Discovery has shifted from volume to strategy. Modern tools and AI allow teams to prioritize key documents early and build evidence‑driven workflows. (“We’re able to take multiple bites at the apple… really able to lead with evidence‑based strategy.”)
• Culture drives outcomes in high‑stakes matters. Trust, transparency, and shared values between service providers, law firms, and corporate clients are essential for meeting deadlines and managing risk.
• Modernization requires clarity and intentionality. Legal departments must understand their data landscape, retention policies, and business goals before investing in new technology.

Action Items for Legal Teams

• Build a repeatable playbook. Standardize privilege, PII, and workflow decisions while leaving room for matter‑specific flexibility.
• Show early wins. Elevate hot documents quickly to build confidence in workflows and AI‑driven approaches.
• Align tech with purpose. Don’t buy AI tools for the sake of AI—define the problem first, then select the right solution.
• Plan modernization over 3–5 years. Evaluate data retention, internal expertise, and IT capacity before deciding what to insource or outsource.

Chapters & Timecodes

00:00 – Introduction
Daniel and Brandon welcome listeners and introduce Amy Abramson.

00:01:52 – Amy’s Career at UnitedLex
How she joined the company right out of law school and grew into a leadership role.

00:02:32 – How the Purpose of e‑Discovery Has Evolved
From search‑term brute force to strategic, evidence‑driven workflows.
(“It’s no longer a badge of honor to say you had 500 people working on a case.”)

00:04:20 – Culture, Values, and Client Partnerships
Why shared values and long‑term relationships matter in complex litigation.

00:06:27 – Managing MDLs and High‑Pressure Matters
How trust, transparency, and tough conversations shape successful outcomes.

00:09:54 – Designing Workflows That Drive Success
The role of playbooks, early wins, and steering committees in building confidence.

00:12:12 – Getting Attorney Buy‑In for AI and CAL
How to address concerns about time, cost, and changing review models.

00:15:22 – The Challenge of Reusing Data
Why consistency matters and how MD5 matching and sampling can help.

00:18:49 – Helping Clients Adopt AI Safely
Understanding goals, vetting tools, and balancing people‑process‑tech.

00:22:12 – Bringing Business Thinking Into Legal Conversations
How Amy’s background in management and marketing shapes her approach.

00:24:41 – The Barriers to Modernization
Data retention, security, BYOD, and the realities of corporate IT.

00:28:33 – Why UnitedLex Supports NELI
A unique environment where judges, lawyers, and technologists learn together.

Compelling Quote

“It’s all still a people‑process‑tech equation… AI isn’t a magic button solution for everything.”

Guest: Steve Davis

Vice President, Forensics & Investigations Practice, Purposely Legal
(“Doing well and good to see you both… always enjoy crossing paths with you.”)

Episode Overview

Digital forensics is evolving faster than ever and returning guest Steve Davis brings a front‑line perspective on how investigators are adapting to a world defined by massive data growth, ephemeral messaging, encryption, and the rise of generative AI. In this episode, Steve breaks down the shifting landscape of evidence collection—from mobile devices and third‑party apps to structured databases and collaboration platforms—and explains why traditional assumptions about “where the data lives” no longer hold.

The conversation also explores the practical realities of modern investigations: how to build a defensible collection plan, how to manage client expectations, and how AI is beginning to transform exfiltration and migration analysis. Steve closes with a candid look at why he keeps returning to NELI and what keeps him energized in such a rapidly changing field.

Key Takeaways

• Data diversity now matters as much as data volume. Investigators must account for mobile apps, collaboration platforms, structured databases, and constantly shifting tool behaviors. (“Things can change literally a week or a month from what we did previously.”)
• Ephemeral messaging isn’t the end of evidence. While deletion is harder to overcome on modern devices, backups, syncs, and other participants’ devices often provide alternative paths to reconstruction. (“If the data is not there, the data is not there… but not necessarily.”)
• Gen AI is poised to reshape forensic analysis. Steve sees major potential in cross‑referencing artifacts, accelerating timeline reconstruction, and identifying patterns in exfiltration investigations. (“I think I’m dead wrong… there’s actually some super interesting things that are happening.”)

Action Items for Legal Teams

• Start every investigation with a structured plan. Identify custodians, platforms, timeframes, and data types before collecting anything.
• Avoid “collect everything” instincts. Large, nonlinear data sources require targeted, defensible scoping to avoid unnecessary cost and noise.
• Prepare clients for the realities of modern forensics. Explain why thorough questioning, planning, and methodical workflows are essential—and why there is no “easy button.”

Chapters & Timecodes

00:00 – Introduction
Daniel and Brandon welcome listeners and reintroduce Steve Davis.

00:02:09 – What’s Changed Since Last Year
Steve explains why digital evidence collection evolves weekly, not yearly.
(“You’ve got to be a student of the game… constantly listen and learn.”)

00:05:21 – The Explosion of Data Types
How investigators help clients navigate diverse platforms, apps, and storage locations.

00:08:31 – Linear vs. Nonlinear Data Challenges
Why collaboration platforms, JSON outputs, and structured databases complicate downstream review.

00:14:23 – Deletion, Encryption, and the Decline of Recoverability
Why SSDs and mobile architectures make deleted data harder to retrieve.

00:17:17 – The Future of Forensics in an Ephemeral World
How backups, syncs, and other participants’ devices can still preserve critical evidence.

00:20:50 – Gen AI’s Emerging Role in Forensics
Steve revises his earlier skepticism and highlights promising applications in migration and exfiltration analysis.

00:24:39 – Discoverability of AI Prompts
A discussion of enterprise vs. consumer AI tools and how prompts, outputs, and source code can be collected.

00:26:57 – Managing Expectations: The Myth of the Easy Button
Why clients often underestimate the complexity of forensic workflows—and how Steve addresses that gap.

Compelling Quote

“You can’t arrive… you’ve got to keep your hand on the pulse and constantly listen and learn.”

NELIPod Episode Summary

Guest: The Honorable Xavier Rodriguez

United States District Court Judge, Western District of Texas

Episode Overview

In this wide‑ranging and deeply practical conversation, Judge Xavier Rodriguez—national authority on e‑discovery, AI, and modern civil procedure—joins Daniel Gold and Brandon Mack to examine how technology continues to reshape litigation. Drawing on his judicial experience, academic work, and decades of practice, Judge Rodriguez offers a candid look at the gaps between the Federal Rules and today’s data landscape, the realities of AI adoption, and the persistent challenges of proportionality.

Key Takeaways

• The Rules haven’t kept pace with modern data. Collaborative platforms, mobile devices, and ephemeral messaging have outgrown the assumptions of the 2015 amendments, creating new complexity in preservation and proportionality. (“The goal has not been able to keep up with collaborative devices… it’s all just increased in complexity.” )
• AI is here to stay—and must be used responsibly. Judge Rodriguez emphasizes validation, human oversight, and transparency, while rejecting blanket bans or unworkable disclosure mandates. (“We’re going to have to adopt a responsible use mentality.” )
• Discovery fights will intensify around AI‑assisted review. Expect disputes over prompts, validation rates, privilege, and sampling—echoes of the TAR wars, but more complex. (“I think it’s going to be even more difficult than the TAR wars.” )

Action Items for Legal Teams

• Document your process. Whether using keywords, TAR, or AI‑driven workflows, maintain clear records of methodology, validation, and decision‑making.
• Be transparent with clients. Inform clients when AI tools are used and obtain consent before uploading sensitive materials. (“I would just be transparent with the client from the get go.” )
• Focus proportionality arguments on marginal utility. Tie requests directly to elements of claims or defenses and articulate why additional data advances the case.

Chapters & Timecodes

00:00 – Welcome & Introductions
Daniel and Brandon open the episode and introduce Judge Rodriguez.

00:01:54 – Why the 2015 Rules Are Struggling Today
Judge Rodriguez discusses the explosion of data sources and the limits of proportionality.
(“The goal has not been able to keep up with collaborative devices… mobile phones, ephemeral messaging.” )

00:03:41 – The Evolution of AI in Legal Practice
How generative AI differs from earlier predictive coding and what responsible use looks like.

00:06:54 – Validating AI‑Assisted Review
The need for human oversight, validation metrics, and realistic expectations.

00:10:34 – Hallucinations, Databases, and Overreaction
Why focusing only on AI failures distorts the conversation.

00:12:32 – Should Courts Require AI Disclosures?
Judge Rodriguez explains why mandatory disclosures are unworkable and what his district is considering.

00:16:00 – Client Communication & Ethics
When and how lawyers should disclose AI use to clients.

00:18:12 – Transparency, TAR Wars, and the Future of E‑Discovery Protocols
A candid look at pre‑production fights, privilege issues, and validation battles.

00:29:52 – Proportionality Done Right
How to argue proportionality effectively—and what wastes judicial time.

00:36:46 – Are Law Schools Preparing Students?
Judge Rodriguez on the gap between legal education and modern practice.

00:41:51 – Why Judge Rodriguez Keeps Returning to NELI
A reflection on community, learning, and the value of the conference.

Compelling Quote

“I’m taking the attitude in my work, hey, there’s some positives here… How can we responsibly adopt some of these AI tools to get to a quicker resolution for our clients with greater accuracy?"