LegalTek.ai is an AI-powered legal solutions company founded by Matthew A. Mishak, Esq. We prove you don't have to choose between speed and care, scale and quality, efficiency and ethics. Our mission is to close the justice gap through ethical AI adoption.

What is the COUNSEL Framework?

The COUNSEL Framework is a comprehensive guide for ethical, secure, and agile AI adoption in legal practice, mapped to and operationalizing ABA Formal Opinion 512. COUNSEL stands for: Confidentiality, Oversight, Understanding, Notice, Scrutiny, Equity, and Learning. ABA Formal Opinion 512 does not endorse any vendor or proprietary framework.

What is SilverTung AI Concierge?

SilverTung AI Concierge is a managed AI service for legal professionals that combines human oversight with ethical guardrails and COUNSEL Framework compliance to deliver AI-augmented legal support.

How does AI help close the justice gap?

AI can help close the justice gap by making legal services more accessible and affordable. LegalTek.ai's approach uses ethical AI tools to increase efficiency without sacrificing quality, enabling lawyers to serve more clients and expand access to justice.

What qualifications does LegalTek.ai's founder have?

Matthew A. Mishak, Esq. is an attorney and AI strategist who is a Harvard Business School Executive Education Graduate and MIT Sloan Artificial Intelligence Graduate, combining deep legal expertise with advanced AI knowledge.

90 Minutes · 1.5 Ethics Hours

OUR CLE FOR LAWYERS

AI in the Courts: Sanctions, Candor, and Compliance

Using the COUNSEL Framework

45 Slides

22 Cases Tracked

ABA Opinion 512

45-Slide Presentation Deck

Scroll through the complete CLE curriculum

Opening & Objectives

Slides 1–3

Slide 1

AI in the Courts: Sanctions, Candor, and Compliance

Using the COUNSEL Framework

90 Minutes · 1.5 Ethics Hours
Developed by Attorney Matthew A. Mishak

Slide 2

What This Course Is (and Is Not)

Ethics-focused risk controls for litigation teams
Anchored to ABA Formal Opinion 512 (2024)
Not jurisdiction-specific legal advice
A compliance system — not a technology demo

Slide 3

Learning Objectives

1. Spot the "hallucination risk pattern" that drives sanctions
2. Apply ABA Formal Opinion 512's core duties to courtroom workflows
3. Implement a pre-filing AI verification protocol
4. Draft a client-facing "AI use notice" aligned with Model Rules
5. Build a firm policy using COUNSEL that reduces sanctions risk
6. Understand the "AI evidence" track and proposed Fed. R. Evid. 707

The Sanctions Menu

Slides 4–8

Slide 4

The Trend Line

From Novelty Sanctions to Routine Enforcement

2023: First shock cases
2024: Sanctions spread + appellate posture
2025: Multi-lawyer stacks
2026: Role-based fines + pro hac vice revocation

Slide 5

The Sanctions Menu

Monetary fines ($1,000 – $10,000+)
Fee-shifting to opposing counsel
Striking briefs / motions
Mandatory CLE / AI training
Client notice / service of order
Bar referral / self-reporting
Pro hac vice consequences

Slide 6

The Non-Delegable Signature Rule

"If you signed it, you own it"

Rule 11 / Rule 9011 + inherent authority
Courts reject "I didn't draft it" defense
Verification is the signer's personal duty
Local counsel is not a shield

Slide 7

The Three Failure Modes

(a) Fake case — citation does not exist
(b) Real case, fake quote — citation exists but language is fabricated
(c) Real case, wrong proposition — citation exists but doesn't say what you claim

Slide 8

The "Second Mistake"

Why Sanctions Escalate

Post-inquiry rationalizations
Slow correction or refusal to withdraw
"Spin" instead of immediate errata
Courts punish doubling-down harder than the original error

Sanctions Casebook

Slides 9–24

Slide 9

Wave 1 (2023): The Case That Taught the Profession

Court

S.D.N.Y.

Citation

Mata v. Avianca, Inc., 678 F. Supp. 3d 443 (S.D.N.Y. 2023)

Sanction / Remedy

Monetary sanction + corrective measures

COUNSEL Fix

S (Scrutiny), O (Oversight), L (Learning)

Slide 10

Wave 2 (2024): Sanctions Spread

Court

2d Cir. / E.D. Tex.

Citation

Park v. Kim, 91 F.4th 610 (2d Cir. 2024); Gauthier v. Goodyear, 2024 WL 4882651 (E.D. Tex.)

Sanction / Remedy

Referral + $2,000 + AI education

COUNSEL Fix

S, O, U, L

Slide 11

Wave 3 Early 2025: "It's Not Just One Lawyer"

Court

E.D. Cal. / D. Wyo.

Citation

United States v. Hayes, 2025 WL 235531; Wadsworth v. Walmart, 348 F.R.D. 489

Sanction / Remedy

Tiered sanctions across drafter/signers

COUNSEL Fix

O, S, U

Slide 12

Bunce v. Visual Tech. Innovations

Court

E.D. Pa.

Citation

No. 2:23-cv-01740-KNS, 2025 WL 662398 (Feb. 27, 2025)

Sanction / Remedy

$2,500 + AI/ethics CLE

COUNSEL Fix

U, S, L

Slide 13

Nguyen v. Savage Enterprises

Court

E.D. Ark.

Citation

No. 4:24-cv-00815-BSM, 2025 WL 679024 (Mar. 3, 2025)

Sanction / Remedy

$1,000 (Rule 11 failure)

COUNSEL Fix

Slide 14

Dehghani v. Castro

Court

D.N.M.

Citation

782 F. Supp. 3d 1051 (D.N.M. 2025)

Sanction / Remedy

Monetary + training/self-reporting

COUNSEL Fix

S, L, O

Slide 15

Mid Central v. Hoosiervac LLC

Court

S.D. Ind.

Citation

No. 2:24-cv-00326, 2025 WL 1511211 (May 28, 2025)

Sanction / Remedy

$6,000 (adopted/reduced); "verification is non-optional"

COUNSEL Fix

S, U, L

Slide 16

In re Martin

Court

Bankr. N.D. Ill.

Citation

No. 24 B 13368, 2025 WL 2017224 (July 18, 2025)

Sanction / Remedy

Rule 9011 monetary + mandatory in-person AI training

COUNSEL Fix

U, S, L

Slide 17

Johnson v. Dunn

Court

N.D. Ala.

Citation

No. 2:21-cv-01701-AMM (July 23, 2025)

Sanction / Remedy

Sanctions + disqualification/referral consequences

COUNSEL Fix

O, S

Slide 18

OTG N.Y. v. Ottogi American

Court

D.N.J.

Citation

No. 2:24-cv-07209, 2025 WL 2671460 (Sept. 18, 2025)

Sanction / Remedy

$3,000 + strike/withdrawal consequences

COUNSEL Fix

Slide 19

Noland v. Land of the Free

Court

Cal. App.

Citation

114 Cal. App. 5th 426 (2025)

Sanction / Remedy

$10,000 — fabricated quotes in appellate brief

COUNSEL Fix

S, U

Slide 20

Lacey v. State Farm General Ins.

Court

C.D. Cal.

Citation

2025 WL 1363069 (May 5, 2025)

Sanction / Remedy

Fee-shifting / cost-of-cleanup

COUNSEL Fix

S, O

Slide 21

Ramirez v. Humala

Court

E.D.N.Y.

Citation

2025 WL 1384161 (May 13, 2025)

Sanction / Remedy

"Staff used the tool" pattern

COUNSEL Fix

O, S

Slide 22

Benjamin v. Costco Wholesale

Court

E.D.N.Y.

Citation

779 F. Supp. 3d 341 (2025)

Sanction / Remedy

Client service requirement + deterrence

COUNSEL Fix

S, U, N

Slide 23

Gardner v. Combs & In re Kenney

Court

D.N.J. / La. 5th Cir.

Citation

Gardner (Dec. 15, 2025); Kenney (Oct. 23, 2025)

Sanction / Remedy

Payment plan + self-reporting; CLE mandate + bar referral

COUNSEL Fix

S, N, L

Slide 24

Wave 4 (2026): Multi-Lawyer Sanction Stack

Court

D. Kan.

Citation

Lexos Media v. Overstock.com, No. 22-2324-JAR (Feb. 2, 2026)

Sanction / Remedy

Public admonishments + fines by role + pro hac vice revocation + policy certification

COUNSEL Fix

O, S, L

Opinion 512 + COUNSEL

Slides 25–34

Slide 25

ABA Formal Opinion 512 in One Sentence

AI is permissible, but lawyers must still meet baseline duties

Competence (Rule 1.1)
Confidentiality (Rule 1.6)
Communication (Rule 1.4)
Supervision (Rules 5.1/5.3)
Reasonable fees (Rule 1.5)

Slide 26

COUNSEL Framework Overview

C — Confidentiality
O — Oversight
U — Understanding
N — Notice
S — Scrutiny
E — Equity
L — Learning

Slide 27

C — Confidentiality

Model Rule 1.6

Never paste client secrets into public/consumer GenAI
Approved tools list: green/yellow/red by data sensitivity
Prompt hygiene: use placeholders, keep translation tables in DMS
"Assume prompts persist unless proven otherwise"

Slide 28

O — Oversight

Rules 5.1 / 5.3

No unsupervised AI for legal authority generation
Two-lawyer rule: drafter + independent verifier
Signature block protocol: personal certification
Staff may summarize, but not generate citations without attorney check

Slide 29

U — Understanding

Rule 1.1, Tech Competence

Train on failure modes: hallucinated cases, Franken-citations, fake quotes
Teach RAG vs. raw chat distinction
Ban "citation generation" prompts without mandatory source retrieval
"Asking for citations" is a known hazard

Slide 30

N — Notice

Rule 1.4

Client notice trigger test: cost, confidentiality risk, strategy, or work allocation?
Engagement letter AI addendum template
Court disclosure: only when required by order/rule or to avoid misleading

Slide 31

S — Scrutiny

Rules 3.3/3.1 + Rule 11/9011

No case cited unless a human opens and confirms: exists, says what you claim, quote is verbatim, pincites match
Maintain a citation verification log
Red flags: citation returned only by AI; no docket footprint; quote not found in 60 seconds

Slide 32

E — Equity

Rule 1.5 and Fairness

Do not bill "AI time" as attorney time
Disclose AI tool cost pass-throughs
Document human review for AI-assisted triage, settlement evaluation, risk scoring
Watch for biased proxies in AI decisioning

Slide 33

L — Learning

Continuous Improvement

Quarterly training refresh: 10-minute new-case roundup
Post-incident review: every hallucination → policy update + training vignette
CLE mandates now appearing as sanctions themselves

Slide 34

COUNSEL as a Litigation Pipeline

Intake → Drafting → Verification → Filing → Post-Filing Monitoring
Each step mapped to COUNSEL controls
Build it into existing workflow — don't bolt it on

Court Rules & AI Evidence

Slides 35–40

Slide 35

Standing Orders & Disclosure

Check before filing: judge standing orders, local rules
Require verification of computer-generated content
Some courts mandate AI use disclosure

Slide 36

AI Disclosure in Practice

Treat like ghostwriting or outsourced drafting

Disclose when required by rule/order
Disclose when necessary to avoid misleading court/client
Don't over-disclose — avoid "disclosure theatre"

Slide 37

AI as Evidence: The Deepfake Problem

Moving from "future risk" to active rulemaking
Machine-generated outputs require authentication
Metadata preservation is critical

Slide 38

Proposed Fed. R. Evid. 707

Machine-Generated Evidence

Would apply Rule 702(a)-(d) reliability requirements
Targets machine outputs offered without an expert
Requires foundation for model training/validation

Slide 39

Litigation Practice Tips for AI Evidence

Authenticate all machine-generated content
Preserve metadata and generation logs
Consider expert foundations
Build cross-exam questions about model training/validation

Slide 40

The Two Tracks of AI Risk

Track 1: Filings accuracy & candor — sanctions for hallucinated authority
Track 2: Evidentiary reliability — deepfakes, machine outputs, authentication
Both tracks are accelerating simultaneously

Workshop & Takeaways

Slides 41–45

Slide 41

Workshop: Build Your AI Filing Checklist

Using COUNSEL

Break into pairs
Use the Pre-Filing AI Verification Protocol
Assign roles: Drafter, Verifier, Signer, Backup

Slide 42

Hypothetical #1: Paralegal Research Assistant

A paralegal uses ChatGPT for case research
Three citations are hallucinated
Who gets sanctioned?
What do you do Monday morning?
→ Tie to Ramirez / Wadsworth / Lexos patterns

Slide 43

Hypothetical #2: Urgent TRO Filing

24-hour deadline, AI-drafted brief
Speed vs. verification tension
What must happen before e-filing?
→ The verification protocol doesn't bend for urgency

Slide 44

The Five Non-Negotiables

1. If it's cited, you (a human) must open it and confirm it.
2. If you signed it, you own it — delegation is not a defense.
3. Treat AI as a drafting assistant, never as authority.
4. Protect confidentiality by default — tools, data, consent.
5. Train, audit, and update — courts now order "policy + proof."

Slide 45

Implementation Plan + Resources

One Week to Compliance

Day 1: Adopt the Pre-Filing AI Verification Protocol
Day 2: Publish approved-tools list (green/yellow/red)
Day 3: Add engagement letter AI addendum
Day 4: Run 30-min training with case spotlights
Day 5: Add AI incident response playbook + tabletop exercise

Sanctions Case Tracker

22 cases mapped to COUNSEL controls (2023–2026)

Date	Court	Case	What Broke	Sanction	Remediation	COUNSEL Fix
2023	S.D.N.Y.	Mata v. Avianca, Inc.	Fabricated citations via ChatGPT	Monetary + corrective measures	Corrective distribution	S, O, L
2023	Colo. O.P.D.J.	People v. Crabill	AI-generated fictitious authority	Disciplinary posture	Bar consequences	U, S, L
2024	2d Cir.	Park v. Kim	Nonexistent authority on appeal	Referral consequence	Appellate discipline	S, O
2024	E.D. Tex.	Gauthier v. Goodyear	Failure to verify AI output	$2,000 + AI education	Education requirement	U, S, L
2025	E.D. Cal.	United States v. Hayes	Fictitious authority cited	Sanctions + corrective distribution	Benchmark for later courts	S, U, O
2025	D. Wyo.	Wadsworth v. Walmart	AI drafting without verification	Tiered fines (drafter/signers)	Signature-block accountability	O, S
2025	E.D. Pa.	Bunce v. Visual Tech.	ChatGPT use admitted	$2,500 + CLE requirement	AI/ethics CLE	U, S, L
2025	E.D. Ark.	Nguyen v. Savage Enters.	AI-generated citations	$1,000 (Rule 11)	Rule 11 enforcement	S
2025	D.N.M.	Dehghani v. Castro	Unverified AI output	Monetary + training	Self-reporting elements	S, L, O
2025	C.D. Cal.	Lacey v. State Farm	Repeat AI failures	Fee-shifting / cleanup costs	Special master appointed	S, O
2025	E.D.N.Y.	Ramirez v. Humala	Staff used AI without oversight	Sanctions for supervising attorney	Staff supervision policy	O, S
2025	E.D.N.Y.	Benjamin v. Costco	Unverified AI citations	Client service + deterrence	Client notification required	S, U, N
2025	S.D. Fla.	Versant Funding v. Teras	Multi-counsel AI failure	Inherent authority sanctions	Multi-counsel accountability	O, S
2025	S.D. Ind.	Mid Central v. Hoosiervac	Repeated fake citations	$6,000 (adopted/reduced)	"Verification is non-optional"	S, U, L
2025	D. Colo.	Coomer v. Lindell	AI-generated sanctions	Reported sanctions	Scrutiny enforcement	S
2025	Bankr. N.D. Ill.	In re Martin	Rule 9011 AI violations	Monetary + in-person AI training	Mandatory training	U, S, L
2025	N.D. Ala.	Johnson v. Dunn	Unverified AI output	Disqualification/referral	Non-monetary consequences	O, S
2025	D.N.J.	OTG N.Y. v. Ottogi Am.	AI-generated false citations	$3,000 + strike/withdrawal	Brief striking	S
2025	La. 5th Cir.	In re Kenney, Kerry	AI citations in appellate brief	CLE mandate + bar referral	Appellate discipline	S, L
2025	Cal. App.	Noland v. Land of the Free	Fabricated quotes/citations	$10,000	Appellate sanctions	S, U
2025	D.N.J.	Gardner v. Combs	Structured AI failures	Payment plan + self-reporting	Client packet requirement	S, N, L
2026	D. Kan.	Lexos Media v. Overstock.com	Multi-lawyer AI failures	Fines by role + pro hac vice revocation	Policy certification required	O, S, L

Knowledge Check

Q1. Under ABA Formal Opinion 512, which duty is most directly implicated by feeding client confidential information into a public GenAI tool?

A: Confidentiality (Rule 1.6) and competence/supervision depending on safeguards.

Q2. True/False: If your paralegal used an AI tool to generate citations, you can avoid Rule 11 exposure if you didn't know and didn't prompt the tool.

A: False. Courts repeatedly treat verification as non-delegable for signing attorneys.

Q3. Which COUNSEL element is the direct "antidote" to fabricated quotations?

A: S — Scrutiny (verify quotes against the underlying source).

Q4. Name two common remedial measures, besides money, that appear in hallucination-sanctions orders.

A: Mandatory CLE/training; client notice/service; bar referral; striking briefs; pro hac vice consequences.

Q5. Proposed Fed. R. Evid. 707 would push which reliability framework onto certain machine-generated evidence?

A: The Rule 702(a)–(d) reliability requirements.

Q6. Is it permissible to bill the client for time the AI tool spent generating a draft while you did other work?

A: Bill only for your actual time and ensure overall reasonableness/transparency; not for fictional "AI time."