AI, Law, and theFuture of Work
Legal, Ethical & Business Implications
Matthew A. Mishak, Esq.
Founder of LegalTek.ai | Managing Member, Mishak Law, LLC
Overview
Duration
6:00–7:30 PM
Theme
AI Transforming Law & Work
Attorney Matthew Mishak delivered a visionary talk connecting AI's scientific foundations to its modern legal and business implications. The presentation traced AI's evolution from the 1950s to today's generative revolution, highlighting both the promise and responsibility of this new era.
From Curiosity to Capability
"Have you experimented with Generative AI?"
AI is no longer just a tool for programmers — it's now a universal platform empowering every professional to automate, innovate, and expand creative reach.
Founded Mishak Law, LLC
Introduced practice management software, automation, and time-tracking
Attended LegalWeek New York and witnessed the turning point of Generative AI in law
"We speak, it computes. Don't be afraid to try."
A Brief History of Intelligence
Key Sources:
- Max Bennett, A Brief History of Intelligence
- Yuval Noah Harari, Sapiens
Conceptual Bridge:
AI mirrors the biological evolution of intelligence:
- The FoxP2 gene enabled language.
- The brain-to-machine shift represents humanity's leap from carbon to silicon.
- Ray Kurzweil's Law of Accelerating Returns illustrates that human intuition is linear, while AI progress is exponential.
The Farmer and the Lily Pond
An Interactive Demonstration of Exponential Growth
Current Day
1
of 30 days
Lily Pads
1
doubling daily
Pond Coverage
0.0%
of total area
The Critical Insight
Watch the left side fill over 29 days. It seems manageable. Then on Day 30, the right side fills completely—matching 29 days of growth in a single day.
Why This Matters for AI
AI progress follows this exact pattern. Years of gradual improvement, then sudden transformation. By day 60, 17.6 billion ponds would be full. Our linear intuition can't grasp this.
Milestones in AI Development
The Journey from Theory to Reality
Turing Test & Dartmouth Conference
Birth of Artificial Intelligence as a discipline
Geoffrey Hinton – Neural Networks
Backpropagation enables deep learning
IBM Deep Blue defeats Kasparov
Machines surpass human chess champions
ImageNet & AlexNet
Deep learning revolutionizes pattern recognition
Google Transformer Paper – 'Attention Is All You Need'
Foundation for modern LLMs
ChatGPT Launch
Democratized AI for the public
Notable Quotes
"AI is going to change the world more than anything in the history of humankind."
— Kai-Fu Lee
"AI is the most profound technology humanity is working on."
— Sundar Pichai
"You have to learn about AI."
— Mark Cuban
Understanding AI Technologies
Core AI Layers
- Machine Learning – Algorithms that learn from data.
- Deep Learning – Multi-layered neural networks recognizing complex patterns.
- Generative AI – Systems that create text, images, and ideas autonomously.
Top 5 AI Systems Today
- ChatGPT (OpenAI)
- Gemini (Google)
- Grok (xAI – Elon Musk)
- Claude (Anthropic)
- DeepSeek (China)
How Large Language Models (LLMs) Work
Process Flow:
- Tokenization: Breaks text into data units.
- Contextual Understanding: Learns meaning and relationships.
- Next-Token Prediction: Forecasts the next most probable word.
- Response Generation: Produces coherent, human-like replies.
Training Stages:
- Pre-Training: Exposure to vast text corpora ("Reading the Library").
- Fine-Tuning: Focused correction through supervised data ("Tutoring").
- RLHF: Reinforcement Learning from Human Feedback ("Finishing School") to align outputs with human values.
Legal & Ethical Responsibilities
Data Protection Principles
How to Protect Client & Customer Data When Using AI:
COUNSEL Framework
LegalTek's AI Governance Model
Confidentiality
Protect client data at every step
Oversight
Supervise employees and approve AI tools
Understanding
Know what each AI is doing and why
Notification
Inform clients when AI materially affects their case
Scrutiny
Verify accuracy, detect bias, correct hallucinations
Equity
Maintain fairness and transparent billing
Lifelong Learning
Stay educated on emerging risks and technologies
The Future of Work
McKinsey Projection:
By 2030, up to 30% of all work hours could be automated, affecting 375 million workers worldwide.
Knowledge Work
Legal, research, data, and creative automation
Humanoid Robotics
Physical and service-based labor transformation
Transportation
Autonomous logistics, safety, and delivery systems
Jobs defined by empathy, leadership, or creativity will evolve — not disappear.
The AI Alignment Problem
Objective: Ensure AI serves human values.
Three Complementary Approaches:
1. Hinton's "AI That Loves Us"
Build emotional or empathic alignment.
2. Fei-Fei Li's Human-Centered Design
Keep humans in the loop.
3. Technical Governance (Stuart Russell)
Create oversight through transparency and corrigibility.
Together, these define the ethical foundation of responsible AI.
Key Takeaways
Embrace AI
Use it responsibly with safeguards
Use COUNSEL
Apply the LegalTek compliance framework
Keep Learning
Future-proof your firm and your career
"AI + Ethics = The Winning Formula for Modern Legal Practice."
Connect with LegalTek.ai
💡 Consulting Services
AI policy design, governance frameworks, and firm integration