New Laws of Robotics
Defending Human Expertise in the Age of AI
By Frank Pasquale • Cornell Law • 2020 • PROSE Awards Finalist
TL;DR:
Pasquale's four laws for AI governance: complementarity (augment, don't replace), authenticity (don't counterfeit humanity), cooperation (avoid zero-sum arms races), and attribution (traceability for accountability)—preserve human expertise and meaningful work.
Governance Framework for AI
The Four Laws of Robotics
Unlike Asimov's laws (protecting humans from robots), Pasquale's laws govern how humans should develop and deploy AI.
Complementarity
AI should augment professionals, not replace them
Why It Matters
Example: AI helps radiologists diagnose better, doesn't replace them
Authenticity
AI should not counterfeit humanity
Why It Matters
Example: Chatbots must identify as AI, not pretend to be human
Cooperation
AI should not intensify zero-sum arms races
Why It Matters
Example: International agreements on autonomous weapons
Attribution
AI must be traceable to creators/controllers
Why It Matters
Example: Clear responsibility chains for AI decisions
Intelligence Augmentation vs. Replacement
Same technology, radically different deployment choices.
Intelligence Augmentation (IA)
Example:
AI diagnostic system → doctors make better diagnoses
Artificial Intelligence (AI)
Example:
Fully automated diagnostic → radiologists unnecessary
Critical Insight
High-Stakes vs. Low-Stakes Systems
Not all decisions should be algorithmic. Stakes determine whether human judgment is required.
Low-Stakes Systems
Algorithmic decisions acceptable
- Entertainment recommendations
- Ad targeting
- Search results
- Social media feeds
- Shopping suggestions
High-Stakes Systems
Human judgment required
- Criminal sentencing
- Employment decisions
- Healthcare diagnosis
- Loan lending
- University admissions
Professional Expertise Framework
Professional expertise includes more than technical knowledge:
What AI Can Help With:
- Technical knowledge
- Pattern recognition
- Data analysis
- Routine tasks
What Requires Humans:
- Contextual judgment
- Ethical reasoning
- Relationships & trust
- Wisdom & values
Pasquale's Vision
Applying the Four Laws in Practice
Pasquale's framework becomes powerful when you use it to evaluate the AI tools you encounter daily. Here's how each law applies to real-world AI products.
Law 1 in Action: Complementarity
Good Example
GitHub Copilot suggests code completions, but the developer decides what to accept, modify, or reject. The developer's expertise becomes more productive, not obsolete.
Concerning Example
Fully automated hiring systems that screen and reject candidates without human review. The recruiter's contextual judgment is eliminated, not augmented.
Law 2 in Action: Authenticity
Good Example
ChatGPT clearly identifies itself as an AI assistant. Users know they're interacting with a machine and can calibrate their trust accordingly.
Concerning Example
Deepfake voice cloning used in phone scams, impersonating real people. The AI counterfeits humanity to deceive and manipulate.
Your Evaluation Framework
When evaluating any AI tool, ask these four questions — one for each law:
Apply It: Evaluate Your AI Tools
- 1List 3 AI tools you use regularly (e.g. ChatGPT, Copilot, Grammarly, image generators).
- 2For each tool, classify it: Does it practice Intelligence Augmentation (makes you better) or AI Replacement (does the work for you)? Evaluate GitHub Copilot
- 3Apply the stakes framework: For which of your tasks is the AI making high-stakes decisions? Are those decisions getting human review?
- 4Score each tool against Pasquale's four laws (1-5 each): Complementarity, Authenticity, Cooperation, Attribution.
- 5Identify one tool where you could shift from "replacement mode" to "augmentation mode" by changing how you use it.
Frequently Asked Questions
What are Pasquale's Four Laws?▾
What's the difference between IA and AI?▾
Which decisions should remain human?▾
Why does expertise matter?▾
How do we ensure AI augments rather than replaces?▾
Evaluate Tools with Pasquale's Framework
Apply the Four Laws
Apply the Four Laws
Key Insights: What You've Learned
Pasquale's four laws for AI governance provide essential principles: complementarity (augment human expertise, don't replace it), authenticity (don't counterfeit humanity), cooperation (avoid zero-sum arms races), and attribution (ensure traceability and accountability)—these laws preserve human dignity and meaningful work.
Apply these laws by distinguishing high-stakes from low-stakes AI systems, preserving human expertise in critical domains, avoiding deceptive AI that mimics humans, and ensuring transparency and accountability—effective AI governance requires balancing innovation with human values.
Build AI systems that enhance rather than diminish human agency: use AI for augmentation in high-stakes contexts, maintain human oversight, preserve meaningful work, and design systems that respect human expertise—the goal is intelligence augmentation, not replacement.
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