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Artificial Intelligence
Overview
Harry Surden
Assoc. Professor of Law – University of Colorado Law
School
Affiliated Facul...
Artificial Intelligence Overview
1. What is Artificial Intelligence ?
2. Major Artificial Intelligence Techniques
• Rules ...
What is
Artificial
Intelligence?
Artificial Intelligence (AI)
• What is Artificial Intelligence (AI)?
• Using computers to solve problems
• Or make automat...
Limits of Artificial Intelligence
• “Strong” Artificial Intelligence
• Computers thinking at a level that meets or surpass...
Major AI Approaches
Two Major AI Techniques
• Logic and Rules-Based Approach
• Machine Learning (Pattern-Based Approach)
Logic and Rules-
Based AI
Logic and Rules-Based Approach
• Logic and Rules-Based Approach
• Representing processes or systems using logical rules
• ...
Machine
Learning
Machine Learning (Pattern based)
• Machine Learning (ML)
• Algorithms find patterns in data and infer rules on their own
•...
Machine Learning Uses
Self-Driving Vehicles Automated
recommendations
Computer
Translation
Learning
Machine Learning Main Points
Pattern Detection
Data
Self-Programming
Spam or Wanted Email?
System detects patterns in Email
About likely markers of spam
Detected Pattern
Emails with “Earn Cas...
Identification Improves
Algorithm improves in performance
In auto-identifying spam
As it is able to examine more data
And ...
For some (not all) complex tasks
Requiring intelligence
Intelligent Results Without
Intelligence
Can get “intelligent” aut...
People use advanced cognitive skills to
translate
Proxies for Intelligent Results
Without Intelligence
Google finds statis...
Detecting
Patterns
Proxy Principle for Automation
That can serve as
Proxies
For some underlying
Cognitive Task
Learning
Machine Learning Main Points
Pattern Detection
Data
Self-Programming
Summary Major AI Approaches
Two Major AI Techniques
• Logic and Rules-Based Approach
• Machine Learning (Pattern-Based App...
Hybrid Systems
• Many successful AI systems are hybrids of
• Machine learning & Rules-Based Hybrids
• e.g. Self-driving ca...
Humans
+
Computers
Technology Enhancing
(Not Replacing) Humans
>
Humans Alone
Computers Alone
Examples of AI in Law Today
• Machine Learning
• AI in Litigation - E-Discovery and ”Predictive Coding”
• Natural Language...
Limits on Artificial Intelligence
• Artificial Intelligence Accomplishments
• Automate many things that couldn’t do before...
Questions
Harry Surden
Associate Professor of Law
University of Colorado Law School
Affiliated Faculty, Stanford CodeX Cen...
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Harry Surden - Artificial Intelligence and Law Overview

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Harry Surden - Artificial Intelligence and Law Overview

  1. Artificial Intelligence Overview Harry Surden Assoc. Professor of Law – University of Colorado Law School Affiliated Faculty, Stanford CodeX Center
  2. Artificial Intelligence Overview 1. What is Artificial Intelligence ? 2. Major Artificial Intelligence Techniques • Rules and Logic Based Approach • Machine Learning Based Approach • Hybrid System 3. Limits of Artificial Intelligence Today
  3. What is Artificial Intelligence?
  4. Artificial Intelligence (AI) • What is Artificial Intelligence (AI)? • Using computers to solve problems • Or make automated decisions • For tasks that, when done by humans, • Typically require intelligence
  5. Limits of Artificial Intelligence • “Strong” Artificial Intelligence • Computers thinking at a level that meets or surpasses people • Computers engaging in abstract reasoning & thinking • This is not what we have today • There is no evidence that we are close to Strong AI • “Weak” Pattern-Based Artificial Intelligence • Computers solve problems by detecting useful patterns • Pattern-based AI is an Extremely powerful tool • Has been used to automate many processes today • Driving, language translation • This is the dominant mode of AI today ✔ ✘
  6. Major AI Approaches Two Major AI Techniques • Logic and Rules-Based Approach • Machine Learning (Pattern-Based Approach)
  7. Logic and Rules- Based AI
  8. Logic and Rules-Based Approach • Logic and Rules-Based Approach • Representing processes or systems using logical rules • Top-down rules are created for computer • Computers reason about those rules • Can be used to automate processes • Example within law – Expert Systems • Turbotax • Personal income tax laws • Represented as logical computer rules • Software computes tax liability
  9. Machine Learning
  10. Machine Learning (Pattern based) • Machine Learning (ML) • Algorithms find patterns in data and infer rules on their own • ”Learn” from data and improve over time • These patterns can be used for automation or prediction • ML is the dominant mode of AI today
  11. Machine Learning Uses Self-Driving Vehicles Automated recommendations Computer Translation
  12. Learning Machine Learning Main Points Pattern Detection Data Self-Programming
  13. Spam or Wanted Email? System detects patterns in Email About likely markers of spam Detected Pattern Emails with “Earn Cash” More likely to be spam email Can use such detected patterns to make automated decisions about future emails Example: Email Spam Filter “Earn Cash” “Earn Cash” detected in 10% of Spam emails 0% of wanted emails
  14. Identification Improves Algorithm improves in performance In auto-identifying spam As it is able to examine more data And find additional indicia of spam Algorithm is “learning” over time from additional examples Example: Email Spam Filter “Free” Probability of Spam Contains “Free” 70% Spam Contains “Earn Cash” 90% Spam From Belarus 85% Spam
  15. For some (not all) complex tasks Requiring intelligence Intelligent Results Without Intelligence Can get “intelligent” automated results without intelligence By finding suitable Proxies or Patterns
  16. People use advanced cognitive skills to translate Proxies for Intelligent Results Without Intelligence Google finds statistical correlations by analyzing previously translated documents Statistical Machine Translation Produces automated translations using statistical likelihood as a “proxy” for underlying meaning
  17. Detecting Patterns Proxy Principle for Automation That can serve as Proxies For some underlying Cognitive Task
  18. Learning Machine Learning Main Points Pattern Detection Data Self-Programming
  19. Summary Major AI Approaches Two Major AI Techniques • Logic and Rules-Based Approach • Machine Learning (Pattern-Based Approach)
  20. Hybrid Systems • Many successful AI systems are hybrids of • Machine learning & Rules-Based Hybrids • e.g. Self-driving cars employ both approaches • Human intelligence + AI Hybrids • Also, many successful AI systems work best when • They work with human intelligence • AI systems supply information for humans
  21. Humans + Computers Technology Enhancing (Not Replacing) Humans > Humans Alone Computers Alone
  22. Examples of AI in Law Today • Machine Learning • AI in Litigation - E-Discovery and ”Predictive Coding” • Natural Language Processing (NLP) of Legal Documents • Automated contract analysis • Predictive Analytics for Litigation • Machine Learning Assisted Legal Research • Logic and Rules-Based Approaches • Compliance Engines • Expert Systems • Attorney Workflow Rule Systems • Automated Document Assembly
  23. Limits on Artificial Intelligence • Artificial Intelligence Accomplishments • Automate many things that couldn’t do before • Limits • Many things still beyond the realm of AI • No thinking computers • No Abstract Reasoning • Often AI systems Have Accuracy Limits • Many things difficult to capture in data • Sometimes Hard to interpret Systems
  24. Questions Harry Surden Associate Professor of Law University of Colorado Law School Affiliated Faculty, Stanford CodeX Center Twitter: @HarrySurden Email: hsurden@colorado.edu

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