Artificial Intelligence&

LawSameer Khan

Centre for Neural and Cognitive SciencesUniversity of Hyderabad

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● Enhancing curriculum ○ Coursework

■ Psychology, reasoning, intelligence, AI■ Rhetoric, persuasion, knowledge representation■ Computer literacy (coding)■ Communication & Systems Theories

○ Culture of Seminars and Colloquia ○ Collaboration

■ Scholar-Scholar vs Student-Teacher relationships

○ Assessment and Evaluation

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● Nature of Algorithms○ Systems perspective○ Memory○ Parallelly Distributed Processing (PDP)

● Nature's Algorithms○ Emergence○ Intelligence○ Law

● Algorithms are Nature○ Experience an algorithm for creativity

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● Judiciary: System of Prescriptive Laws○ Having and maintaining law and order

● Use of AI in law and order situations○ Military and Industrial Grade AI○ Civilian Grade AI

■ Check for plagiarism■ Legal analytics

● Issues of law and order due to AI○ Credit assignment problem○ Jurisprudence issues

Nature of Algorithms: Systems

● System: "A collection of things and relationships between those things"○ Systems may have subsystems and atomized

components ○ Is judiciary a system?○ What are its subsystems and components?○ Is it a part of a larger system?

● What is not a system?

Nature of Algorithms: Memory

● Memory: "persistence of a physical configuration within spacetime"○ A system has memory due to its physicality○ Change in memory entails change in physicality○ Change in memory is "information"

● Parallelly distributed processing: "information processed by networked systems"

Nature of Algorithms

● Algorithm: "set of ordered instructions that channelize information"○ typically, language of mathematics is used to read

and write algorithms○ algorithms can also be considered as cascade of

function mappings ○ any system can implement an algorithm provided

■ the instructions are compatible with system configuration

Nature's Algorithms: Emergence

Complex behavior emerges from simple rules iterated over spacetimedue to stochasticity and dynamism

Nature's Algorithms: Intelligence● Intelligence is an emergent phenomenon

○ Interactivity and reordering within systems to

achieve precision in information processing

■ Processed information can be harbored as

symbol-meaning bindings

■ Processed information contributes to means-

goals mappings

○ Embodiment of such capacities afford the system

certain actions within an environment (situation)

Nature's Algorithms: Law● Nature's algorithms are law

○ Science perspective: A law cannot be broken

○ Scientists excavate such laws and not invent them

■ Laws are described by use of "models"

○ Examples:

■ Entropy: "In this universe, change happens"

Algorithms are Nature: Creativity

● Let us implement and realize an algorithm:○ parallel processors (audience)○ hard disk (paper and pen)

■ randomly choose a sound si from set S = {consonants AND vowels}

■ construct word z = s1s2s3s4 by concatenation over si

■ assign arbitrary meaning to z

Judiciary: System of Prescriptive Laws● Why isn't there a law concerning scratching

your chin with an active chainsaw?● Prescriptions are concerned with efficacious

societal functions○ Politico-socio-economic functions (relations)○ Issues arise due to a multitude of reasons

● Here is one more reason:○ All human relations are technology mediated

■ politico-socio-economic-technological relations

Note: Definition of technology● All that which enhances human capacity is

called technology○ does not endow new capacity

■ weaponry enhances capacity to aggress or withstand aggression

■ language enhances capacity to articulate and reason● words, script, syntax, etc are indeed

technology■ chairs enhance capacity to be lazy

Judiciary: Legal Reasoning and Criteria

● As a whole, is a judicial system an intelligent

system?○ If yes, how?

○ If no, how? (Why are we still using a dumb

system?)

Judiciary: Legal Reasoning and Criteria● Legality implies that there exists a criteria for

assessing veridicality and applicability of a

statement, given a context.

Judiciary: Legal Reasoning and Criteria● Veridical statements applicable in a context

○ Where then did this criteria come from?

○ How was the context ascertained?

○ What form of knowledge representation was

used for expressing the rules?

○ What course of action was taken to implement

the rule? Was the desired realization achieved?

Application of AI: ● Logic: ordered collection of veridical statements

(information)● Context: Knowledge discovery and representation

The above two things can be done by intelligent systems

Example of Industrial Strenght AI: Unmanned Vehicles, Google, BlueGene - Whatson

Application of AI: ● Logic: ordered collection of veridical statements

(information)● Context: Knowledge discovery and representation

[Video of Biomimetic AI]

Application of AI: Legal Analytics ● Logic oriented:

○ Theorem proving algorithms for argument checking

○ Pattern recognition within cases (ontologies)○ Identification of judgment bias

● Context discovery oriented:○ Automated annotation and transcription○ Precedence discovery○ Plagiarism checking (copyright and patent laws)○ Mitigating legalese by

■ "legal language processing"

Application of AI: Legal Systems ● Fully automated arbitration for petty cases and

small claims ○ address backlog of cases in existing legal

system○ realize valid outcomes faster○ global context (bridge issues of jurisprudence)

● ISO Certified Legal Systems!○ Is a judiciary not to be held to international

standards?

Application of AI: Legal Systems ● Artificial immune systems

○ system wide AI■ Police■ Courtroom■ Statements compiled in legal language

Go to a court, put a coin in a jukebox, get a verdict!

Issues Due to AI ● Issues of jurespudence

○ AI like Google is spread all across the globe● Issues of credit assignment (who is responsible)

○ The code was written by umpteen people■ Open sourced and crowd sourced AI

● Issues of uncertainity○ The AI makes use of uncertainty to cope with

uncertainty■ Some output might not be desirable

Discussion● Enhancing curriculum

○ Coursework ■ Psychology, reasoning, intelligence, AI■ Rhetoric, persuasion, knowledge representation■ Computer literacy (coding)■ Communication & Systems Theories

○ Culture of Seminars and Colloquia ○ Collaboration

■ Scholar-Scholar vs Student-Teacher relationships

○ Assessment and Evaluation

Thank youContact:Sameer KhanCNCS, University of HyderabadGachi Bowli 500046

email: samkhan13@gmail.com