SlideShare a Scribd company logo
Modeling meaning and
knowledge: legal knowledge
Anna Ronkainen
Chief Scientist, TrademarkNow Inc
@ronkaine
2016-04-25
My professional background
-  studies in EE/CS, law, linguistics, will finish
my LL.D. in legal theory eventually (all
articles published already)
-  worked in language technology
development since 1995
-  misc stints in academia, including teaching
IP law here and legal tech in U of Turku
-  co-founded TrademarkNow (originally
Onomatics) in 2012
Law is just a bunch of rules, right?
if steal_thing
then go_to_jail
Think about buying a cup of coffee...
Simple enough, right?
-  order
-  pay
-  drink and leave (not necessarily in that
order)
Then think about all the legal issues
involved
-  (un?)specified amount of liquid with
somewhat specified qualities changes owner
Then think about all the legal issues
involved
-  (un?)specified amount of liquid with
somewhat specified qualities changes owner
-  what about ownership of the container?
-  a non-exclusive lease to use some part of the
premises for some amount of time?
-  probably a packet of sugar at no extra cost,
maybe two, or a kilo?
-  plus all the liability issues...
Of course you can also engineer away
all the uncertainties...
...but that kind of limits your options
-  conceptual vagueness is an intrinsic part of
pretty much any situation worth analyzing in
legal terms
-  often it is hidden from view thanks to
human cognition, which is why legal theory
has focused on the most contentious cases
-  but it is unescapable in computational
modelling even for easy/unproblematic cases
Why?
”As we know, there are known knowns. There
are things we know we know. We also know
there are known unknowns, that is to say, we
know there are some things we do not know.
But there are also unknown unknowns, the
ones we don’t know we don’t know.”
– Donald Rumsfeld (2002)
(Un)known (un)knowns
known	
unknowns	
known	
knowns	
unknown	
unknowns	
??
(Un)known (un)knowns
known	
unknowns	
known	
knowns	
unknown	
unknowns	
unknown	
knowns
(Un)known (un)knowns
conscious	
ignorance	
conscious	
knowledge	
unconscious	
ignorance	
unconscious	
knowledge
Dual-process cognition
System 1
•  evolutionarily old
•  unconscious, preconscious
•  shared with animals
•  implicit knowledge
•  automatic
•  fast
•  parallel
•  high capacity
•  intuitive
•  contextualized
•  pragmatic
•  associative
•  independent of general
intelligence
System 2
•  evolutionarily recent
•  conscious
•  distinctively human
•  explicit knowledge
•  controlled
•  slow
•  sequential
•  low capacity
•  reflective
•  abstract
•  logical
•  rule-based
•  linked to general intelligence
(Frankish	&	Evans	2009)
Systems 1 and 2 in legal reasoning:
interaction
System 1:
making the
decision
System 2:
validation and
justification
(Ronkainen	2011)
These are few of my
favourite things...
Classical	(crisp)	logic	
0																																																																																	1	
						no																																																																															yes
Fuzzy	logic	
0																																							0.5																																					1	
						no																																					meh																																			yes
Fuzzy	logic	
0				0.1																													0.5																											0.9					1	
hell	no					no																										meh																									yes			hell	yes
Second-order/Type-2	fuzzy	logic	
		0.1±0.1																					0.5±0.2																					0.9±0.1	
													no																												meh																													yes
Systematizing Estonian laws through
self-organization
-  project carried out at Tallinn U of Tech by
Täks et al
-  legal acts modelled as term vectors (based
on occurrences of individual words in each
document) which are used to generate a
self-organizing map (SOM, Kohonen)
-  provides a 2-dimensional map of
hypothetical (and also actual) relationships
between statutes
(Täks	&	Lohk	2010)
(Täks	&	Lohk	2010)
Ontologies in law
-  Valente’s functional ontology (1995):
-  norms (normative knowledge)
-  things, events, etc. (world knowledge)
-  obligations (responsibility knowledge)
-  legal remedies (reactive knowledge: penalties,
compensation)
-  rules of legal reasoning (meta-legal knowledge,
e.g. lex specialis)
-  legal powers (creative knowledge)
-  (and several others)
Segment from the E-Courts ontology
(Breuker	et	al	2002)
E-courts top-level ontology
(Breuker	et	al	2002)
Use of ontologies
-  always exist in a specific context, built for that
(no Begriffshimmel and no point in aiming for
one)
-  can be generated by hand or by machine
-  two very different ontologies can work just as
well (no Right Answer!)
-  very useful for information retrieval (find similar
things that are called something else)
-  can also be used e.g. for similarity metrics
-  categorization hierarchy also interesting from a
cognitive perspective (basic-level concepts etc.)
Modeling meaning and
knowledge: legal knowledge
Anna Ronkainen
Chief Scientist, TrademarkNow Inc
@ronkaine
2016-04-25
Questions?
Thank you!
A few words about
commercializing academic
research...
The real innovator’s dilemma
1.  do research
2.  ...
3.  profit!
Research commercialization is difficult
in general – not only for AI & law
-  innovation and commercialization are tossed
around as vital research policy goals a lot these
days pretty much wherever you go
-  said tossers* tend to treat it as a black box,
basically thinking that telling academics to be
innovative is all it takes
-  there are two parts in the equation, and only
one of them can be said to be the academics’
responsibility
* sorry, couldn’t resist
Why research commercialization fails
-  most such ventures fail for a simple reason: putting the
cart before the horse
-  solution looking for a problem, not the other way
around
-  academics (typically) don’t have a very commercially
oriented mindset
-  perhaps most importantly, product design and
management are often left out of the equation
altogether
-  basic research is a fairly blunt instrument: research end-
product (good enough for publication) very different
from a marketable and commercially viable product
The first part of the equation:
What academics can do about it
-  consider potential uses even when planning
and carrying out basic research
-  and of course there’s also applied research:
for legal tech, a lot of general AI/NLP stuff
just waiting to be (tried out to see if it can
be) used (cf. e-discovery)
-  try to take an active role in seeking out
potential partners for commercialization (no
time for that, I know...)
Applied and basic research:
Pasteur’s quadrant
Quest for
fundamental
understanding? yes
Pure basic
research
(Bohr)
Use-inspired
basic research
(Pasteur)
no
-
Pure applied
research
(Edison)
no yes
Considerations of use?
(Stokes 1997)
The other part of the equation:
The people with the actual problems
-  you are more likely to end up with a viable
product when you start with a problem and
use research to look for a solution, not the
other way around
-  the initiative should come from someone
who has experienced the pain points first
hand – or at least people who can see an
inefficiency, have an idea about what to do
about it, and can figure out how to fill in the
blanks
Questions?
Thank you!

More Related Content

What's hot

Helsinki Legal Tech Meetup introduction
Helsinki Legal Tech Meetup introductionHelsinki Legal Tech Meetup introduction
Helsinki Legal Tech Meetup introduction
Anna Ronkainen
 
What is legal technology?
What is legal technology?What is legal technology?
What is legal technology?
Anna Ronkainen
 
Introduction to Legal Technology, lecture 3 (2015)
Introduction to Legal Technology, lecture 3 (2015)Introduction to Legal Technology, lecture 3 (2015)
Introduction to Legal Technology, lecture 3 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 10 (2015)
Introduction to Legal Technology, lecture 10 (2015)Introduction to Legal Technology, lecture 10 (2015)
Introduction to Legal Technology, lecture 10 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 8 (2015)
Introduction to Legal Technology, lecture 8 (2015)Introduction to Legal Technology, lecture 8 (2015)
Introduction to Legal Technology, lecture 8 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 1 (2015)
Introduction to Legal Technology, lecture 1 (2015)Introduction to Legal Technology, lecture 1 (2015)
Introduction to Legal Technology, lecture 1 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 2 (2015)
Introduction to Legal Technology, lecture 2 (2015)Introduction to Legal Technology, lecture 2 (2015)
Introduction to Legal Technology, lecture 2 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 4 (2015)
Introduction to Legal Technology, lecture 4 (2015)Introduction to Legal Technology, lecture 4 (2015)
Introduction to Legal Technology, lecture 4 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 7 (2015)
Introduction to Legal Technology, lecture 7 (2015)Introduction to Legal Technology, lecture 7 (2015)
Introduction to Legal Technology, lecture 7 (2015)
Anna Ronkainen
 
Querying Patent Data for Empirical Scholarship : Tools and Strategies
Querying Patent Data for Empirical Scholarship : Tools and StrategiesQuerying Patent Data for Empirical Scholarship : Tools and Strategies
Querying Patent Data for Empirical Scholarship : Tools and Strategies
Professor Jon Cavicchi, UNH School of Law
 
Patent Database Mining and Patent Information Management
Patent Database Mining and Patent Information Management Patent Database Mining and Patent Information Management
Patent Database Mining and Patent Information Management
spkowalski
 
Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research.
Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research. Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research.
Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research.
Professor Jon Cavicchi, UNH School of Law
 
Search strategy analysis
Search strategy analysisSearch strategy analysis
Search strategy analysis
amirabella
 
Introduction to IP Research Tools & Strategies
Introduction to IP Research Tools & StrategiesIntroduction to IP Research Tools & Strategies
Introduction to IP Research Tools & Strategies
Professor Jon Cavicchi, UNH School of Law
 
Presentatie Tilt September 2010
Presentatie Tilt September 2010Presentatie Tilt September 2010
Presentatie Tilt September 2010
frankvogt
 
Career Resources to Help Find Jobs in the Intellectual Property Area of Law
Career Resources to Help Find Jobs in the Intellectual Property Area of LawCareer Resources to Help Find Jobs in the Intellectual Property Area of Law
Career Resources to Help Find Jobs in the Intellectual Property Area of Law
Professor Jon Cavicchi, UNH School of Law
 
Patentability Search- Importance and How to Do Patentability Search
Patentability Search- Importance and How to Do Patentability SearchPatentability Search- Importance and How to Do Patentability Search
Patentability Search- Importance and How to Do Patentability Search
TT Consultants
 
Flyer 03.042015 REVISED
Flyer 03.042015 REVISEDFlyer 03.042015 REVISED
Flyer 03.042015 REVISED
Teesta Jain
 
Bradford Careers Week 2008 Slide Show
Bradford Careers Week 2008 Slide ShowBradford Careers Week 2008 Slide Show
Bradford Careers Week 2008 Slide Show
guestf711b5
 
Copy Right issue in computer software and hardware and IP
Copy Right issue in computer software and hardware and IPCopy Right issue in computer software and hardware and IP
Copy Right issue in computer software and hardware and IP
muhammadshahid2047
 

What's hot (20)

Helsinki Legal Tech Meetup introduction
Helsinki Legal Tech Meetup introductionHelsinki Legal Tech Meetup introduction
Helsinki Legal Tech Meetup introduction
 
What is legal technology?
What is legal technology?What is legal technology?
What is legal technology?
 
Introduction to Legal Technology, lecture 3 (2015)
Introduction to Legal Technology, lecture 3 (2015)Introduction to Legal Technology, lecture 3 (2015)
Introduction to Legal Technology, lecture 3 (2015)
 
Introduction to Legal Technology, lecture 10 (2015)
Introduction to Legal Technology, lecture 10 (2015)Introduction to Legal Technology, lecture 10 (2015)
Introduction to Legal Technology, lecture 10 (2015)
 
Introduction to Legal Technology, lecture 8 (2015)
Introduction to Legal Technology, lecture 8 (2015)Introduction to Legal Technology, lecture 8 (2015)
Introduction to Legal Technology, lecture 8 (2015)
 
Introduction to Legal Technology, lecture 1 (2015)
Introduction to Legal Technology, lecture 1 (2015)Introduction to Legal Technology, lecture 1 (2015)
Introduction to Legal Technology, lecture 1 (2015)
 
Introduction to Legal Technology, lecture 2 (2015)
Introduction to Legal Technology, lecture 2 (2015)Introduction to Legal Technology, lecture 2 (2015)
Introduction to Legal Technology, lecture 2 (2015)
 
Introduction to Legal Technology, lecture 4 (2015)
Introduction to Legal Technology, lecture 4 (2015)Introduction to Legal Technology, lecture 4 (2015)
Introduction to Legal Technology, lecture 4 (2015)
 
Introduction to Legal Technology, lecture 7 (2015)
Introduction to Legal Technology, lecture 7 (2015)Introduction to Legal Technology, lecture 7 (2015)
Introduction to Legal Technology, lecture 7 (2015)
 
Querying Patent Data for Empirical Scholarship : Tools and Strategies
Querying Patent Data for Empirical Scholarship : Tools and StrategiesQuerying Patent Data for Empirical Scholarship : Tools and Strategies
Querying Patent Data for Empirical Scholarship : Tools and Strategies
 
Patent Database Mining and Patent Information Management
Patent Database Mining and Patent Information Management Patent Database Mining and Patent Information Management
Patent Database Mining and Patent Information Management
 
Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research.
Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research. Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research.
Shift This!: A Paradigm for Integrating Law School & Law Firm Patent Research.
 
Search strategy analysis
Search strategy analysisSearch strategy analysis
Search strategy analysis
 
Introduction to IP Research Tools & Strategies
Introduction to IP Research Tools & StrategiesIntroduction to IP Research Tools & Strategies
Introduction to IP Research Tools & Strategies
 
Presentatie Tilt September 2010
Presentatie Tilt September 2010Presentatie Tilt September 2010
Presentatie Tilt September 2010
 
Career Resources to Help Find Jobs in the Intellectual Property Area of Law
Career Resources to Help Find Jobs in the Intellectual Property Area of LawCareer Resources to Help Find Jobs in the Intellectual Property Area of Law
Career Resources to Help Find Jobs in the Intellectual Property Area of Law
 
Patentability Search- Importance and How to Do Patentability Search
Patentability Search- Importance and How to Do Patentability SearchPatentability Search- Importance and How to Do Patentability Search
Patentability Search- Importance and How to Do Patentability Search
 
Flyer 03.042015 REVISED
Flyer 03.042015 REVISEDFlyer 03.042015 REVISED
Flyer 03.042015 REVISED
 
Bradford Careers Week 2008 Slide Show
Bradford Careers Week 2008 Slide ShowBradford Careers Week 2008 Slide Show
Bradford Careers Week 2008 Slide Show
 
Copy Right issue in computer software and hardware and IP
Copy Right issue in computer software and hardware and IPCopy Right issue in computer software and hardware and IP
Copy Right issue in computer software and hardware and IP
 

Viewers also liked

Ethical machines: data mining and fairness – the optimistic view
Ethical machines: data mining and fairness – the optimistic viewEthical machines: data mining and fairness – the optimistic view
Ethical machines: data mining and fairness – the optimistic view
Anna Ronkainen
 
Product management – what makes or breaks a startup
Product management – what makes or breaks a startupProduct management – what makes or breaks a startup
Product management – what makes or breaks a startup
Anna Ronkainen
 
Tulevaisuus on jo täällä
Tulevaisuus on jo täälläTulevaisuus on jo täällä
Tulevaisuus on jo täällä
Anna Ronkainen
 
Product management (at Boost Turku Startup Journey 2015)
Product management (at Boost Turku Startup Journey 2015)Product management (at Boost Turku Startup Journey 2015)
Product management (at Boost Turku Startup Journey 2015)
Anna Ronkainen
 
Tavaramerkki. NYT! IPR-palveluihin uusi ulottuvuus
Tavaramerkki. NYT! IPR-palveluihin uusi ulottuvuusTavaramerkki. NYT! IPR-palveluihin uusi ulottuvuus
Tavaramerkki. NYT! IPR-palveluihin uusi ulottuvuus
Anna Ronkainen
 
Tietokone korvaa juristin – vai korvaako?
Tietokone korvaa juristin – vai korvaako?Tietokone korvaa juristin – vai korvaako?
Tietokone korvaa juristin – vai korvaako?
Anna Ronkainen
 

Viewers also liked (6)

Ethical machines: data mining and fairness – the optimistic view
Ethical machines: data mining and fairness – the optimistic viewEthical machines: data mining and fairness – the optimistic view
Ethical machines: data mining and fairness – the optimistic view
 
Product management – what makes or breaks a startup
Product management – what makes or breaks a startupProduct management – what makes or breaks a startup
Product management – what makes or breaks a startup
 
Tulevaisuus on jo täällä
Tulevaisuus on jo täälläTulevaisuus on jo täällä
Tulevaisuus on jo täällä
 
Product management (at Boost Turku Startup Journey 2015)
Product management (at Boost Turku Startup Journey 2015)Product management (at Boost Turku Startup Journey 2015)
Product management (at Boost Turku Startup Journey 2015)
 
Tavaramerkki. NYT! IPR-palveluihin uusi ulottuvuus
Tavaramerkki. NYT! IPR-palveluihin uusi ulottuvuusTavaramerkki. NYT! IPR-palveluihin uusi ulottuvuus
Tavaramerkki. NYT! IPR-palveluihin uusi ulottuvuus
 
Tietokone korvaa juristin – vai korvaako?
Tietokone korvaa juristin – vai korvaako?Tietokone korvaa juristin – vai korvaako?
Tietokone korvaa juristin – vai korvaako?
 

Similar to Modeling meaning and knowledge: legal knowledge

Scientific and Academic Research: A Survival Guide 
Scientific and Academic Research:  A Survival Guide Scientific and Academic Research:  A Survival Guide 
Scientific and Academic Research: A Survival Guide 
PayamBarnaghi
 
Scientific and Academic Research: A Survival Guide 
Scientific and Academic Research:  A Survival Guide Scientific and Academic Research:  A Survival Guide 
Scientific and Academic Research: A Survival Guide 
PayamBarnaghi
 
Academic Research: A Survival Guide
Academic Research: A Survival GuideAcademic Research: A Survival Guide
Academic Research: A Survival Guide
PayamBarnaghi
 
Research Automation
Research AutomationResearch Automation
Research Automation
Pavel Loskot
 
RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)
RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)
RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)
Michael Zock
 
Task Analysis and User-centered Design.pptx
Task Analysis and User-centered Design.pptxTask Analysis and User-centered Design.pptx
Task Analysis and User-centered Design.pptx
LoredelTamayo2
 
Emerging practices 2019 week 3
Emerging practices 2019 week 3Emerging practices 2019 week 3
Emerging practices 2019 week 3
R. Sosa
 
An Introduction into Philosophy of Science for Software Engineers
An Introduction into Philosophy of Science for Software Engineers An Introduction into Philosophy of Science for Software Engineers
An Introduction into Philosophy of Science for Software Engineers
Daniel Mendez
 
Introduction to ai
Introduction to aiIntroduction to ai
Introduction to ai
Shiwani Gupta
 
Nlp presentation
Nlp presentationNlp presentation
Nlp presentation
Surya Sg
 
One Person's Journey in Practicing Anthropology
One Person's Journey in Practicing AnthropologyOne Person's Journey in Practicing Anthropology
One Person's Journey in Practicing Anthropology
Amy L. Santee
 
Open Innovation: The important of tapping into external expertise
Open Innovation: The important of tapping into external expertise Open Innovation: The important of tapping into external expertise
Open Innovation: The important of tapping into external expertise
Ideon Open
 
Empirical Software Engineering - What is it and why do we need it?
Empirical Software Engineering - What is it and why do we need it?Empirical Software Engineering - What is it and why do we need it?
Empirical Software Engineering - What is it and why do we need it?
Daniel Mendez
 
Lift+fing 09 Michael Shiloh slides with notes
Lift+fing 09 Michael Shiloh slides with notesLift+fing 09 Michael Shiloh slides with notes
Lift+fing 09 Michael Shiloh slides with notes
michaelshiloh
 
Communication Skills in Science: Research in 4 minutes (Rin4)
Communication Skills in Science: Research in 4 minutes (Rin4)Communication Skills in Science: Research in 4 minutes (Rin4)
Communication Skills in Science: Research in 4 minutes (Rin4)
Aurelio Ruiz Garcia
 
9 Questions for Learning Professionals in 2011
9 Questions for Learning Professionals in 20119 Questions for Learning Professionals in 2011
9 Questions for Learning Professionals in 2011
Hans de Zwart
 
Artificial Intelligence PPT.ppt
Artificial Intelligence PPT.pptArtificial Intelligence PPT.ppt
Artificial Intelligence PPT.ppt
DarshRawat2
 
2016 03-16 - viktoria pammer-schindler - designing interactive systems
2016 03-16 - viktoria pammer-schindler - designing interactive systems2016 03-16 - viktoria pammer-schindler - designing interactive systems
2016 03-16 - viktoria pammer-schindler - designing interactive systems
Viktoria Pammer-Schindler
 
Aut tace, Aut Loquere meliora Silentio (and the Likes)
Aut tace, Aut Loquere meliora Silentio (and the Likes) Aut tace, Aut Loquere meliora Silentio (and the Likes)
Aut tace, Aut Loquere meliora Silentio (and the Likes)
Alfonso Pierantonio
 

Similar to Modeling meaning and knowledge: legal knowledge (20)

Scientific and Academic Research: A Survival Guide 
Scientific and Academic Research:  A Survival Guide Scientific and Academic Research:  A Survival Guide 
Scientific and Academic Research: A Survival Guide 
 
Scientific and Academic Research: A Survival Guide 
Scientific and Academic Research:  A Survival Guide Scientific and Academic Research:  A Survival Guide 
Scientific and Academic Research: A Survival Guide 
 
Academic Research: A Survival Guide
Academic Research: A Survival GuideAcademic Research: A Survival Guide
Academic Research: A Survival Guide
 
Research Automation
Research AutomationResearch Automation
Research Automation
 
RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)
RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)
RING panel discussion, Coling 2010 ( E. Hovy + M. Zock)
 
Task Analysis and User-centered Design.pptx
Task Analysis and User-centered Design.pptxTask Analysis and User-centered Design.pptx
Task Analysis and User-centered Design.pptx
 
Emerging practices 2019 week 3
Emerging practices 2019 week 3Emerging practices 2019 week 3
Emerging practices 2019 week 3
 
An Introduction into Philosophy of Science for Software Engineers
An Introduction into Philosophy of Science for Software Engineers An Introduction into Philosophy of Science for Software Engineers
An Introduction into Philosophy of Science for Software Engineers
 
Introduction to ai
Introduction to aiIntroduction to ai
Introduction to ai
 
Nlp presentation
Nlp presentationNlp presentation
Nlp presentation
 
One Person's Journey in Practicing Anthropology
One Person's Journey in Practicing AnthropologyOne Person's Journey in Practicing Anthropology
One Person's Journey in Practicing Anthropology
 
Open Innovation: The important of tapping into external expertise
Open Innovation: The important of tapping into external expertise Open Innovation: The important of tapping into external expertise
Open Innovation: The important of tapping into external expertise
 
Empirical Software Engineering - What is it and why do we need it?
Empirical Software Engineering - What is it and why do we need it?Empirical Software Engineering - What is it and why do we need it?
Empirical Software Engineering - What is it and why do we need it?
 
Lift+fing 09 Michael Shiloh slides with notes
Lift+fing 09 Michael Shiloh slides with notesLift+fing 09 Michael Shiloh slides with notes
Lift+fing 09 Michael Shiloh slides with notes
 
Communication Skills in Science: Research in 4 minutes (Rin4)
Communication Skills in Science: Research in 4 minutes (Rin4)Communication Skills in Science: Research in 4 minutes (Rin4)
Communication Skills in Science: Research in 4 minutes (Rin4)
 
9 Questions for Learning Professionals in 2011
9 Questions for Learning Professionals in 20119 Questions for Learning Professionals in 2011
9 Questions for Learning Professionals in 2011
 
Artificial Intelligence PPT.ppt
Artificial Intelligence PPT.pptArtificial Intelligence PPT.ppt
Artificial Intelligence PPT.ppt
 
What is D&T
What is D&TWhat is D&T
What is D&T
 
2016 03-16 - viktoria pammer-schindler - designing interactive systems
2016 03-16 - viktoria pammer-schindler - designing interactive systems2016 03-16 - viktoria pammer-schindler - designing interactive systems
2016 03-16 - viktoria pammer-schindler - designing interactive systems
 
Aut tace, Aut Loquere meliora Silentio (and the Likes)
Aut tace, Aut Loquere meliora Silentio (and the Likes) Aut tace, Aut Loquere meliora Silentio (and the Likes)
Aut tace, Aut Loquere meliora Silentio (and the Likes)
 

More from Anna Ronkainen

Introduction to Legal Technology, lecture 9 (2018)
Introduction to Legal Technology, lecture 9 (2018)Introduction to Legal Technology, lecture 9 (2018)
Introduction to Legal Technology, lecture 9 (2018)
Anna Ronkainen
 
Introduction to legal design: Product & project management
Introduction to legal design: Product & project managementIntroduction to legal design: Product & project management
Introduction to legal design: Product & project management
Anna Ronkainen
 
Introduction to Legal Technology, lecture 9 (2015)
Introduction to Legal Technology, lecture 9 (2015)Introduction to Legal Technology, lecture 9 (2015)
Introduction to Legal Technology, lecture 9 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 6 (2015)
Introduction to Legal Technology, lecture 6 (2015)Introduction to Legal Technology, lecture 6 (2015)
Introduction to Legal Technology, lecture 6 (2015)
Anna Ronkainen
 
Introduction to Legal Technology, lecture 5 (2015)
Introduction to Legal Technology, lecture 5 (2015)Introduction to Legal Technology, lecture 5 (2015)
Introduction to Legal Technology, lecture 5 (2015)
Anna Ronkainen
 
Technology can transform the law – but only if done right (ReInvent Law Londo...
Technology can transform the law – but only if done right (ReInvent Law Londo...Technology can transform the law – but only if done right (ReInvent Law Londo...
Technology can transform the law – but only if done right (ReInvent Law Londo...
Anna Ronkainen
 
Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...
Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...
Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...
Anna Ronkainen
 

More from Anna Ronkainen (7)

Introduction to Legal Technology, lecture 9 (2018)
Introduction to Legal Technology, lecture 9 (2018)Introduction to Legal Technology, lecture 9 (2018)
Introduction to Legal Technology, lecture 9 (2018)
 
Introduction to legal design: Product & project management
Introduction to legal design: Product & project managementIntroduction to legal design: Product & project management
Introduction to legal design: Product & project management
 
Introduction to Legal Technology, lecture 9 (2015)
Introduction to Legal Technology, lecture 9 (2015)Introduction to Legal Technology, lecture 9 (2015)
Introduction to Legal Technology, lecture 9 (2015)
 
Introduction to Legal Technology, lecture 6 (2015)
Introduction to Legal Technology, lecture 6 (2015)Introduction to Legal Technology, lecture 6 (2015)
Introduction to Legal Technology, lecture 6 (2015)
 
Introduction to Legal Technology, lecture 5 (2015)
Introduction to Legal Technology, lecture 5 (2015)Introduction to Legal Technology, lecture 5 (2015)
Introduction to Legal Technology, lecture 5 (2015)
 
Technology can transform the law – but only if done right (ReInvent Law Londo...
Technology can transform the law – but only if done right (ReInvent Law Londo...Technology can transform the law – but only if done right (ReInvent Law Londo...
Technology can transform the law – but only if done right (ReInvent Law Londo...
 
Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...
Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...
Intelligent Trademark Analysis: Experiments in Large-Scale Evaluation of Real...
 

Recently uploaded

Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...
Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...
Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...
James AH Campbell
 
A slightly oblate dark matter halo revealed by a retrograde precessing Galact...
A slightly oblate dark matter halo revealed by a retrograde precessing Galact...A slightly oblate dark matter halo revealed by a retrograde precessing Galact...
A slightly oblate dark matter halo revealed by a retrograde precessing Galact...
Sérgio Sacani
 
Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...
Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...
Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...
Sérgio Sacani
 
Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...
Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...
Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...
University of Maribor
 
Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...
Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...
Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...
University of Maribor
 
A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....
A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....
A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....
Sérgio Sacani
 
MCQ in Electrostatics. for class XII pptx
MCQ in Electrostatics. for class XII  pptxMCQ in Electrostatics. for class XII  pptx
MCQ in Electrostatics. for class XII pptx
ArunachalamM22
 
Adjusted NuGOweek 2024 Ghent programme flyer
Adjusted NuGOweek 2024 Ghent programme flyerAdjusted NuGOweek 2024 Ghent programme flyer
Adjusted NuGOweek 2024 Ghent programme flyer
pablovgd
 
largeintestinepathologiesconditions-240627071428-3c936a47 (2).pptx
largeintestinepathologiesconditions-240627071428-3c936a47 (2).pptxlargeintestinepathologiesconditions-240627071428-3c936a47 (2).pptx
largeintestinepathologiesconditions-240627071428-3c936a47 (2).pptx
muralinath2
 
2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...
2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...
2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...
khadija07kubra
 
Active and Passive Surveillance of pharmacovigillance
Active and Passive Surveillance of pharmacovigillanceActive and Passive Surveillance of pharmacovigillance
Active and Passive Surveillance of pharmacovigillance
SejalAgrawal43
 
The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...
The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...
The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...
Sérgio Sacani
 
BIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptx
BIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptxBIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptx
BIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptx
alishyt102010
 
Gametogenesis: Male gametes Formation Process / Spermatogenesis .pdf
Gametogenesis: Male gametes Formation Process / Spermatogenesis .pdfGametogenesis: Male gametes Formation Process / Spermatogenesis .pdf
Gametogenesis: Male gametes Formation Process / Spermatogenesis .pdf
SELF-EXPLANATORY
 
The Dynamical Origins of the Dark Comets and a Proposed Evolutionary Track
The Dynamical Origins of the Dark Comets and a Proposed Evolutionary TrackThe Dynamical Origins of the Dark Comets and a Proposed Evolutionary Track
The Dynamical Origins of the Dark Comets and a Proposed Evolutionary Track
Sérgio Sacani
 
Komodo Dragon I PPT
Komodo Dragon I PPT Komodo Dragon I PPT
Komodo Dragon I PPT
alokitapramanik0
 
A mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopy
A mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopyA mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopy
A mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopy
Sérgio Sacani
 
Science-Technology Quiz (School Quiz 2024)
Science-Technology Quiz (School Quiz 2024)Science-Technology Quiz (School Quiz 2024)
Science-Technology Quiz (School Quiz 2024)
Kashyap J
 
HAZARDOUS ENERGIES -LOTO Training Program.pptx
HAZARDOUS ENERGIES -LOTO Training Program.pptxHAZARDOUS ENERGIES -LOTO Training Program.pptx
HAZARDOUS ENERGIES -LOTO Training Program.pptx
ArfanSubhani
 
smallintestinedisorders-causessymptoms-240626051934-b669b27d.pptx
smallintestinedisorders-causessymptoms-240626051934-b669b27d.pptxsmallintestinedisorders-causessymptoms-240626051934-b669b27d.pptx
smallintestinedisorders-causessymptoms-240626051934-b669b27d.pptx
muralinath2
 

Recently uploaded (20)

Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...
Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...
Probing the northern Kaapvaal craton root with mantle-derived xenocrysts from...
 
A slightly oblate dark matter halo revealed by a retrograde precessing Galact...
A slightly oblate dark matter halo revealed by a retrograde precessing Galact...A slightly oblate dark matter halo revealed by a retrograde precessing Galact...
A slightly oblate dark matter halo revealed by a retrograde precessing Galact...
 
Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...
Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...
Transmission Spectroscopy of the Habitable Zone Exoplanet LHS 1140 b with JWS...
 
Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...
Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...
Deploying DAPHNE Computational Intelligence on EuroHPC Vega for Benchmarking ...
 
Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...
Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...
Modelling, Simulation, and Computer-aided Design in Computational, Evolutiona...
 
A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....
A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....
A Strong He II λ1640 Emitter with an Extremely Blue UV Spectral Slope at z=8....
 
MCQ in Electrostatics. for class XII pptx
MCQ in Electrostatics. for class XII  pptxMCQ in Electrostatics. for class XII  pptx
MCQ in Electrostatics. for class XII pptx
 
Adjusted NuGOweek 2024 Ghent programme flyer
Adjusted NuGOweek 2024 Ghent programme flyerAdjusted NuGOweek 2024 Ghent programme flyer
Adjusted NuGOweek 2024 Ghent programme flyer
 
largeintestinepathologiesconditions-240627071428-3c936a47 (2).pptx
largeintestinepathologiesconditions-240627071428-3c936a47 (2).pptxlargeintestinepathologiesconditions-240627071428-3c936a47 (2).pptx
largeintestinepathologiesconditions-240627071428-3c936a47 (2).pptx
 
2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...
2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...
2. Osmotic pressure, osmotic potential, turgor pressure, wall pressure, water...
 
Active and Passive Surveillance of pharmacovigillance
Active and Passive Surveillance of pharmacovigillanceActive and Passive Surveillance of pharmacovigillance
Active and Passive Surveillance of pharmacovigillance
 
The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...
The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...
The cryptoterrestrial hypothesis: A case for scientific openness to a conceal...
 
BIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptx
BIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptxBIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptx
BIOPHYSICS Interactions of molecules in 3-D space-determining binding and.pptx
 
Gametogenesis: Male gametes Formation Process / Spermatogenesis .pdf
Gametogenesis: Male gametes Formation Process / Spermatogenesis .pdfGametogenesis: Male gametes Formation Process / Spermatogenesis .pdf
Gametogenesis: Male gametes Formation Process / Spermatogenesis .pdf
 
The Dynamical Origins of the Dark Comets and a Proposed Evolutionary Track
The Dynamical Origins of the Dark Comets and a Proposed Evolutionary TrackThe Dynamical Origins of the Dark Comets and a Proposed Evolutionary Track
The Dynamical Origins of the Dark Comets and a Proposed Evolutionary Track
 
Komodo Dragon I PPT
Komodo Dragon I PPT Komodo Dragon I PPT
Komodo Dragon I PPT
 
A mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopy
A mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopyA mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopy
A mature quasar at cosmic dawn revealed by JWST rest-frame infrared spectroscopy
 
Science-Technology Quiz (School Quiz 2024)
Science-Technology Quiz (School Quiz 2024)Science-Technology Quiz (School Quiz 2024)
Science-Technology Quiz (School Quiz 2024)
 
HAZARDOUS ENERGIES -LOTO Training Program.pptx
HAZARDOUS ENERGIES -LOTO Training Program.pptxHAZARDOUS ENERGIES -LOTO Training Program.pptx
HAZARDOUS ENERGIES -LOTO Training Program.pptx
 
smallintestinedisorders-causessymptoms-240626051934-b669b27d.pptx
smallintestinedisorders-causessymptoms-240626051934-b669b27d.pptxsmallintestinedisorders-causessymptoms-240626051934-b669b27d.pptx
smallintestinedisorders-causessymptoms-240626051934-b669b27d.pptx
 

Modeling meaning and knowledge: legal knowledge

  • 1. Modeling meaning and knowledge: legal knowledge Anna Ronkainen Chief Scientist, TrademarkNow Inc @ronkaine 2016-04-25
  • 2. My professional background -  studies in EE/CS, law, linguistics, will finish my LL.D. in legal theory eventually (all articles published already) -  worked in language technology development since 1995 -  misc stints in academia, including teaching IP law here and legal tech in U of Turku -  co-founded TrademarkNow (originally Onomatics) in 2012
  • 3. Law is just a bunch of rules, right? if steal_thing then go_to_jail
  • 4. Think about buying a cup of coffee... Simple enough, right? -  order -  pay -  drink and leave (not necessarily in that order)
  • 5. Then think about all the legal issues involved -  (un?)specified amount of liquid with somewhat specified qualities changes owner
  • 6. Then think about all the legal issues involved -  (un?)specified amount of liquid with somewhat specified qualities changes owner -  what about ownership of the container? -  a non-exclusive lease to use some part of the premises for some amount of time? -  probably a packet of sugar at no extra cost, maybe two, or a kilo? -  plus all the liability issues...
  • 7. Of course you can also engineer away all the uncertainties...
  • 8. ...but that kind of limits your options -  conceptual vagueness is an intrinsic part of pretty much any situation worth analyzing in legal terms -  often it is hidden from view thanks to human cognition, which is why legal theory has focused on the most contentious cases -  but it is unescapable in computational modelling even for easy/unproblematic cases
  • 10. ”As we know, there are known knowns. There are things we know we know. We also know there are known unknowns, that is to say, we know there are some things we do not know. But there are also unknown unknowns, the ones we don’t know we don’t know.” – Donald Rumsfeld (2002)
  • 14. Dual-process cognition System 1 •  evolutionarily old •  unconscious, preconscious •  shared with animals •  implicit knowledge •  automatic •  fast •  parallel •  high capacity •  intuitive •  contextualized •  pragmatic •  associative •  independent of general intelligence System 2 •  evolutionarily recent •  conscious •  distinctively human •  explicit knowledge •  controlled •  slow •  sequential •  low capacity •  reflective •  abstract •  logical •  rule-based •  linked to general intelligence (Frankish & Evans 2009)
  • 15. Systems 1 and 2 in legal reasoning: interaction System 1: making the decision System 2: validation and justification (Ronkainen 2011)
  • 16. These are few of my favourite things...
  • 21. Systematizing Estonian laws through self-organization -  project carried out at Tallinn U of Tech by Täks et al -  legal acts modelled as term vectors (based on occurrences of individual words in each document) which are used to generate a self-organizing map (SOM, Kohonen) -  provides a 2-dimensional map of hypothetical (and also actual) relationships between statutes
  • 24. Ontologies in law -  Valente’s functional ontology (1995): -  norms (normative knowledge) -  things, events, etc. (world knowledge) -  obligations (responsibility knowledge) -  legal remedies (reactive knowledge: penalties, compensation) -  rules of legal reasoning (meta-legal knowledge, e.g. lex specialis) -  legal powers (creative knowledge) -  (and several others)
  • 25. Segment from the E-Courts ontology (Breuker et al 2002)
  • 27. Use of ontologies -  always exist in a specific context, built for that (no Begriffshimmel and no point in aiming for one) -  can be generated by hand or by machine -  two very different ontologies can work just as well (no Right Answer!) -  very useful for information retrieval (find similar things that are called something else) -  can also be used e.g. for similarity metrics -  categorization hierarchy also interesting from a cognitive perspective (basic-level concepts etc.)
  • 28. Modeling meaning and knowledge: legal knowledge Anna Ronkainen Chief Scientist, TrademarkNow Inc @ronkaine 2016-04-25
  • 30. A few words about commercializing academic research...
  • 31. The real innovator’s dilemma 1.  do research 2.  ... 3.  profit!
  • 32. Research commercialization is difficult in general – not only for AI & law -  innovation and commercialization are tossed around as vital research policy goals a lot these days pretty much wherever you go -  said tossers* tend to treat it as a black box, basically thinking that telling academics to be innovative is all it takes -  there are two parts in the equation, and only one of them can be said to be the academics’ responsibility * sorry, couldn’t resist
  • 33. Why research commercialization fails -  most such ventures fail for a simple reason: putting the cart before the horse -  solution looking for a problem, not the other way around -  academics (typically) don’t have a very commercially oriented mindset -  perhaps most importantly, product design and management are often left out of the equation altogether -  basic research is a fairly blunt instrument: research end- product (good enough for publication) very different from a marketable and commercially viable product
  • 34. The first part of the equation: What academics can do about it -  consider potential uses even when planning and carrying out basic research -  and of course there’s also applied research: for legal tech, a lot of general AI/NLP stuff just waiting to be (tried out to see if it can be) used (cf. e-discovery) -  try to take an active role in seeking out potential partners for commercialization (no time for that, I know...)
  • 35. Applied and basic research: Pasteur’s quadrant Quest for fundamental understanding? yes Pure basic research (Bohr) Use-inspired basic research (Pasteur) no - Pure applied research (Edison) no yes Considerations of use? (Stokes 1997)
  • 36. The other part of the equation: The people with the actual problems -  you are more likely to end up with a viable product when you start with a problem and use research to look for a solution, not the other way around -  the initiative should come from someone who has experienced the pain points first hand – or at least people who can see an inefficiency, have an idea about what to do about it, and can figure out how to fill in the blanks