Introduction to Legal Technology, lecture 1 (2015)
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Transcript of Introduction to Legal Technology, lecture 1 (2015)
TLS0070 Introduction to Legal Technology
Lecture 1 Introduction University of Turku Law School 2015-01-13 Anna Ronkainen @ronkaine [email protected]
Welcome! ...on a journey to the unknown. (Really, I have no idea what will actually come out of this. Caveat auditor.)
So, what is this? - not a course about the legal regulation of
technology (save for lecture 8) - not your average legal theory course (even if the
teacher is a legal theorist...)
- it’s about technology (ICT) as it relates to the practice of law
- existing technology but even more so future technology, and the changes it will bring to the legal profession – and your career
- 1st course of its kind in Nordics/Baltics (?)
http://www.americanbar.org/publications/law_practice_magazine/2014/july-august/teaching-the-technology-of-practice-the-10-top-schools.html
Meanwhile, across the pond:
Look who’s talking Anna Ronkainen - a lawyer at least on paper (LL.M., U of Cph);
also studied EE/CS, linguistics; researcher in computational legal theory (U of Hki)
- Chief Scientist and co-founder, Onomatics Inc. - worked in the software industry since the early
1990s - my knowledge of practical lawyering comes from just very little in-
house work (and a lot of films and TV), so please correct me whenever I’m wrong...
So, why this now? - in 1995, lawyers didn’t use e-mail – and
were vehemently against the whole idea - ... and now ... - in 2035, who knows? (and if you’re in law school now, you
probably expect to practice well into the 2050s) - what we do know is that a change is
underway – and where it’s coming from – and that’s what this course is all about
- for example: legal startups have gone from about 20 to about 500 in the past 5 years
Course format - 10 lectures (2 h each) on Tuesdays between
14 and 18 (check the schedule!) - attendance not mandatory but strongly
recommended (20% of grade) - final paper: 2500–4000 words (80% of
grade) - required reading: Richard Susskind:
Tomorrow’s Lawyers (OUP 2013) and some articles (see Moodle)
Lesson plan (1/2) 1. Introduction. On law and technology. What is
legal technology? (Jan 13, 16–18) 2. Artificial intelligence and law: the 20th century
(Jan 27, 14–16) 3. Artificial intelligence and law: the 21st century
(Jan 27, 16–18) 4. Human factors: What does AI tell us about legal
reasoning in general? Human-computer interaction (Feb 3, 14–16)
5. Legal technology now: information retrieval, electronic discovery, knowledge management (Feb 10, 14–16)
Lesson plan (2/2) 6. Legal technology now: case management, online dispute
resolution, access to justice (Feb 17, 14–16) 7. Legal technology now: decision support, prediction,
automation, self-service (Feb 17, 16–18) 8. Ethical and regulatory questions. AI and IP law. Big data
and data protection (Feb 24, 16–18) 9. Legal technology in the future: emerging technologies,
innovation, disruption and legal startups (Mar 3, 14–16) 10. Legal technology and you: the impact of legal technology
on the legal profession, new business models for legal services and alternative business structures, unauthorized practice versus liberalization (Mar 10, 14–16)
Lecture etiquette - please interrupt me! - but say your name at least once a day when
you do
- use electronic devices if you absolutely have to (for taking notes, looking up relevant stuff etc)
Required reading - Susskind book chapters and/or articles given
on Moodle for each lecture - not going to go all Socratic on you... - ... but reading the indicated things at least
cursorily before each lecture should make it a lot easier to understand the lectures
- and of course you’ll need them for the paper, supplemental readings also indicated
Final paper - 2500–4000 words (10–16 pages) - to be returned on Moodle by Apr 10 - topic and form must be approved by the lecturer in
advance - possible topics (non-exhaustive list):
- some specific technology and its application to law - some specific field of law or type/stage of legal
practice and the current/potential application of technology in it
- thorough analysis of 1–2 existing legal startup(s) - business plan for your own future legal startup
Communications protocols - in person (somewhere here for about 1 h
before each lecture (except 14:00–14:15)) - Moodle - Twitter: @ronkaine #legaltechturku - if you absolutely must: email
[email protected] - my blog: http://www.legalfuturology.com/
(posts tagged ltcourse)
What is technology? - τέχνη ‘art, skill, craft’ + -λογία ‘study of’ - “Technology is society made durable” (Bruno
Latour) - ”technologies of power” (Michel Foucault) - the practical application of knowledge to a
particular area - “the collection of tools, including machinery,
modifications, arrangements and procedures used by humans” (yay Wikipedia!)
What is legal technology? - technology (mainly ICT) used
- in courts - in legal practice - for doing things which conventionally have
required the assistance of a lawyer - ...
What kind of legal technology does this course (not) cover? - ICT only: no photocopiers, no writing - law-specific only: no e-mail - focus on innovative technologies: no (or very
little) Finlex or LexisNexis
What kind of legal technology does this course cover? - artificial intelligence - machine learning - cloud computing - big data - disruptive - innovative - robot judges - (bingo!)
No, seriously. What types of legal technology does this course cover? Lecture 5: - information retrieval - e-discovery (e-disclosure) - knowledge management Lecture 6: - case management - online dispute resolution - access to justice solutions Lecture 7: - decision support - prediction - automation - self-service
And the other 6.29 lectures? - brief history of the AI and law field - emerging technologies most likely to make
an impact - my own research (sorry, couldn’t resist...)
- professional ethics and regulatory issues - innovation! disruption!! startups!!! - ...and what you can/should do about all this
Susskind (ch. 3): The evolution of legal service 1. bespoke 2. standardized 3. systematized 4. packaged 5. commoditized
1. Bespoke lawyering - the traditional model: everything done
individually for each client - not going to disappear, high-profile litigation
will certainly always have a lot of this - however, its role is diminishing - hourly billing offers no incentives for greater
efficiency to the service provider...
2. Standardized lawyering - ... but who wants to pay for each contract to
be written from scratch (heck, who even wants to actually do that)
- standard document templates - checklists - the bulk of work still done manually
3. Systematized lawyering - same as standardized, only with better tech - e.g. computerized checklists or process
manuals for compliance (workflow systems) - automated document generation, with a
decision tree logic to select the right type of document, using just the necessary inputs
4. Packaged lawyering - systematized lawyering offered so the clients
can use it themselves - tools and information offered online in
ready-made chunks, backed by individual (manual) service
- pricing model innovation by this stage, e.g. based on fees for specific transactions or monthly/annual subscription fees
5. Commoditized lawyering - packaged lawyering minus people, and with
even better tech - offered strictly as a computerized service e.g.
as a web or mobile app - scalable (the same number of people can
provide the service to 1 or 100000 people), can be provided at a radically lower cost
- this is what many (but far from all) legal startups are doing
...and that’s why we’re here - the role of tech grows at each stage and its
importance for legal innovation is unquestionable
- but it’s not everything - an ounce of prevention is worth a pound of
cure! - design thinking now emerging in law - alternative dispute resolution - legal project management
Artificial intelligence (AI) - basically: what people can and computers can’t
(yet) do - when it becomes possible, it generally starts to
be called something else - (no good definition for intelligence of the non-
artificial kind in psychology either, except that it’s whatever IQ tests measure)
- deep AI: general purpose intelligence (cf. the Terminator movies)
- shallow AI: task-specific intelligence (this is where the action is for us in law)
Turing test - the most (but not very) agreed-upon validation
experiment for deep AI - a number of people have to carry a
conversation with a person and a computer without knowing (or the setup revealing) which is which and >30% have to get it wrong
- “passed” by “Eugene Goostman” in 2014 (by lowering expectations by claiming to be a 13-y.o. non-native speaker of English)
- The Imitation Game: in cinemas Feb 20
(the technological) Singularity - the moment when the computing power of
all computers combines exceed that of humankind
- depending on who you believe, the beginning of the total annihilation of humanity or total eternal bliss
- (if you ask me, I think the whole issue is not well-formed)
Moore’s Law - the observation that transistor density in an
integrated circuit doubles every ~2 years (Gordon E. Moore, co-founder of Intel, in 1965)
- has enabled the exponen- tial growth of computer processing capacity - likely to slow down soon
Tests for shallow AI - games, e.g.
- tic-tac-toe - checkers - chess - Jeopardy! - poker (2015!) - go - football (Robo-Cup)
http://xkcd.com/1002/
Rule-based artificial intelligence - also known as Good Old-Fashioned Artificial
Intelligence (GOFAI) - based on symbolic (human-readable)
representations of rules, logic etc. - expert systems - dominant paradigm in AI through the 1980s - still the dominant paradigm in AI & law, but
it too is finally starting to give way to...
Statistical artificial intelligence Machine learning - algorithms created by learning a model of the
target domain from data typically using some general-purpose algorithm - supervised learning - unsupervised learning - reinforcement learning
- the dominant paradigm in most areas of AI for a couple of decades now
- enabled by advances in processing capacity and better availability of teaching data (Big Data)
Which methods are the best for law? - the best (in my opinion: the only) way forward
is to use both where they are best - rule-base methods are easy to implement and
maintain - statistical methods can better accommodate
real-world complexity - vast majority of AI & law research done in rule-
based frameworks (or pure theory), statistical methods quickly emerging
- (more about this in Lecture 4)