Here is the description: “Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.” Check it out!
TOC ML4Hackers

Program admissions are rolling and applications are due no later than March 25, 2012.  Given that space in the program is limited, applicants are encouraged to submit their application as soon as possible.    APPLY HERE!

If you know someone who might be interested in this exciting new program — please help us spread the word.  Any student at an ABA Accredited law school is encouraged to apply.

For those who have already applied – please note we will be sending out the first round of acceptances to the program in the next few days.

Program Description:
“The MSU / Westminster 21st Century Law Practice London Summer Program is a first of its kind, intensive study of technology, innovation, regulation, entrepreneurship and the international legal marketplace. With the deregulation of lawyers in the United Kingdom and the outgrowth of alternative legal services delivery models, London is poised to become the global leader in the legal services market. Our program will educate students about these new delivery models and help prepare students for the technology infused law jobs of the 21st Century.”

Educational Objectives:
(1) Provide students a comprehensive understanding of the market for legal services as it transitions to a global legal supply chain in the wake of deregulation, economic pressures, and technological innovation.
(2) Prepare students to become practice-ready entrepreneurial lawyers who can leverage information technology in order to operate more efficiently and thereby attract (and retain) clients.
(3) Inspire students to think broadly about future delivery of legal representation and access to justice by exposing them to the innovative legal service delivery models and platforms of the present (and not-too-distant future).

Courses for the 2012 Program:

Legal Information Engineering & Technology – The increasing role of legal information technology in the law practice of today (and the not too distant future) will be highlighted in this course. Students will be exposed to a number of emerging approaches in legal automation, process engineering, informatics / ‘soft’ artificial intelligence (e-discovery, automated document generation), supply chain management, and quantitative legal prediction.

21st Century Law Practice – This course will provide students with an overview of the practice challenges facing lawyers in the 21st century, including economic pressures, technological advancements, increased globalization, international deregulation, and access to justice concerns (for example, reading the work of Richard Susskind, Thomas Morgan, and others).  Building upon this background, the course will then explore a set of case studies to examine a variety of innovative new legal services delivery mechanisms and businesses in the US and the UK, such as Axiom, LawVest, Lawyers2You, LegalZoom, QualitySolicitors, Rocket Lawyer and others that have been created in anticipation of (or in some cases in response to) these practice challenges.  Students will critically assess these legal service providers, and will reflect upon how lawyers and regulators should respond.

The Legal Services Act and UK Deregulation – Students will study the history and impact of the Legal Services Act and deregulation of the profession in the UK with a focus on how the resulting innovations (both regulatory changes and new legal services delivery mechanisms that follow) might be exported to the United States. Also encompassed in this course will be a comparative overview of American and British law governing lawyers and law practice, along with emphasis on globalization pressures faced by the legal profession.

This is very useful paper. If anything, I believe the authors have understated the importance of these questions and this line of research – particularly in light of the broader dynamic of “human v. machine” which I have argued will come to dominate the future of the legal services industry (as well as other professional services).  That does not mean that humans will be replaced writ large but there is some significant displacement coming down the pipeline — see here, here, here, here, here, etc.

Program Description:  “The MSU / Westminster 21st Century Law Practice London Summer Program is a first of its kind, intensive study of technology, innovation, regulation, entrepreneurship and the international legal marketplace. With the deregulation of lawyers in the United Kingdom and the outgrowth of alternative legal services delivery models, London is poised to become the global leader in the legal services market. Our program will educate students about these new delivery models and help prepare students for the technology infused law jobs of the 21st Century.”

Educational Objectives:

My thanks to Neil Rose and all of the LegalFutures.co.uk conference organizers and speakers – it was a very interesting conference. As a byproduct of the modifications to the UK Legal Services Act, change is on the march in the UK legal services market. Keep your eye on these developments — as they may be coming to the US — sooner rather than later.

Artificial Intelligence is the science of making computer software that reasons about the world around it. Humanoid robots, Google Goggles, self-driving cars, even software that suggests music you might like to hear are all examples of AI. In this class, you will learn how to create this software from two of the leaders in the field. Class begins October 10.” Check out the syllabus here. Although I have previously highlighted Academic Earth – I am a little late on this New York Times coverage available here. See also Andrew Ng’s class on Machine Learning (which is also available right now on Academic Earth).

Kevin Slavin argues that we’re living in a world designed for — and increasingly controlled by — algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture.

Community detection in networks is an extremely important part of the broader network science literature. For quite a while, we have meant to highlight the extremely useful review article written by Mason Porter (Oxford) Jukka-Pekka Onnela (Harvard/Oxford) and Peter J Mucha (UNC). Rather than offer our description of the article, we thought it best to highlight commentary on the subject provided by the authors.

For example, in describing the paper over at Harvard’s Complexity and Social Networks Blog Jukka-Pekka Onnela posted the following… “Uncovering the “community” structure of social networks has a long history, but communities play a pivotal role in almost all networks across disciplines. Intuitively, one can think of a network community as consisting of a group of nodes that are relatively densely connected to each other but sparsely connected to other dense groups of nodes. Communities are important because they are thought to have a strong bearing on functional units in many networks. So, for example, communities in social networks can correspond to different social groups, such as family, whereas web pages dealing with a given subject tend to form topical communities.  The concept is simple enough, but it turns out that coming up with precise mathematical definitions and algorithms for community detection is one of the most challenging problems in network science. Recently, a lot of the research in this area has been done using ideas from statistical physics, which has an arsenal of tools and concepts to tackle the problem. Unfortunately (but understandably) relatively few non-physicists like to read statistical physics papers.”

These scholars quote Mark Newman noting “[T]he development of methods for finding communities within networks is a thriving sub-area of the field, with an enormous number of different techniques under development. Methods for understanding what the communities mean after you find them are, by contrast, still quite primitive, and much needs to be done if we are to gain real knowledge from the output of our computer programs.”  They later note “the problem of how to validate and use communities once they are identified is almost completely open.”

Anyway, if you are interested in learning more about this important piece of the network science toolkit … we suggest you read this paper!