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From February 8th to 10th 2017 the Berlin Legal Tech will take place. The three day event begins with a hackathon, where lawyers and software developers will jointly identify problems and develop solutions. Accompanied by legal knowledge engineers, lawyers with technical expertise, ideas will be generated in an open format, teams created around shared interests and the concepts and prototypes will be pitched in a friendly competition. The most convincing and forward-thinking contributions will be awarded by an expert jury.

The actual conference – the Berlin Legal Tech 2017 – will take place on February 10th. The winners of the hackathon will present their ideas and products and renowned speakers will have the opportunity to give their view on how the digital revolution will affect law and legal practice in the near and far future.

Meet ELTA’s board member Micha Bues at the conference, who is going to attend the conference as a speaker.

For further information, please check: https://berlinlegal.tech/en/

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By Micha Bues

The term „Machine Learning“ was unheard of in most law firms years, or even months ago. Now it seems almost every discussion around the „digital law firm“ or legal tech revolves around this topic. Simply throwing the term “Machine Learning ” into a discussion guarantees attention and excitement. The media continuously reports that Machine Learning will either destroy the legal profession or lift it up to new heights. Comparatively, there has been very little discussion on what this developments actually means for law firms and, perhaps most importantly, how they could get Machine Learning ready.

The term „Machine Learning“ is also often used interchangeably with Artificial Intelligence. Thus before we dive into the question of how law firms could get Machine Learning ready I want to briefly highlight the differences between Machine Learning and Artificial Intelligence.

In short,

  • Artificial Intelligence is the broader concept of machines being able to carry out tasks in a “smart” or „intelligent“ way.
  • Machine Learning is a current application of AI that „gives computers the ability to learn without being explicitly programmed“ (Arthur Samuel, 1959). Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses in prediction-making through the use of computers.

The use of Machine Learning is already changing business in virtually every industry. Even though the likelihood of self-directed, quasi-intelligent computational robots emerging in the foreseeable future is extremely low, Machine Learning can provide huge benefits in the day-to-day business. Over the next 5 to 10 years, the biggest business gains will stem from the gathering and sourcing of data and providing this data in new products and/or business models to the customers/client. Machine Learning will accelerate and facilitate finding patterns and automate value extraction in many areas.

So how can a law firm start to use Machine Learning?

# 1  Step: Analyze business processes

Machine Learning is perfectly suitable for repetitive processes. Therefore, the first step is to analyze processes in a law firm in order to detect tasks, procedures and decisions that are repeated frequently and consistently. This could be, for instance, various tasks in a Due Diligence (DD) process. A DD process comprises of every task, procedure or decision that is done, followed or made from the initial contact with the client and the delivery of the DD report. After having identified these processes it is vital to gather as much data as feasible around them. This is the kind of data that can be used to fuel Machine Learning in the future.

# 2 Step: Understand Machine Learning

Machine Learning won’t be suitable for all processes. It is not a solution for every type of problem. There are a lot of problems and areas where robust solutions may be developed without using Machine Learning techniques. Machine Learning is, for instance, not required if you can determine a target value by using simple rules, computations, or predetermined steps that can be programmed without needing any data-driven learning. Often these robust solution suffice to gain transparency and reliability.

Machine Learning is useful if the set of rules is unclear or follows complex, non-linear patterns. In particular, Machine Learning is helpful where

  • Rule-based solution are inadequate: If a large and overlapping number of factors influences the answer it is impossible to use a simple (deterministic), rule-based solution. It is just too complex to accurately code the rules and to fine tune them. Machine Learning, however, effectively solve this problem; or
  • Large-scale problems arise: ML solutions are effective at handling large-scale problems. A smaller set of data (documents etc.) might be handled manually or with rule-based solution. This however becomes impossible for millions of documents.

# 3 Step: Focus on quick wins

Focus on the low hanging fruit. Automation based on Machine Learning will work best on well defined and understood processes which are not overly complex. In a legal context, focus on tasks, decisions and problems that do not require a lot of in-depth „legal thinking“. Concentrate on tasks that are repetitive and could be performed by literally „everyone“. Surprisingly, there are lot of tasks in a law firm that qualify for Machine Learning testing ground, i.e …

#4 Step: Action

Start testing.

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The joint study on “Digital Economy & Law” prepared by the German Association of General Counsel (Bundesverband der Unternehmensjuristen) and commercial law firm CMS in Germany published in late 2016 addresses the legal challenges presented by digital transformation and the effects on corporate legal departments. For the survey 1,050 companies were contacted, 305 answered the questionnaire, resulting in a return of 29.0 %. Findings are based on the opinions of German corporate legal departments from 25 branches. The study thus represents a broad spectrum of the German economy.

The majority of in-house legal departments (roughly 69.9%) agrees that digital transformation is having a considerable influence on their company. Nonetheless, tendency shows: The larger the company, the stronger the sense of impact. Companies and groups with an annual turnover of EUR 10 billion and more consider that the consequences of digital technology are particularly far-reaching. When asked whether the digital transformation offers more opportunities than risks, there also is a clear picture: Most of those asked expect a positive impact. On a scale of 1 (high risks) to 10 (large opportunities) two-thirds assess the situation at 7 or higher. Conversely, the group which considers that the development conceals risks, is very small at 6.3%.

In-house lawyers still see a long way to go, both with regards to their own abilities and skills, as well as competences relating to digitalisation. For example, only roughly a quarter of in-house legal departments considers that they are “very well” (4.5%) or “well” (23.3%) prepared for the challenges brought about by digital transformation. Nearly half (48.5%) award themselves a 3 (on a German school scale of 1 to 6, 1 being the top mark). The most frequently named reasons given by the in-house legal departments for not being best prepared for digitalisation are as fol-lows: The existing budget is too low and urgently required resources are not available. In addi-tion, the topic of digitalisation has frequently not percolated through sufficiently, so that the measures required are not undertaken. Some other critical issues are: not enough willingness to change, colleagues are too old for the topic, lack of in-service training, slow adaptability.

Today, on average nearly every third member of in-house legal departments (31.4%) is involved with digital topics. They use 1/5 to 2/5 of their available time for aspects and issues relating to digitalisation. Barely 1/5 of those asked (17.1%) have a digital work focus, defined as more than 60% of their time spent on digital aspects. It is agreed that the digital economy requires, among other things, additional competencies, new focuses and more resources. However, not even eve-ry 10th company (9%), is setting aside a higher budget for this aspect. But the few companies which do allocate additional funds for digital transformation in their legal departments are aim-ing to increase their legal budget by quite significant 18.9%.

The answer to the demand for more resources does not have to be an increase in personnel. Thus, 39.9% of those taking part in the study hope to compensate for the extra work caused by digitalisation with improved processes and organisation, including the use of Legal Tech. Thanks to digital technology, it is possible to carry out high-calibre tasks in many areas with the assis-tance of specific software. Hence, legal departments want to make more use of the opportunities offered by Legal Tech. The suggestions often made include: processes which can be standard-ised and which do not required any express legal competence should be outsourced increasingly to shared services platforms. Those responding to the survey consider the greatest potential for the use of shared services platforms to be in the area of reviewing and drafting simple contracts. Recommendations are often given to make available on digital service platforms the work of the legal department and to bundle it on these platforms, provided no specialist know-how is re-quired. Those responding to the survey expect that the use of digital tools and programs will speed up their work and processes. In this way the degree of optimised legal advice will increase and the range of digital services will be extended.

For obtaining the full study (available only in German), please visit the following link.

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