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11 February 2019
"Risk and contract management" may sound boring and tedious to some. However, when it comes to keeping on top of your construction contracts, nothing could be more important. Any tool which assists in this respect and increases the chances for a project's success is therefore essential. When we consider how artificial intelligence (AI) and machine learning may play a part in all of this, we see that the use of these tools is inevitable. It is only a matter of time before they become part and parcel of daily contract and project management routines. If risk and contract management become more reliable, more robust, easier and more efficient through the use of intelligent and automated processes, perhaps they may even become a bit more exciting to some.(1)
Assuming for the moment risk and obligation management is paramount: do you review all contracts before signing, regardless of the value? Do you have an efficient and automated means of monitoring all obligations within all of your contracts and an understanding the differences or anomalies between each one? Is there a system in place which highlights and organises the contractual risks across your contracts and/or automatically alerts you when deadlines are fast approaching? When it comes to disputes, are you able to predict the likely outcome, from a Judge or Adjudicator's point of view, so that you can take an informed decision on how to proceed?
Whilst there is not (and I would suggest there is unlikely to be anytime soon) any one piece of software which will solve all of your problems, there certainly are platforms and technologies available now which utilise AI and machine learning to assist with solutions to some of the questions posed above.
A lot of discussion, and indeed hype, exists at the moment around AI: for example, will robots and machines take over the role and/or services of the lawyer? Rather than continuing this debate, efforts are best placed on focusing on and developing the practical applications of the technologies currently available.
This article looks generally at some of the current technologies available(2) and begins to consider how they may assist in a construction context.
Before jumping feet first into what technologies available and which one(s) you should choose, it is essential to understand first what is AI and what issue are you trying to solve or what efficiency do you want it to improve upon.
To start with, what is AI? Perhaps Deloitte's simple definition is most helpful. AI is:
"the theory and development of computer systems able to perform tasks that normally require human intelligence".(3)
As journalist and author Joanna Goodman summarises:
"Basically, artificial intelligence is about machines (computer software) doing things that are normally done by people."(4)
My personal favourite is the definition provided by Radiant Law(5):-
"A term for when a computer system does magic. "General" artificial intelligence refers to thinking computers, a concept that for the foreseeable future exists only in science fiction and LawTech talks. "Narrow" artificial intelligence refers to a limited capability (albeit one that may be very useful) such as classifying text or pictures, or expert systems. Discussions of AI that blur general and narrow AI are a good indication that you are dealing with bullshit."
That sounds relatively straightforward. So what about all of the other terms out there: for example, machine learning, deep learning and natural language processing? First, it may be useful to know that people often use the term AI generally, to cover a whole range of processes, when in fact they mean only a small subset of AI or perhaps even a technology that does not employ AI at all. Michael Mills, co-founder and chief strategy officer of Neota Logic, defines the field of AI as having seven branches: machine learning, natural language processing, expert systems, vision, speech, planning, and robotics.(6)
Others consider that much of the discussion about AI is actually a discussion about pattern recognition within text and the automation of extracting this text. Therefore, it is not necessarily AI in its purest form. As such, terminology and discussions you come across in the context of legal technology simply may be reference to a particular subset of AI or indeed not AI whatsoever.
Accordingly, rather than starting with the specific AI process, terminology or technology you want to use, identify what it is you want it to do: what is the desired outcome?
What do you want your technology to do? What is the outcome you want?
First, recognise and identify the issue you want to solve, the work stream you want to make more efficient and/or the risk you want to manage. In other words, identify the "use case". Focus on the outcome or the product of AI.
Having first done this, you can then set off shopping for and implementing the appropriate technologies. Only once we identify the outcome required or the problem to be solved, can we harness the various platforms/technologies to realise these objectives.
AI can assist with a number of objectives: contract review, document automation, billing and time analysis, research, collaboration platforms, etc. It is also starting to be used to predict the outcome of disputes.(7) The following considers in closer detail contract review/analysis and document automation in the context of construction law.
There are a number of technologies that go some way to assist with contract review and analysis. For example, technologies which read documents for the analysis and extraction of data, each with their own selling points.
One such technology is an artificial intelligence platform for document review, which provides insight into data and contracts. It utilises pattern recognition algorithms to understand text by context and content, not just by key word searches.
Another example goes beyond simple contract clause searching and extraction and generates a detailed party-specific summary of obligations, liabilities and other meta-data from the contracts analysed. Each agreement, and its component issues, is assigned a risk rating based on the organisations' specific risk policies. This automates a degree of the risk analysis and decision making during a contract review process, highlighting those parts of the contract which need to be manually considered and why.
A further technology, amongst other things, provides text analytics solutions and smart search solutions which index unstructured data, inspect and extract data from documents and uncover the connections between them, no matter where the information is stored.
In the context of construction, infrastructure and energy projects it is relatively easy to see how these types of technologies can be instrumental in contract review and analysis. The possibilities are endless, for example:
With greater collaboration between lawyers and their clients and the use of technology such as those listed above, greater efficiency and efficacy is possible for the review and management of contract risks and obligations. An off the shelf product may or may solve the desired objective, but through greater collaboration and innovation, development of tailored solutions and services will, I suggest, minimise risks and improve the management of contract obligations, at a lower cost.
Document automation is also known as "contracting platforms" and are technologies that aim to speed up the generation, negotiation and completion of contract documents between contracting parties.
One such platform automates the generation of the contract and provides live-negotiation and analytics tools. It enables the user to create contract drafts (or contract templates in the first instance) which then can be negotiated with the other contracting party in real-time. Contracts can also be analysed during the negotiation process to see how they have evolved, as compared to the templated precedent. A further platform also offers a contract automation and contract management platform: contract creation, negotiation, e-signing and analytic tools.
Again, collaboration between lawyers and their clients to establish contract templates and workflows for contract negotiations and completion, with the use of AI-enabled technologies, will minimise risks during the contracting process where possible and enhance efficiencies. In the construction industry where standard forms and standard terms and conditions are regularly used, and in an era of the rise of the Smart Contract, it is only a matter time before document automation and the automation of workflows which follow thereafter to achieve a completed contract will become the norm.
This article, Part 1, considered briefly AI and construction law in the context of risk and contract management and just a few of the technologies which are available now to assist in this respect. With greater collaboration between lawyers and clients I suggest AI (to use the general, though not perhaps technically correct, term) can bring greater efficiencies and efficacies to the contract generation, review, analysis and management processes. This is but one use for AI in the context of construction law. Part 2 will consider the use of AI in predicting the outcome of disputes.
Whilst there indeed is a significant amount of hype around AI, I am of the view that AI and construction law are an essential and inevitable partnership: if you are not implementing it now, you certainly will be, to some degree, in the very near future – either by choice or by obligation. In 1996 Richard Susskind was deemed "dangerous" and "insane" for suggesting that email would become the principal means by which clients and lawyers would communicate.(8) The suggestion here that AI soon will be used throughout the legal industry in the context of construction law is not as far-fetched: it is already here.
For further information on this topic please contact Stacy Sinclair at Fenwick Elliott Solicitors by telephone (+44 20 7421 1986) or email (email@example.com). The Fenwick Elliott Solicitors website can be accessed at www.fenwickelliott.com.
This article has been reproduced in its original format from Lexology – www.Lexology.com.
(3) David Schatsky, Craig Muraskin and Ragu Gurumurthy (2014), "Demystifying artificial intelligence", https://dupress.deloitte.com/dup-usen/focus/cognitive-technologies/ what-is-cognitive-technology.html
(6) Michael Mills (2016), "Artificial Intelligence in Law: The State of Play 2016" https://www.neotalogic.com/ wp-content/uploads/2016/04/ Artificial-Intelligence-in-Law-TheState-of-Play-2016.pdf
(7) For example, in October 2017 software developed by a Cambridge start-up company CaseCrunch predicted the outcomes of 775 cases with an accuracy of 86%, while the 112 lawyers' average was 62.3% www.lawgazette.co.uk/practice/robot-beats-human-lawyers-in-outco...
(8) Susskind R., "Legal informatics - a personal appraisal of context and progress", in European Journal of Law and Technology, Vol. 1, Issue 1, 2010. http://ejlt.org/article/view/18/7#_edn2
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