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Trends in information technology law: looking ahead to 2016

This piece looks ahead to what we might expect as IT law developments in 2016.

More than most years, looking ahead to what’s in store for IT lawyers next year is all about the big picture: how IT developments will impact businesses generally, and how this will affect what comes across IT lawyers’ desks. Two key words for next year are ‘scale’ and ‘disruption’. IT developments are now at sufficient scale that even year on year increases have an increasingly large impact; and these changes, characterised as ‘digital transformation’ by research consultancy Gartner, will start to disrupt established business patterns more significantly. What’s behind these changes is the rapid market adoption and convergence of artificial intelligence (AI) and the cloud, two separate but related areas of technology development that are transforming IT, each with data at its heart.

Artificial Intelligence

AI, as the convergence of four separate, rapidly advancing machine technologies – processing, learning, perception and control (see Figure 1 below) – will move to the mainstream in 2016.

Machine processing is fuelled Moore’s law, the fifty year old empirical rule the computer processor speeds double every 18 to 24 months. The basic building block of IT, Moore’s law still has some oomph left but is starting to run out of steam as ever higher microprocessor density on the chip produces excess heat and adverse side effects: Intel announced in mid-2015 that its 10nm (nanometre) Cannonlake processor would be delayed until 2017.

Machine learning is the process by which computers teach themselves to carry out pattern recognition tasks without being explicitly programmed. They do this by analysing and processing very large datasets using algorithms called neural networks as they mimic the human brain. For example, a computer may teach itself to recognise a human face by breaking down input information into layers and passing data from layer to increasingly abstract layer until the final output layer can categorise the image as a particular face. What is novel is that the size of the datasets means that the computer itself can generate the rules by which data passes between layers. Voice recognition is another area where machine learning is developing quickly as the error count now has been reduced to below 10% and companies like Apple, Google and Microsoft invest heavily in their Siri, Google Now and Cortana virtual assistants – a growth area for 2016.

Machine learning techniques combine with increasingly powerful and cheap cameras and sensors to accelerate machine perception – the ability of processors to analyse any digital data to accurately recognise and describe people, objects and actions. With internet connected sensors set to increase from 5bn today to between 20bn and 30bn by 2020, machine perception ushers in an era of autonomous machines and machine to machine communication, quietly humming away in the background keeping the lights on and the temperature steady as cities start to become machine enabled, or ‘smart’.

Machine control is the design of robots and other automated machines using better materials and better control mechanisms to enhance the speed, sensitivity and functionality of response. A popular misconception is to anthropomorphise AI along the lines of the movie ‘I Robot’ but AI will enable radically different and improved solutions for day to day tasks.

The combination of these evolutions sets the stage for AI’s rapid advance in 2016 where virtual reality headsets will be a stand-out. An example of AI closer to home for lawyers is IBM’s Watson, whose first legal application, ROSS, is due for release shortly. ROSS has four main components: first, a natural language user interface so everyone can type or speak their question in plain English (“what’s the earliest date I can terminate this contract?”); second, awareness of the context of the question to better analyse the data; third, generation of plain English evidence-based responses ranked from most to least likely; and fourth, ROSS is cognitive – meaning dynamic: it learns from user feedback so next time it is asked the same question its answer will be better.

Machine to machine communication and decision making, driverless cars and other autonomous machines raise important issues for the longer term about legal responsibility for the consequences of acts, omissions and decisions made without immediate human intervention. English law has the flexibility and suppleness to respond to these changes, and the areas of agency/vicarious liability, negligence/duty of care, strict or fault-based liability and perhaps new types of legal person will all be influenced by AI’s development in years ahead.

The Cloud

The cloud – as the convergence of the mobile, social, cloud and data (see Figure 1 below) – represents a genuine paradigm shift. With the number of connected sensors set to rise hugely in the next few years, and Facebook and WeChat active account numbers already at 1.5bn and 0.55bn in 2015, mobile and social well illustrate the point that IT change is now at scale: the internet of things/me/everything will truly arrive in 2016.

Figure 1: Data is at the heart of the rapid development and convergence of AI and the cloud, two separate but related areas that are transforming IT

Hyper-scale data centres – $1bn+ investment, 1m+ square foot buildings housing 100,000+ servers – are the engine rooms of the new computing. Price is driving cloud computing, and at scale the price benefit of public over private cloud can be up to ten times. Cloud service revenues are currently growing at 25% per annum, overall revenues at the large providers are doubling annually, and growth is set to accelerate up to 2020. This is leading to rapid price reduction, which in turn will lead to supply-side consolidation around six or so large providers including Microsoft, Amazon, IBM and Google.

At the same time, enterprise customers are putting more strategic IT workloads into the cloud – cloud enterprise applications are forecast to rise by two-thirds from 20% of the total to 33% by 2018 – so cloud dependency is increasing at the same time as prices fall. This leads to tensions in managing contractual risk, where the supplier wants to limit liability to a few months’ service fees – the best it will ever do is get paid – and the customer wants a higher limit – the worst it could do is lose a critical part of its business. The consequence is that cloud contract liability clauses will be in the spotlight in 2016.

The cloud enables parts of the service to be daisy chained together to make the service that the customer finally gets and any break in the chain can put the whole service at risk, so cloud buy-side lawyers need to look carefully at providers’ subcontractors to ensure resilience.

More and more cloud contracts will cross IT lawyers’ desks in 2016 and falling prices, supplier consolidation, growing customer cloud dependency, liability clauses and subcontracting arrangements are some of the key points for cloud buyers’ lawyers to watch out for this year.


Data is the raw material for and the product of the cloud and AI. Data volumes are growing at the rate of ten times every five years. Harnessing this surging tide to achieve competitive advantage is fuelling the development of big data analytics and AI techniques. Data law – data contracting, intellectual property, and regulation (broadly, data protection, security and sovereignty and sector specific data regulation) – will become increasingly prominent in 2016. This will be driven at the legislative level by the passage of the EU General Data Protection Regulation, EU Network and Information Security Directive and the UK Investigatory Powers Bill; at the political level by growing concerns about physical and cyber terrorism and crime; and through continuing widespread media coverage of data breaches. Microsoft’s November 2015 agreement for Deutsche Telekom to become the Data Trustee for its cloud offering in Germany and shield customer data from US intrusion is the shape of things to come.

Digital transformation

The scale of the changes from AI and the cloud means that Gartner’s ‘digital transformation’ impacts all sectors of the economy from 2016. Figure 2 shows the most recent Gross Value Added (output value less input costs) estimate of UK GDP across eight industry sectors, and where government, retail and distribution, and financial, information and professional services account for 60% (£965bn) of the whole. Digital transformation and disruption start to characterise each sector from 2016.

Figure 2 – Breakdown of UK Gross Value Added by industry, 2013 (total = £1,545.5bn); Source: Figure 2.1, UK Blue Book, 2015 edition, ONS

IT is at the heart of the government’s approach to transforming public services. This includes moving them at scale to the public sector cloud (where HMG has done terrific work on data classification, data security principles and standards) as well as contracting out work previously done within a government department. All this will involve significant IT contract legal work in 2016, whether through G-Cloud, HMG’s cloud services procurement initiative, or in- or out- sourcing.

Internet retail sales now account for 13.4% of all UK retail spending according to the ONS November 2015 Retail Sales Statistical Bulletin and continue to grow much more quickly than overall retail sales: November 2015 saw a 12.7% year on year increase in weekly online spending, compared with 5.0% for overall retail. Within internet retail, mobile commerce is the fastest growing segment, and within that, social m–commerce – buying directly without leaving your social platform – is growing faster still.

Retail and distribution are particularly susceptible to digital transformation and here successful market participants are transitioning from physical to digital where they can – in operations to enable quicker innovation, in business transformation to digital products and personalising the customer experience around her or his data. A second generation consequence of the cloud is to enable development of a whole range of new automated services by assembling cloud computing componentry in innovative ways.

Research consultancy McKinsey in its October 2015 banking annual review predicts that technology-based competition will sharply reduce profits over the next five years in credit cards, car loans, payment processing and many other financial services that do not depend on balance sheet capacity as innovative IT enables more efficient service provision and lower costs for customers. Also in October, electronic currencies received a boost when bitcoin transactions were held VAT exempt by the EU Court of Justice. Equally important for 2016 is the growing recognition that the blockchain, the technology that underpins bitcoin by aggregating computer power through public key cryptography to create an open, shared, immutable accounting record, has use cases far beyond cryptocurrency to applications ranging from asset title databases to counterparty reconciliation in financial transactions.

In UK legal services, digital transformation developments in second half of 2015 saw Denton’s Next Law Labs announce an investment in ROSS (see above); BLP tie-up with RAVN Systems’ AI platform to develop LONald, a property contract robot for issuing light obstruction notices; and Pinsent Mason take control of Cerico, a cloud-based regulatory compliance platform. 2016 will see more deals like this.

Gene edition and quantum computing

Finally, two IT advances from late 2015 which could have more far reaching consequences than even AI and the cloud. The first is ‘gene editing’ – inserting new genes into living cells – where a new approach, called CRISPR Cas9, allows a particular gene to be changed far more quickly than before through a sort of ‘cutting and pasting’ process. This was the subject of a conference in Washington in December 2015 which proposed a moratorium on making inheritable changes to the human genome, an area we will be hearing more about.

Second, in September 2015, Canada’s D-Wave Systems claimed to have developed a working quantum computer. In digital computing, the basic unit of data processing is the bit (binary digit), which at any one time may have one of two values (0 or 1) or occupy one of two states (on or off). Quantum computing seeks to harness the subatomic physics of quantum mechanics where particles may occupy more than one value or state at the same time. Because a qubit (quantum computing’s equivalent of the bit) can have more than one value or be in more than one state simultaneously, quantum computing has the potential to increase the number of computations that can be processed concurrently compared with digital computing, so enhancing computer speed just at the time when Moore’s law may be running out of steam.

Gene editing and quantum computing are just smudges on the horizon at the moment. For 2016 and beyond, it is the legal implications of AI, the cloud, data and digital transformation that will make much of the weather for IT lawyers.

First published in Practical Law, January 2016.


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