Lawtech and the Transformation of Legal

 

Thoughts on a Round Table Discussion by Richard Susskind and Mark Cohen

by Adam Manning

The acceleration in computing power is unrelentingly accelerating and recent striking examples of artificial intelligence in action have revealed to many the new possibilities that are opening before us. What implications are there for the law and lawyers, and especially the role that law plays in society? These were the focus of a fascinating round table discussion by Richard Susskind, President of the Society for Computers and Law, and Mark Cohen, Executive Chairman of Digital Legal Exchange, moderated by Anusia Gillespie of UnitedLex.

In considering the future of legal services, a key question is, what is the role of law in society? It cannot be just for the benefit of lawyers! Impressively for such a forward-looking arena of thought, mention was made of the jurisprudence of ancient Rome and Mesopotamia, and Mark concluded that law is for societal cohesion, that is the regular and easy functioning of the community. Richard put it in terms of justice, but then wondered how justice applied, for example, in the context of corporate law. One answer might be that, as an example, drawing up and executing a substantial commercial agreement is an exercise in “anticipatory justice”, in the sense of the parties seeking to clarify their relationship and spell out what they expect of each other, in the knowledge that the law will provide remedies if it is breached. Corporate law is justice in a sophisticated, preventative mode, to avoid injustice (that is the breach of contract or law) ever occurring. In this sense, justice and the cohesion of society are not dissimilar.

Yet we live in, the speakers suggested, an age when access to justice is becoming more restricted for so many. Most people, Richard told us, cannot afford access to lawyers and the Courts. How can there be the much-touted rule of law, one of the founding concepts of a modern, democratic society, if in practice many of its citizens cannot easily and effectively have recourse to the Courts or legal advice?

On this point, Mark called for a more customer-centric functioning of legal systems as a way of reversing such a trend. Richard picked the point up by suggesting it was a question of legal design thinking.  Legal systems, including the Courts, must meet the needs of legal users. In my jurisdiction, the legal system has gone through rapid change in recent decades, sweeping away much of the historical legacy of previous centuries. One pertinent example is the rationalisation and clearing up of many of the Court forms needed for legal proceedings.

The 21st Century has seen an ongoing shift to interfacing with the Court system in England and Wales via electronic means, with an online Court system replacing a paper based one. A key theme in legal adaptation must be considering the possibility of entirely or substantially redesigning legal systems, including the Courts, as a result. Simply paralleling an online Court system on the previous paper-based system is not always going to result in an efficient or easy to understand process for the Court user.  Ultimately such profound reform may lead to redrafting the rules of Court and even the law itself. An online Court system, aimed at maximising access to justice for all citizens, could be very different from what we have at present. I know that many people at present find the Court’s implantation of an online system to be difficult and opaque.

When the Courts and the legal system are primarily an online arena, the legal profession must change as well. The great volumes of data required and the enormous advances in artificial intelligence, and our exposure to it, play a role here. As a striking example of what might happen, mention was made of ChatGPT, a recently launched chatbot designed to mimic a human conversationalist. Using ChatGPT, it becomes clear very quickly that it can do so much more than mimic conversation. My first forays were just for fun, and I asked it to rewrite Lord Byron’s poem “She Walks in Beauty” as if the subject were someone walking in the daylight instead of night. Within twenty seconds ChatGPT had done just that, in modern, clear English with an interesting rhyming structure. I was astonished. 

A further humorous suggestion was to write Hamlet’s famous soliloquy in the style of one of Ronnie Corbett’s monologues. Again, within thirty seconds it had done just that, and rather delightfully spun the Bard’s timeless portrayal of existential angst in a laughably stereotypical British manner, suggesting the answer was a good cup of tea and putting your feet up for a bit. “I'm sure everything will look better in the morning.” 

ChatGPT has been a phenomenon as it such a striking example of the new power of artificial intelligence to manipulate words and language. Perhaps somewhat overlooked in comparison to its creative power is the way it is used, which if anything is even more astonishing. To ask it to create these works, the user writes in perfectly normal English. No special training is needed, no understanding of programming a computer is required. “Please rewrite Hamlet's famous soliloquy that begins To be or not to be in the style of a Ronnie Corbett funny story”, and the magic happens.

As amusing as such examples are, to the lawyer there is an immediate analogy with drafting legal documents. Take a precedent and apply new data to it. A ChatGPT of the, perhaps not so far, future could have access to all appropriate statutes, statutory instruments, common law precedents, the whole body of law of the jurisdiction, along with a bank of precedents for legal correspondence, contracts, and Court documents, all for a particular area of law. All you might need to do is ask it, in normal English, to accomplish a task for you and it would draft the document. “Draft the appropriate Court proceedings needed to apply for an order for possession against my client’s commercial tenants currently occupying its premises in Oxford” might be one example. Another might be, “draw up a contract for the supply of my client’s latest range of scientific equipment to the Ministry of Defence’s research establishment.” This doesn’t seem hugely far-fetched for a system that can already creatively combine Shakespeare and Corbett.

To make such powerful lawtech a reality, a great deal of data will be required, and Richard suggested that lawyers of the future will be orientated towards that aspect of the profession, rather than simply knowing how the law and Courts work. To be able to draft such documents or advise on a case, an AI legal system will need data, and so the role of legal data scientists will be important. The professions will have to change and the haunting question of wether the profession of Solicitors will still exist in 2070 hung in the air at one point. Instead of doing the drafting and advising themselves, Richard suggested that lawyers of the future will licence their legal systems to clients for them to use.

Surveying the legal profession of 2023, rather than roughly fifty years in the future, suggests that even law firms that are seeking to embrace these profound changes are only at the foothills. Widescale, innovative disruption will have to take place rather than the more incremental process improvement that is taking place.  We’re still firmly stuck in the first generation of change, a mostly marketing exercise, rather than the more profound revolution of the second generation that Richard described. I couldn’t help imagining Richard setting up his own law firm based on the principles of his second generation, but then it isn’t necessarily the case that the traditional law firm is going to be the source of such substantial change. “The competition that kills you doesn’t look like you”, we were left with. Richard also suggested lawyers and clients could liaise in virtual reality, although he studiously avoided using the M word.

Every other profession must deal with constant change, and it is odd that we as lawyers often think, hope, or pretend that it might be otherwise for us. It had been a rewarding discussion, and I am looking forward to reading Richard Susskind’s book, “Tomorrow’s Lawyers”.

Artificial Intelligence and the Internet of Things – a Legal Scenario

By Adam D.A. Manning LLB, LLM

Artificial Intelligence (AI) already plays a surprisingly large role in our society and economy, from the way mobile phones route calls to financial software predicting or playing the stock market, and will become even more prevalent in the future.  A term used to refer to computer systems that mimic aspects of human intelligence such as taking decision or even learning, AI is here to stay.

Another related, revolutionary advance is the Internet of Things (IoT). Put simply, IoT is interconnecting all sorts of devices, including everyday objects, over the Internet so that they can exchange data.  This can include medical equipment such as pacemakers, beds in hospitals able to detect if someone is lying in them and even smart watches worn to track exercise. It can include devices monitoring infrastructure such as roads, bridges and railway tracks. It is of potentially enormous application and there are estimates of 20 to 30 billion IoT enabled devices by 2020.  One consequence is a huge increase in the amount of data available for access.

In considering the practical implications of these developments, one illustrative scenario could be that unfortunately regular occurrence, the road traffic accident.  Cars are a perfect example of “devices” that could be on the IoT and if so, this might entail a car transmitting constant data about its position, speed, orientation and even whether it has a fault or is damaged and in need of repair.

Imagine also that the roads themselves have sensors embedded in them that can detect similar information about the vehicles travelling on them, such as their position and heading. This might be linked to a CCTV system through fixed position cameras or even drones. Data from the transport infrastructure system might also include information about the conditions of the road, such as whether it is dry or not, and the general prevailing conditions (time of day, bright sunshine, visibility, fog, cloud, wind and so forth).

For the time being, ignore the issue of driverless cars to keep things simpler. Now, on this road of the future, imagine that there has been a nasty accident involving several motor vehicles, in which sadly some of the occupants have been injured.

The data from vehicles and the road network could be transferred to the police force’s computer to determine whether the emergency services were needed to attend at the scene and, if so, in what number. As this is a serious incident, a substantial contingent might be appropriate. As a result, the emergency services might be alerted sooner than any of the humans at the scene or observing might have been able to contact them. 

Once the emergency personnel arrive, their data would be added to the set of information already available from the vehicle and road sensors, including an assessment of the injuries suffered by victims at the scene and more details about the damage to the vehicles, including photo and video imagery. Witness evidence from people at the scene (or later taken at the police station or a victim’s home) would add further data.

The AI system used by the police would then analyse all of this data and consider issues concerning criminal liability. This might involve, in part, the use of an expert system, which takes data and applies decision making processes to it. Expert systems are an established field of AI with a long history and do not represent a radical new advance, apart from perhaps the huge amount of data that a true IoT would provide. 

Whether anyone involved was driving over the speed limit might be a relatively straightforward issue for the system to analyse. The software might also analyse whether any of the drivers were driving in such a way that might be considered dangerous or caused the incident. This analysis might evolve over time as the software begins to recognise features of a situation that to a police officer suggest dangerous driving; true machine learning might be required.

The data set could then be further analysed by the police force’s AI to determine if any of the drivers had breached the criminal law and warranted prosecution as a result. This would involve analysing the witness evidence for weaknesses such as contradictions with the objective data obtained from the vehicles and road sensors. Part of this system would entail natural language comprehension on the part of the AI; that is the system would have to “understand” the text of the witness evidence.

If the police force’s AI determined that the case might warrant prosecution, a recommendation could be made for the case to be forwarded to the Crown Prosecution Service (CPS) for a CPS lawyer to review, possibly with the assistance of the CPS’ AI system. The CPS’s AI could analyse the data relevant to this incident and compare it to its library of similar incidents, reviewing their outcomes and predicting what could happen concerning this particular incident. The conclusion of this analysis would be a recommendation regarding prosecution and the possible offence involved.

With regard to the civil law aspects of the situation, the data would be transferred to the AI system for the insurers for those involved in the incident. The insurer’s AI would analyse all of this data to determine if any of the parties involved had a personal injury or motor vehicle damage claim against any of the others.

This would, as the case progressed, include data from the hospitals, GPs and other medical practitioners involved concerning the nature and extent of the injuries suffered.  At an appropriate point in time, when prognoses were as clear as they could be, the insurers’ AI systems could recommend offers to make to settle the claims and even negotiate settlements based on precedents for the amount of compensation involved.

Data from garages, employers, physiotherapists and others could be included in the claim to ensure full compensation was recovered, including loss of earnings. Insurance companies already use software such as Colossus to value claims; this just takes the process to its ultimate conclusion.

Of course, in reality this system might have regular human supervision to ensure it wasn’t making aberrant decisions, but in principle this could operate quite independently of human intervention. Lawyers, that is human lawyers, might only be involved in very difficult cases where the data, even in this amount, was unclear as to whether there was any issue of liability.

The widespread use of driverless vehicles in the future implies that a lot of the data about the vehicle’s position, speed and heading will be available in any event as it will be needed by the driverless navigation system.  In the event of an incident, the issue of who, if anyone, is prosecuted or liable in a civil sense becomes rather more abstract and it may be that the appropriate tort is one of product liability rather than negligence.

This thought experiment illustrates an example of how an even more data driven digital society might function. It relies on an Internet of Things generating the huge amount of data necessary, the internet as a medium for the exchange of this data and AI systems within our institutions and companies processing it and taking sometimes very serious decisions as a result.