The term 'Artificial Intelligence' or AI, was introduced by John McCarthy in 1956 in the first AI conference. However, even before that, machines were capable of solving problems that were challenging for humans to do so. Today, we can define AI, or Machine Learning, in different ways, but the most common definition is the automation of intellectual tasks which are typically performed by humans.
While not all AI technologies are suited to help with legal processes, there is one that is particularly helpful to Law. Natural Language Processing (NLP) is the subspecialty of AI that allows software to understand natural human language. NLP can be incredibly useful to the legal profession, especially when considering that Law is centred around linguistic analysis; from generating and applying the Law to interpreting precedent and constructing contracts.
AI has advanced as it becomes more sophisticated, and it is now playing a pivotal role in businesses across the globe. As AI is gaining traction, the level of automation (0-10) was created to define the level of automation of each organisation. The metric shows the degree to which a machine will be able to operate different tasks and to what extent humanity will intervene in the machine's operation. In developed states such as the UK, the automation metric is considerably higher; however, it varies when it comes to specific industries. The legal industry, being one of the most traditional ones, started incorporating AI technologies only recently. Regardless, the slow but steady transition has stirred numerous opinions on the matter.
While management teams are enjoying a skyrocketing efficiency of their systems when adopting AI technologies, the staff and jobseekers might be frightened that their skills are becoming obsolete. This is the critical point where the AI community got polarised, and a dispute arises: how much autonomy should we allocate to AI at work?
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Integrating technology in the legal profession is bringing confidence and a significant increase in efficiency. That is especially when it comes to mundane standard tasks that require endless paperwork -automating document management resolves such situations in a matter of seconds. However, the polarisation of the AI community and the ethical questions posed have extended to the legal profession. The polarisation in this occasion gains an entirely new dimension, as fast-developing, rapidly-changing, innovative technologies clash with rigid law practices and possibly a system that is forced to adapt, rather than grow into the new normal. Due to the current controversies and potentially, fear for the unknown changes the integration of technology might bring, many legal professionals are stuck in a 'transition zone,' which bears the question:
Is the legal profession destined to stand still or dive into the modern age of automation?!
The history of the evolution of technology, reveals that this type of reaction has been typical in other traditional industries and individuals who are less receptive to change and risk. The uncertainty involved in adopting a practice that one might not fully understand the mechanics of it explains the hesitation toward digitalisation. However, as legal work becomes increasingly complex, the need for artificial intelligence as a handy tool becomes more prevalent. The need for technological adaptation then requires a careful strategy of incorporating such technologies in a manner that is not intimidating or abstract.
Regarding this issue, I believe the best coping mechanism is for organisations in the legal profession to keep a balance between the human workforce and complex machine learning approaches. Although AI technology is evolving rapidly and the profession has to 'catch up' by training staff and honing innovation, that should be implemented gradually and steadily. When this balance is achieved, the nightmare and stress of coping with AI ends and the workforce can see themselves in wonderland, with machines alleviating the technical tasks.
It is also necessary for the workforce to be educated on technology and understand how it can improve life at work and the industry more broadly. I believe the magic of AI has benefits for ordinary young professionals like me. For example, contract review becomes incremental at the due diligence stage of a corporate acquisition that involves reviewing thousands of contracts on files. The contracts in question can be relatively simple, such as non-disclosure agreements (NDAs), or substantial and complex, stretching to many hundreds of pages. Automated contract review systems can be used to review documents which are relatively standardised and predictable in terms of the types of content. As NLP is the bridge between the natural language and computers, the process involves decomposing the contract into its individual provisions, and then assessing each of them using specific algorithms, either to extract vital information or to compare against some standards which are specified in each case. The technology begins to incorporate aspects of what has become known as legal analytics, aggregating information across the data set to detect anomalies and outliers, and producing charts or tables that make life easier to compare all documents. This service can be life-saving for a client and their legal counsel being in an urgent need of receiving legal advice.
On a societal level, incorporating technology in the industry is also beneficial. For most, getting legal advice is extraordinarily expensive and unaffordable, leading to pro-bono clinics overflowing with work or significant debts for legal fees. However, innovative solutions, such as the DoNotPay app, can alleviate a considerable amount of cases. DoNotPay is the most publicly visible legal advisor: it is an interactive tool that was initially designed to help members of the general public to contest parking tickets (the app was created by Joshua Browder, after receiving a parking ticket). The scope of the application has grown significantly since then. The DoNotPay app supports several different cases in the UK and US, including fighting against unfair bank practices (i.e. charging of overdraft fees, etc. ), getting refunds from Uber and Lyft, or claiming refunds for late package deliveries. While each case has unique facts, most times the success of smaller claims depends on specific, well-defined criteria, which can act as variables in software to produce sound legal advice.
My final thought on the matter is that, as members of the legal industry and future young professionals, we should not be hesitant about the changes AI might bring. Instead, we should be aware of the changes, educate ourselves on the flow of new technologies and embrace the ways an 'automated approach' can improve our work life.
Bibliography
V. Subramanian, Deep Learning with PyTorch, Packt, 2018.