Tomorrow’s law firm is automated

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Marco Martorana
Studio Legale Martorana, Lucca
info@studiolegalemartorana.it

For few years, now, the expansion of artificial intelligence (AI) systems in the digital age has generated fears about a reduction in employment rates in many sectors, including legal services. This has led some authors to suggest that tomorrow’s lawyer will be a robot. While it is not likely that machines will replace lawyers’ work ‘because the human element of caring, compassion and advocacy cannot be translated into a computer program’,^[1] automation will play a large role in increasing efficiency and diligence in law firms. Tomorrow’s lawyer might not be a robot but, tomorrow’s law firm will nevertheless be automated.

At first glance, two main AI assets are present in law firms - data mining and predictive systems.

Data mining can be defined as ‘the process of discovering interesting and useful patterns, and relationships in large volumes of data.’^[2] In the legal sector, this technology allows for the reading, analysis and extraction of information from a high volume of documents.

By using data mining, lawyers will quickly gain a better understanding of voluminous files, contracts or documents. In this way, they will be able to give clients more accurate legal advice faster.

Indeed, while human beings may easily make mistakes when conducting arduous and repetitive analysis of documents, machine learning systems, by contrast, develop themselves by analysing their own data, leading to progressively more accurate results.

In addition, data mining allows for the extraction of information from analysed documents, leading to the creation of smart digital libraries that will be more exhaustive and continuously updated by AI.

Such libraries will be very useful for feeding predictive AI systems. Predictive algorithms are used to extract jurisprudential threads from previous judicial decisions in similar cases. Using this type of technology in law firms consequently allows for improvement in the accuracy of legal advice. This is even more important in common law legal systems where the stare decisis principle of law is of fundamental importance.

However, the way an algorithm produces a decision is always conditioned by how that algorithm has been determined in the first place. Ethical concerns can therefore easily arise in the question of how predictive algorithms may extract jurisprudential threads.

Another way to use data mining and predictive systems is to verify whether an adopted decision complies with specific guidelines. The main characteristic of data mining is that of making explicit the relationship between the various factors taken into consideration in a decision-making process. Data mining will therefore be helpful in verifying whether these factors are consistent with guideline directives.

Lawyers, and legal sector actors more generally, are often reluctant about technological evolution. This is even more the case today, when many fear being replaced by AI. However, as mentioned above, the use of data mining and predictive systems is crucial for adding efficiency to a firm’s time management and accuracy to advice given to clients.

The main risk for lawyers, therefore, is not that of being replaced by AI, but rather that of missing the opportunities presented by new technologies and falling behind the lawyers and law firms using automated systems.

In conclusion, while AI is unlikely to be a threat to lawyers, fear of AI might be.

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