Artificial Intelligence and the Law: The Future of Legal Practice (Part 1)
Introduction
Artificial Intelligence (AI) is emerging rapidly as a transformative force across various industries, and the legal profession is no exception to this wave of change, as AI has started to play a significant role in various aspects of legal practice. It has become crucial for legal professionals and aspiring Lawyers to either adapt to the changing dynamics of a technology-driven world, or risk stagnation. This article explores the intersection of artificial intelligence and the law, examining the current state of AI in the legal field, and its potential impact on the future of legal practice.
Meaning of Artificial Intelligence (AI)
Artificial intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as: Learning; Reasoning; Problem-solving; Perception and Natural Language Processing (NLP). It is a machine, computer system or software, designed to think like the human mind. It is created to mimic the cognitive capabilities of the human brain, to complete tasks which would rather require human intelligence. AI algorithms can tackle learning, perception, problem-solving, language understanding and logical reasoning. It encompasses various subfields, including machine learning, natural language processing, computer vision, and robotics, all of which aim to create systems that can exhibit human-like intelligence and behaviour.
John McCarthy first defined the term “Artificial Intelligence”, in 1956, as the development and use of machines to execute tasks which usually required human intelligence. Similarly, Ziyad Saleh of the British University in Egypt sees it as, the ‘intelligence demonstrated by machine in contrast to the natural intelligence displayed by humans and other animals’. Data Robot CEO, Jeremy Achin’s, speech at the 2017 Japan AI Experience, summed up the modern definition of AI. According to Jeremy, “AI is a computer system, able to perform tasks that ordinarily require human intelligence … many of these artificial intelligence systems are powered by machine learning; some of them are powered by deep learning, and very boring things like rules power some of them”.
How Artificial Intelligence Works
But, how do machines learn? Simply put, a subtle illustration can be drawn from how a baby learns to do certain things, by merely observing and learning from how the parents behave. So too, these AI learns from experience, and act accordingly. In the legal context, AI systems have been employed for a variety of applications. AI systems use algorithms and data to learn from experience, adapt to new information, and improve their performance over time.
In order to achieve an AI, scientists draw inspiration from the sensory organs of humans. In AI research, there is the subfield of ‘Natural Language Processing (NLP)’, which makes it possible for computers to read text, hear speech, interpret it, measure thoughts and emotions, and determine which parts are important. There is also ‘Machine Learning (ML)’, an algorithm which is capable of receiving input data and using statistical analysis to glean insight and predict an output. Another subfield is ‘Deep Learning’, which aims to replicate the learning development pathways of humans, with a focus on visual or abstract work and self-improving without human intervention. Therefore, some common examples of AI today include virtual assistants like Siri and Alexa; fraud detection systems in banking; self-driving cars and more.
Types of Artificial Intelligence (AI)
Three types of AI have been classified based on capabilities, to wit:
1. Artificial Narrow Intelligence.
2. Artificial General Intelligence.
3. Artificial Super Intelligence.
A. Artificial Narrow Intelligence (ANI)
This type of AI is also referred to as Narrow AI or Weak AI, and it is a form of artificial intelligence we encounter in our daily lives. Unlike its counterparts, Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI), ANI is already a reality that has made significant contributions to the economic development of nations in recent decades.
In the last decade, Narrow AI has experienced many breakthroughs that have contributed to the economic vitality of nations around the world. ANI can be categorised into two main types: limited memory or reactive AI. The limited memory ANI is more advanced, as it can access historical data, enabling it to make decisions based on past information, much like how humans rely on their memories to make decisions. In contrast, reactive ANI lacks data storage or memory capability, but it can respond to various stimuli without any prior experience, similar to the way the human mind reacts to new situations.
In the contemporary landscape, most AI systems fall under the category of limited memory ANI. These AI systems use stored data for deep learning and excel in performing specific tasks. Examples of Narrow AI encompass a wide range of applications, including drone robots, virtual assistants like Siri, Alexa, and Cortana, Google’s Rankbrain, social media monitoring tools, facial and image recognition software, personalised Netflix recommendations, self-driving cars, and disease mapping tools. For clarification and reference, it is important to note that much of the AI mentioned in this discussion, falls under the category of “Narrow AI.” This means that these AI systems are designed for specific purposes, and do not possess the broad cognitive capabilities that are associated with higher-level artificial intelligences like AGI and ASI.
B. Artificial General Intelligence (AGI)
This type of AI is also known as Deep AI or Strong AI, and it represents a level of machine intelligence that possesses the capability to tackle a wide array of tasks with human-like intelligence. Unlike its narrow counterparts (ANI), AGI goes beyond mere task-specific learning, and has the ability to think and understand in a manner similar to humans. This advanced cognitive capacity is underpinned by a framework known as, the “theory of mind AI.”
The “theory of mind AI” framework, is an essential aspect of AGI. It refers to the AI’s ability to not only mimic human actions, but also to discern and comprehend human emotions, needs, thought processes, and beliefs. In essence, it allows AGI to engage with humans on a deeper level, approaching human-level understanding and empathy.
To successfully develop AGI, researchers and scientists face the formidable challenge of programming machines to possess a broad spectrum of cognitive abilities. This is no small task, as it goes beyond the limitations of mimicking human-like actions, and involves instilling machines with the capacity to truly understand humans, their emotions, and their intentions.
However, it’s important to note that, achieving Deep AI is fraught with numerous difficulties. Unfortunately, several difficulties, such as the inability to replicate essential functions of movement and sight, mar the quest for Deep AI. Experts at the NSTC Committee on technology agreed that, Deep AI seems impossible to achieve for the next decades.
C. Artificial Super-intelligence (ASI).
This is a hypothetical type of AI. At this stage, AI does not just understand or mimic human intelligence; it surpasses human intelligence. In the words of Nick Bostrom, the Swedish author of “Super intelligence: Paths, Dangers, Strategies”, defined ASI as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom, and social skills.” While the core concept of Artificial Intelligence revolves around computers replicating human thought processes, the notion of artificial super-intelligence transcends this, by envisioning a scenario where computers possess cognitive abilities that vastly surpass those of humans.
Artificial Super Intelligence (ASI) has long served as a central theme in dystopian fictional works where machines, often in the form of robots, pose existential threats to human civilisation. Prominent examples of such narratives can be found in movies like “Ex Machina”, “2001: A Space Odyssey”, “Metropolis”, and “Interstellar.” Despite these dystopian visions, it’s crucial to recognise that the development of advanced AI, including ASI, remains in its nascent stages. Imagining a world dominated by highly intelligent AI systems may be challenging at present, because current AI technologies are still in their infancy.
For about a decade, there has been massive investment in the development of AI. Google has invested massively in Bard while OpenAI Global Incorporation is investing massively in AI, too. Sometime in July, 2023, Elon Musk, CEO of Tesla and SpaceX, and owner of “X” (formerly Twitter), announced the debut of a new AI company, XAI, with the goal to “understand the true nature of the universe.” It is pertinent to note that, Musk was one of the co-founders of OpenAI.
The Introduction of Artificial Intelligence into Legal Practice
The introduction of AI into legal practice goes as far back as 1970, when the use of computers in law firms had not gained as much integration as in these days. In establishing the origin of AI and legal reasoning, it is imperative to reference the work of Bruce G. Buchanan and Thomas E. Headrick. In their article titled, “Some Speculation about Artificial Intelligence and Legal Reasoning”, it was stated thus:
“Interdisciplinary work between Lawyer and the computer scientist has floundered on the misconception that each has of the other’s discipline…A new legal retrieval system has been or is being developed” foot note a somewhat similar system is under development by the American Bar Foundation in cooperation with I.B.M…these processes aid a researcher in finding all the documents that might have some conceivable relationship to the problem under search.”
The Nigerian Legal Practice
In discussing the future of legal practice in Nigeria, it is important to first establish where we are now. The term “The Nigerian legal practice” refers to the legal system, profession, and the practice of law in Nigeria. Our legal practice reflects soberness. However, the development of ICT (AI), has put a strain on such an ideology.
Key Aspects of the Nigerian Legal Practice
Nigeria operates a Federal system of government, with both Federal and State laws. Our legal system is influenced by a combination of the English common law, principles of equity, customary law, Islamic law, and various statutes. The Constitution of Nigeria is the supreme law of the land. Any law that is inconsistent with the provisions of the Constitution, is a nullity. (To be continued)
THOUGHT FOR THE WEEK
“Artificial Intelligence will not replace jobs, but it will change the face of jobs.” – Kai Fu Lee
