Source: Filevine - An AI Primer for Legal
How will new AI technologies shape the future of law? And how can legal professionals ensure that they adhere to legal ethics while they benefit from new technologies?
In part I of our new series, Filevine’s legal futurists Dr. Cain Elliott and Dr. Megan Ma, along with Senior Director of Product Alex McLaughlin, help lawyers answer these questions — and prepare for the future of their practice.
Don't want to wait for Part IV, watch the full AI, Ethics, and Legal: A Deep Dive Into the Future of Legal Tech Webinar on Youtube
Understanding Artificial intelligence (AI) and It's Implications
AI has become a transformative force in various industries, and the legal field is no
exception. However, with great power comes great responsibility. This series delves into the ethical implications of AI adoption in the legal industry and how Filevine is committed to empowering legal professionals to leverage AI effectively and ethically.
The world of AI can seem overwhelming, especially with the abundance of terminology surrounding it. However, it is crucial to move beyond the vocabulary and grasp how these tools and innovations impact the actual practice and work lives of legal professionals. Let's start by clarifying a few key points.
AI Terminology for Legal Professionals
Defining Artificial Intelligence
At its core, creators of artificial intelligence aim to develop machines that possess the ability to think and act intelligently. This includes leveraging technology to enable problem-solving, information retrieval, and simple reasoning. It is essential to establish this definition as it forms the basis of our discussion.
Artificial General Intelligence (AGI) vs. Artificial Intelligence
It's important to distinguish between artificial intelligence and artificial general intelligence (AGI). While AI focuses on machines capable of some level of reasoning, problem-solving, and assisting in finding answers, AGI refers to machines that surpass human intelligence in every domain. To date, AGI remains a concept rather than a reality, and won’t be discussed in this series.
Machine Learning: Learning from Experience
Within the realm of AI, the term "machine learning" frequently emerges. Machine learning involves creating systems where computers and algorithms can learn from experience without explicit programming.
Unlike traditional computing, where specific actions and expected outputs are predefined, machine learning enables machines to understand patterns and make predictions based on observed data. It provides a more dynamic and adaptable approach to computing.
Deep Learning and Neural Networks
Deep learning and neural networks build upon the foundations of machine learning. Instead of relying solely on symbolic logic and logical teaching, these approaches are inspired by the workings of the human brain. Deep learning and neural networks mimic the interconnectedness of neurons in the brain, enabling machines to process complex information and make sophisticated judgments.
The ongoing debate in AI history has revolved around the symbolic logic approach versus the neural network and deep learning approach. While symbolic logic emphasizes teaching machines logical information to mimic human reasoning, neural networks and deep learning seek to replicate the workings of the human brain.
In this series, we will explore these concepts further, demonstrating how AI, machine learning, and deep learning can enhance legal practices and improve efficiency. By understanding the foundations of AI and its various branches, you will gain valuable insights into the potential applications and benefits of this technology in the legal industry.
What Large Language Models Mean for the Legal Industry
The continuous coverage and buzz surrounding AI in the news are largely attributed to the advancements in deep learning and neural networks. These powerful technologies enable the creation of expansive systems that allow AI to perform actions without explicit instructions.
In this section, we will explore the role of large language models (LLMs) in this context and delve into the excitement and concerns surrounding their capabilities.
Unveiling the Magic of Large Language Models
LLMs, such as ChatGPT from OpenAI, Claude from Anthropic, and Bard from Google, have recently gained significant attention in both technological and media spheres. These models harness the potential of neural networks to accurately predict the next word in a sequence, generating content that often feels remarkably magical. The ability of computers to approximate the next word in a sentence, based on predictive modeling, has captivated audiences and spurred widespread interest.
The remarkable achievements of LLMs have generated tremendous excitement among technologists and the general public. However, their rapid advancements have also instilled a sense of unease and caution about the potential implications. Driven by a desire to delve deeper into the concerns surrounding AI and its impact on the legal landscape, this series aims to initiate a conversation about responsibility and ethical considerations.
Navigating AI's Impact on the Legal Community
AI has the potential to revolutionize every industry, including the legal sector. However, its widespread implementation does not automatically imply equal exposure and adoption among all users or the legal community. Recognizing the diverse concerns and responsibilities associated with AI, it is crucial to address these matters proactively.
Stay tuned for future blog posts in this series, where we highlight key areas of concern and soliciting the thoughts and perspectives of experts, such as Megan and Alex, to foster a collaborative conversation on the intersection of AI, law, and ethics.