Google Announces the Public Release of Gemini: Can it be Used to Support Legal Research?

“Google launched its most ambitious AI model called Gemini on Wednesday [December 6, 2023], which is described as Google’s “largest and most capable AI model.” The company announced a “Gemini era” where the model will be used widely in companies and consumer devices like Google Pixel phones. Unlike existing AI models that focus on one type of input like text or images, Gemini is “multimodal” and can accept different types of media like text, images, audio and video as inputs. Google’s AI chatbot Bard has been upgraded with Gemini, and Google plans to add Gemini to widely used products like Search, Chrome and its cloud services”
Benzinga News, December 7,

On December 6, 2023, Google announced the public the launch of Gemini, its most powerful and versatile artificial intelligence (AI) model yet. According to Google, this groundbreaking technology marks a significant milestone in the field of AI, with the potential to revolutionize various industries and impact our daily lives in profound ways. This posting consists of an overview of Gemini based on various materials I could retrieve on short notice–since I was unaware that the unveiling of Gemini would be on December 6. As explained in the second part of this post I also include material addressing the question: Is Gemini capable of supporting legal research. Much of this commentary is derived from my interaction with Google Bard.

A word of caution:  When reading the below material be aware that as wonderful, flexible, and ground breaking this version of Gemini appears to be issues related to fake news and hallucinations are still with us. Therefore, when using this version of Gemini (and other generative AI applications that I am aware of) to research foundational information in any area, it is important to verify the authenticity of such information by also consulting other sources deemed reliable and authentic.

The development of artificial intelligence (AI) has been a gradual process, with significant breakthroughs occurring throughout history. Early pioneers like Alan Turing and John McCarthy laid the foundation for AI research, exploring theories and developing fundamental algorithms. In the 1970s and 80s, expert systems and knowledge representation became areas of focus, leading to applications in medicine, finance, and other industries.

The 1990s and 2000s saw the rise of machine learning, where algorithms learn from data without explicit programming. This led to advancements in areas like computer vision, natural language processing, and robotics. However, the capabilities of AI models remained limited, often struggling with complex tasks requiring understanding and reasoning.
In recent years, the development of large language models (LLMs) has marked a significant turning point in AI research. These models, trained on massive datasets of text and code, can perform a wide range of tasks, including writing different kinds of creative text formats like poems, code, scripts, musical pieces, email, letters, etc., answering your questions in an informative way, even if they are open ended, challenging, or strange, and generating different responses based on a given context.

Basically, Gemini is a multimodal AI model capable of understanding and generating text, code, audio, images, and video. This unique ability allows it to perform a wide range of tasks, from writing creative content and translating languages to generating realistic images and composing music. Additionally, Gemini boasts exceptional performance across various benchmarks, exceeding the capabilities of other leading AI models in several areas. One of Gemini’s new features that I believe is especially important relates to natively multimodal as described below. Through its added power and flexibility, Gemini should be useful as an enhancement to existing features in many areas of research such as criminal justice and law. For more detail see: Google Unveils Gemini by Casey Newton

• Natively multimodal: Unlike previous LLMs, Gemini can understand and operate across text, code, audio, image, and video, enabling it to process and generate information in a more natural and human-like way.  State-of-the-art performance: Across a range of tasks, Gemini has achieved state-of-the-art performance, surpassing even the most advanced LLMs available.
• Open-ended capabilities: Gemini is not limited to specific tasks or domains. It can be fine-tuned and adapted to an incredibly diverse range of applications, making it a truly versatile tool.

Potential Applications of Gemini according to Google.

The potential applications of Gemini are vast and encompass various sectors, including:
• Scientific research: Gemini can accelerate scientific discovery by analyzing complex data sets and identifying hidden patterns.
• Healthcare: Gemini can assist in personalized medicine by analyzing genetic data and predicting patient responses to treatments.
• Education: Gemini can personalize learning experiences and provide students with tailored support.
• Business: Gemini can improve business processes by analyzing data, identifying trends, and making predictions.
• Law: Gemini’s potential to support the practice of law is vast. Some of the areas of law mentioned are: litigation support, legal research and discovery, legal writing and drafting and legal research assistance.

While preparing this post, I could not resist, as a law librarian, consulting Google Bard and requesting the following:

1. I need an explanation as to how recently released AI Gemini can support legal research.
2. Given its many capabilities, can features of AI Gemini be useful in legal research systems such as Lexis and Westlaw?
Below are the unedited answers from Bard in the order listed above:

1. I need an explanation as to how recently released AI Gemini can support legal research

Bard’s answer:

Gemini, launched in December 2023, is Google’s most advanced AI model to date. It can potentially revolutionize legal research in several ways:

a. Legal document analysis and comprehension:
• Gemini can quickly analyze large amounts of legal text, including case law, statutes, and regulations. This can save researchers hours or even days of time compared to traditional manual methods.
• It can identify relevant legal concepts and principles within these documents, helping researchers to focus on the most important information.
• It can also understand the relationships between different legal concepts, which can be helpful for legal reasoning and argumentation.

b. Legal research automation:
• Gemini can automate many repetitive tasks involved in legal research, such as identifying relevant cases and statutes, analyzing factual patterns, and drafting legal documents.
• This can free up lawyers and legal researchers to focus on more complex and strategic tasks that require human judgment.
• It can also help to ensure that legal research is more accurate and consistent.

c. Legal research insights:
• Gemini can provide researchers with insights and perspectives that they might not have considered on their own.
• It can do this by identifying patterns and trends in legal data, and by suggesting alternative arguments and interpretations of the law.
• This can help researchers to develop stronger legal arguments and to make more informed decisions.

d. Legal writing assistance:
• Gemini can help lawyers and legal researchers to draft legal documents more efficiently and effectively.
• It can do this by suggesting language, formatting, and citation styles that are consistent with legal standards.
• It can also help to identify and correct errors in legal writing.

e. Legal education:
• Gemini can be used to create more interactive and engaging learning experiences for law students.
• It can do this by providing students with personalized feedback on their legal research and writing assignments.
• It can also help students to develop their legal reasoning and problem-solving skills.

However, it is important to note that Gemini is still under development and has limitations:
• It is not a substitute for human judgment and expertise. Legal professionals should always review and verify any information or advice provided by Gemini.
• It may not be able to understand complex legal concepts or nuanced arguments.
• It may not be familiar with all areas of law.
• It may be biased based on the data it was trained on.

Overall, Gemini has the potential to significantly improve the efficiency and effectiveness of legal research. However, it is important to use it responsibly and to be aware of its limitations.

2. Given its many capabilities, can features of AI Gemini be useful in supporting legal research systems such as Lexis and Westlaw?

Bard’s Answer:

Yes, the features of AI Gemini have the potential to be highly beneficial for legal research systems like Lexis and Westlaw in various ways:

a. Advanced Search and Retrieval:
• Multimodal understanding: Gemini can process text, audio, images, and video simultaneously, allowing for more comprehensive and nuanced search queries. This could involve searching for relevant legal documents based on audio recordings of court proceedings or images of handwritten notes.
• Reasoning and inference: Gemini’s advanced reasoning abilities could help to identify relevant legal precedents even when they are not explicitly mentioned in the search query. This could be achieved by understanding the legal arguments presented in a case and identifying similar arguments in other cases.
• Fact-checking and verification: Gemini could be used to verify the accuracy and reliability of legal information, which is crucial for legal research. This could be done by cross-checking information against multiple sources and identifying potential inconsistencies.

b. Improved Research Efficiency:
• Automatic summarization and extraction: Gemini can summarize lengthy legal documents and extract key points, saving researchers valuable time and effort.
• Identifying relevant case law: Gemini could analyze a user’s research query and proactively suggest relevant case law, even if the user is unfamiliar with all the relevant legal areas.
• Predicting legal outcomes: In some cases, Gemini could analyze legal arguments and predict the likely outcome of a case, which could be helpful for lawyers preparing for litigation.

c. Enhanced User Experience:
• Natural language interaction: Gemini’s ability to understand natural language queries could allow researchers to interact with legal research systems in a more natural and intuitive way.
• Personalized recommendations: Gemini could learn from a researcher’s past searches and preferences to suggest relevant legal resources and tailor the research experience to their individual needs.
• Multilingual support: Gemini’s ability to understand and translate multiple languages could make legal research more accessible to researchers from all over the world.

d. Integration with Existing Systems:
• Gemini’s API could be integrated with existing legal research systems to provide additional features and functionalities.
• This could involve adding a “Gemini powered” search bar to existing platforms or allowing users to access Gemini’s advanced search and retrieval capabilities from within their existing workflow.

e. Potential for Innovation:
• Gemini’s capabilities can open up new possibilities for legal research, such as developing new tools for legal analysis and argumentation.
• This could lead to a more efficient and effective legal system overall.

However, it is important to consider the following limitations:
• Bias and fairness: AI models can inherit biases from the data they are trained on. It is important to ensure that Gemini is trained on a diverse and representative dataset of legal information to avoid perpetuating bias.

• Explainability and transparency: It is important to understand how Gemini arrives at its conclusions to ensure that its predictions are reliable and trustworthy.

• Accessibility and cost: Access to advanced AI models like Gemini could be expensive, potentially creating a barrier for some legal researchers.

Overall, AI Gemini has the potential to significantly improve legal research by making it more efficient, effective, and accessible. However, it is important to address the challenges of bias, explainability, and accessibility before Gemini can be widely adopted in the legal industry.


I have read several descriptions Gemini, but this one best explains how it works and it’s purposes.                                                                                                                                                                                                                                                                                       John   E. Tomaszewski,  Computer Scientist

Congratulations, David!  Well thought out and a great perspective.  I am going to try it [Gemini] out!                                                                                                                                                                                                                                                                 Mitchell Erickson, U.S. Department of Homeland Security.


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