IMPLIMENTING OPEN SOURCE LARGE LANGUAGE IN LEGAL BUSINESS/FIRM

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles, and books, to generate text, translate between languages and write many types of content. There are two types of these generative AI models: proprietary large language models and open source large language models . The term “open source” refers to the LLM code and underlying architecture being accessible to the public, meaning developers and researchers are free to use, improve or otherwise modify the model.

As the AI field is becoming more diverse with a wider variety of open source alternatives, here are some of the contenders making the biggest impact. Public interest in large language models or LLMs has grown significantly since the launch of Open AI’s chatbot, ChatGPT late last year. Open AI’s GPT-3 model is the most advanced and widely known large language model. It stands for Generative Pre-Trained Transformer 3. It is a cutting age language model that uses deep learning to generate human like text based on input it receives. As a continent, we are experiencing a transformative shift in the artificial intelligence landscape. The emergence of Open Source Large Language Models is reshaping how businesses approach AI development and deployment presenting opportunities and challenges that demand our attention.

Open Source Language Model, is an advanced AI technology revolutionizing natural language processing and transforming industries with its ability to understand and generate
human prized business. It is changing the dynamic landscape of AI, and offering unprecedented opportunities for enterprises and businesses.

For instance the emergence of Chat-GPT on November 30, 2022, presented businesses with a critical question: how much should they rely on Generative AI? In the legal field, the consensus is clear: AI won’t replace lawyers, but tech-savvy lawyers will likely outpace their peers who avoid it. Large Language Models (LLMs) such as GPT-4 are revolutionizing the industry by automating routine tasks like drafting documents and summarizing contracts. This wave of automation mirrors the disruption Uber caused in transportation, but the legal field is poised to innovate rather than be overtaken. Leading legal firms and businesses are already investing heavily in AI, with LexisNexis integrating AI and Thomson Reuters acquiring Case text for $650 million, illustrating a survival-of-the-fittest scenario.

Open source large language models: Benefits, risks and types, IBM Data and AI Team,https://www.ibm.com/blog/open-source-large-language-models-benefits-risks-and-types/ accessed on 18th August , 2024.

CAPABILITY OF THE OPEN SOURCE LARGE LANGUAGE MODELS

LLMs like AI’s have the capability of a computer program to perform tasks or reasoning process that are normally associated to intelligence of human beings. They respond to
stimulation consistent with human responses such as contemplation, judgment, and intention. AI’ technology has the capacity to engage in critical appraisal and selection of differing opinions within themselves and ultimately make of differing opinions within themselves and ultimately make decisions which would normally require human expertise. The ultimate goal of AI is reportedly to solve a wide range of practical problems, boost productivity and foster new discoveries across industries . AI is credited for transforming tasks that require brain power.

COMPARISON BETWEEN THE AUTOMATED SYSTEM AND THE TRADITIONAL HUMAN CENTRED SYSTEM IN LEGAL BUSINESSES

LLM code based framework which revolutionizes it’s structure by deploying fine-tuned large language models to perform specific tasks based on the uniqueness of each case and
complexity of the task.

AI can automate and improve tedious tasks, enhance efficiency and increase the speed for research. This is made possible by leveraging the vast amounts of unstructured and structured data held in systems in a firm’s legal department.

As opposed to the Traditional human centered approach, which operates on a hierarchal structure with a partner who develops overall strategy and advise on complex legal issues,
provide regulatory guidance. Associates who assist with document drafting, legal research and litigation. Assistants who support associates with document preparation and drafting. Paralegals/legal assistants performing tasks – going to a chain of associates then senior counsel –this approach heavily relies on expertise and billable hours of each team member high operational costs.

Darrel M West and John R Allen ‘How artificial intelligence is transforming the world’, Brookings (2018) https://www.brookings.edu accessed on 17, August, 2024.

ADVANTAGES OF OPEN SOURCE LARGE LANGUAGE MODELS IN OPERATING LAW FIRM BUSINESSES

In an ever –evolving landscape of legal practice, innovation is key to maintaining a competitive advantage and ensuring high quality client service. The LLMs represent ground
breaking shift in how law firms operate, integrating advanced AI models to perform specific legal tasks that were previously traditionally handled by human personnel. The Open
Source movement is democratizing access to powerful AI tools bringing several key advantages to the forefront.

Efficiency: LLMs enhance operational efficiency by automating and refining routine tasks. The routine tasks include inventory, management, and payroll, customer service which can be automated, reducing the need for extensive human intervention and allowing businesses to reallocate resources more effectively. It facilitates data integration across various business functions, streamlining operations and enabling quicker, more informed decision making. AI technologies have the capacity to engage in critical appraisal and selection of differing opinions within themselves and ultimately make decisions which would normally require human expertise.

Cost effectiveness: Billing is based on each model and task. The LLM will bill based on complexity and computational effort required for each task. This ensures transparency and
aligns costs with value provided by AI models through assessment of the overall work done to litigate a client’s case which includes drafting, research, searches, analysis, review,
litigation. It can revolutionize the billing structure by deploying fine-tuned large language models to perform specific tasks. Billing can based on the complexity of the task and computational effort required for each task. It may bill high complexity tasks e.g – strategic advisory because it be able to access searches, analysis, review, litigation strategies. This ensures transparency and aligns costs with value provided by AI models.

Accessibility: Open Source LLMs are significantly lowering the barrier to entry enabling businesses of all sizes leverage advanced AI capabilities without prohibitive costs or
restrictive licensing agreements. AI can automate and improve tedious tasks, enhance efficiency and increase the speed to insight –all made possible by leveraging the vast amounts of unstructured and structured data held in systems in a firm and legal departments.

Shukla Shubhendu and Jaiswal Vijay, ‘Applicability of Artificial Intelligence in Different Fields International Journal of Scientific Engineering and Research (IJSER) www.ijser.in ISSN (Online): 2347-3878 Volume 1 Issue 1, September 2013, https://www.ijser.in/archives/v1i1/MDExMzA5MTU=.pdf accessed on 19th August, 2024.

Customization Flexibility: Unlike proprietary models, Open Source LLMs offer unprecedented flexibility. They can be fine –tuned and adapted to specific use cases, allowing for tailored solutions that address unique business needs.

LLMs are instrumental in overcoming language and communication barriers within the multilingual African landscape, enhancing interactions and a diverse customer base. The
natural language processing tools allow for effective communication across multiple language, helping businesses expand market reach and ensuring that their marketing
materials and customer interactions are culturally and linguistically aligned with their target audiences. This technological advancement minimizes misunderstanding and broadens the customer base by making business more accessible to a wider audience.

Content filtering and moderation: LLMs can be valuable in identifying and filtering out inappropriate or harmful online content, which is a huge help in maintaining a safer online
environment.

CONCERNS WITH USING OPEN SOURCE LANGUAGE MODELS

What legal risks/accountability questions does the use of open source LLMs create?

Adopting AI doesn’t ensure success; it requires ongoing adaptation. The legal battleground illustrates this well: if both sides use GPT-4, the advantage may neutralize, leading to a new phase of AI competition—customization. For legal generative AI to be an asset rather than a liability, it must be dependable and controllable. This is where open-source LLMs shine, offering transparency and adaptability, unlike closed-source models. As the legal sector navigates this new terrain, open-source AI seems to be the strategic choice for those aiming to stay competitive and compliant with evolving AI legislation.

Bias and fairness. Open Source Language Models rely on algorithms and logarithms can be biased by data they rely on. In 2016, it was reported that the COMPAS AI, an AI powered risk assessment tool used in the United States of America judicial system to determine the risk of a convict in committing crimes, was racially biased . COMPAS AIwas more likely to falsely “flag” black defendants as future criminals, wrongly labeling/categorizing them this way at almost twice the rate of white defendants . This illustrates bias that might manifest from relying entirely on AI to make decision and assessments for a legal business. In these circumstances, even as one considers the applicability of AI’s, they ought to consider how the risk of bias may be minimized?

Confidentiality: This is one of the cardinal reasons that parties choose AI can be used to analyze large volumes of data/information/ facts related to an international commercial
dispute. In the event that the law is amended, challenges are bound to arise where a client is unwilling to share their data to inform future predictions. As AI algorithms require data to learn patterns and make decisions and predictions based on it. This raises the question on confidentiality of information which can only be preserved through anonymization of the data . AI technologies are also subject to cyber security risks, such as hacking, as well as the predicted risk that AI technologies may one day become counterproductive and turn against humans .[26] These technical challenges, highlight the reasons as to why adoption of AI in ICA faces stern criticism.

Implementing the LLMs is financially tedious: This is primarily due to the substantial costs associated with setting up and maintaining the systems. These costs include initial investment in technology and software and the ongoing maintenance and upgrades of the systems. Additionally, the LLMs often require robust data infrastructure and advanced computing resources which can be expensive. This creates a difficulty because a business/ firm could divert funds from essential departments which could potentially inhibit growth and innovation in an already challenging economic environment.

CONCLUSION

Conclusively, the rapid advancement of AI presents transformative opportunity for LLMs across Africa, offering significant improvements in operational efficiency, market research, product innovation and communication. However, the mentioned above requires a balanced approach involving strategic investments in technology comprehensive training programs and robust partnerships between public and private sectors. By navigating these complexities thoughtfully, African countries can harness the full potential of LLMs and AIs to drive growth and innovation, ensuring they remain competitive on a global scale while fostering sustainable economic development within content. LLMs are increasingly becoming one of the key drivers for change throughout the key drivers for change throughout the professional landscape, given its ever evolving influence on how businesses operate, invest and adapt to its implications.

4ProPublica, ‘Machine Bias’, 23rd May 2016, https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing , accessed on the 22nd August 2024.
5Ibid
6Lucas Bento, ‘International Arbitration and Artificial Intelligence: Time to Tango?’ Kluwer Arbitration Blog (2018) https://arbitrationblog.kluwerarbitration.com/2018/02/23/international-arbitration-artificial-intelligencetime-tango/ accessed on 18th August, 2024
Muller Vincent C and Bostrom Nick, ‘Future Progress in artificial intelligence: A survey of expert opinion’ in Vincent C Muller (Ed), Fundamental Issues of Artificial Intelligence, Springer, 553 (2016)
https://philpapers.org/rec/MLLFPI accessed on 22nd August 2024.

BIBILOGRAPHY

1. Lucas Bento, ‘International Arbitration and Artificial Intelligence: Time to Tango?’KluwerArbitrationBlog(2018)https://arbitrationblog.kluwerarbitration.com/20 18/02/23/international-arbitration-artificial-intelligence-time-tango/
   
2. Muller Vincent C and Bostrom Nick, ‘Future Progress in artificial intelligence: A survey of expert opinion’ in Vincent C Muller (Ed), Fundamental Issues of Artificial Intelligence,
   Springer, 553 (2016) https://philpapers.org/rec/MLLFPI 3 .ProPublica,’MachineBias’,23rdMay2016,https://www.propublica.org/article/machine
   -bias-risk-assessments-in-criminal-sentencing .
   
3. Shukla Shubhendu and Jaiswal Vijay, ‘Applicability of Artificial Intelligence in Different Fields International Journal of Scientific Engineering and Research (IJSER) www.ijser.in I S S N ( O n l i n e ) : 2 3 4 7 – 3 8 7 8 V o l u m e 1 Iss u e 1 , S e p t e m b e r 2 0 1 3 , https://www.ijser.in/archives/v1i1/MDExMzA5MTU=.pdf accessed on 19th August,
   2024.
   
4. Darrel M West and John R Allen ‘How artificial intelligence is transforming the world’, Brookings (2018) https://www.brookings.edu
   
5. Open source large language models: Benefits, risks and types, IBM Data and AI Team,https://www.ibm.com/blog/open-source-large-language-models-benefits-risksand-types/ accessed on 18th August , 2024.