Owning Your AI: Why This Matters in the Legal Industry

The legal world finds real comfort in consistency. It's a profession deeply rooted in precedent, reliability, and attention to detail and the constant (every day) evolution of AI can sometimes feel like a double-edged sword in terms of the how things work.

Recently, OpenAI's decision to deprecate GPT-3.5 models, nudging users towards GPT-4 Mini, really shows this challenge - while the power of GPT-4 is obvious, the speed of the shifts in capabilities present a challenge for legal professionals who crave consistency in their tools.

Here's the interesting bit though, for many tasks within legal workflows, such as content summarisation or document review, you don't really need the god like power of GPT-4. In fact, for some tasks, it's just overkill. So if that's the case then why rely on a constantly shifting cloud-based model when you could run your own AI, tailored to your needs, locally? This approach offers control, security, and the kind of reliability that cloud services can't always guarantee.

The Case for Local AI in Law

For firms, the idea of owning their AI may seem like a radical departure from the norm. I mean, after all, cloud services are super convenient, scalable and have been the main direction of travel for everything else the past 5-10 years, but running AI models locally has awesome advantages that shouldn't be overlooked - especially in an industry where sensitivity and confidentiality are key.

A big benefit to running your own models locally means you can also tap into uncensored AI models, which I discussed in a previous post, most commercial models have guardrails around input and output, however the nature of legal work can often mean that commercial models don't want to process certain content types. Using uncensored models locally means that you can benefit from AI capabilities without having to send incredibly sensitive content into the world.

Now let's say your law firm is approached by a whistleblower with evidence of high-level corporate corruption. The documents are incredibly sensitive, implicating several prominent figures in a complex web of financial fraud, the mere sniff of this information leaking could compromise the entire case and put your client at risk.

Instead of relying on an external cloud service that's constantly evolving and requiring adaptation, you deploy your AI model on an air-gapped, segregated machine. This approach brings several significant benefits:

1. Consistency and Control: When running AI locally, you're not subject to the frequent changes and updates that cloud-based services enforce. Your model remains as capable tomorrow as it is today, providing a dependable tool for recurring legal tasks. This consistency is crucial when dealing with long-term cases or establishing precedents.
2. Security and Confidentiality: With local AI, especially in the legal sector, sensitive data never leaves the building. This is particularly important when dealing with client data that must remain secure and private. An air-gapped machine means there's no network connection, reducing exposure to potential cybersecurity threats. For law firms handling high-profile or sensitive cases, this level of security can be a key factor.
3. Efficiency Without Overkill: Not every task requires the computational power of a huge model like GPT-4, content summarisation or contract analysis can often run efficiently on more lightweight, locally deployed models. You don't need god-like AI to get high-quality results for many day-to-day legal tasks.
4. Scalable Capabilities: With a sufficiently powerful computer, you can run incredibly powerful models locally, including large language models and vision models. This scalability means you can tailor your AI capabilities to your firm's specific needs:
   • Language Models: For complex document analysis, contract review, or legal research.
   • Vision Models: To process and analyse visual evidence, such as surveillance footage, photos of evidence, or complex diagrams in the fraud investigation.
5. Customisation and Specialisation: Local deployment allows you to fine-tune models on your firm's specific areas of practice or client industries. This specialisation can provide a significant edge in niche legal areas or when dealing with industry-specific terminology and concepts.
6. Cost Control: While there's an initial investment in hardware and setup, local AI can offer more predictable long-term costs compared to usage-based cloud services, especially for firms with high AI usage.

By leveraging local AI, law firms can ensure they have the right tool for each job – from efficient, lightweight models for routine tasks to powerful, specialised models for complex cases requiring advanced language processing or understanding more visual content. This flexibility I find combined with the security and consistency of local deployment, positions firms to handle a fairly wide range of legal challenges while maintaining full control over their AI resources.

Leveraging Local AI: Tools You Can Use

If the idea of running your own AI sounds complicated, it doesn't have to be. It's fairly straightforward for legal firms to implement AI models in-house without requiring a team of AI specialists, rather AI appliers. Ollama allows you to run open-use AI models directly on your own hardware, whether it's for document review or general chat, Ollama gives you the flexibility to choose from a range of pre-trained models that can then be used however you want.

Another powerful, yet simple development tool which complements Llama is Streamlit. It allows for quick and easy development of custom data-driven applications. It's a rally great way to build workflows that can integrate with both local and cloud-based models. A legal tech team could build a Streamlit app that interfaces with a local AI model for document analysis, while also having the option to hook into a cloud-based model for more complex tasks.

These tools lower the barrier to entry for firms that want to maintain full control over their AI usage without compromising on ease of use or functionality.

Cloud vs Local AI: What's Right for Your Firm?

The decision to run AI in the cloud versus locally is not just either/or - it depends on your firm's needs, client expectations, and the sensitivity of the data being handled.

• Cloud AI: Offers scalability, easier access to the latest advancements, and the ability to handle large, complex datasets that require significant computational power. However, the trade-off is that you rely on third-party providers for data handling, and the model capabilities may change frequently.
• Local AI: Provides greater control over the model and data. You're not subject to sudden shifts in capabilities and updates, and you can ensure that sensitive data remains secure within your own environment. This is especially useful for routine tasks like summarisation, document review, or internal analysis, where high consistency and confidentiality are key.

Building Trust with Clients Through Local AI

For legal professionals, client trust is everything. By offering AI solutions that run locally, you can assure clients that their sensitive data is handled with the utmost care and security. There's no need to upload confidential documents to the cloud, and all analysis can be done in-house and in fact, for the most sensitive cases, you can even offer a completely segregated, air-gapped solution, where data is never exposed to external networks at all, so literally in-house, or in-office to be precise.

This kind of client assurance is fundamental in the legal industry, where data privacy and security are non-negotiable, being able to confidently tell clients that their data remains secure, while still benefiting from AI tools, is the kind of thing that sets your firm apart.

Owning Your AI Future

AI is a tool, and like any tool, its value comes from how it's used and for law firms, the ability to run AI locally provides an invaluable sense of control, consistency, and security. Tools like Ollama and Streamlit make it easier than ever to build and deploy AI solutions in-house, ensuring that you're not dependent on external factors.

As AI continues to advance, owning your AI will become an essential part of offering high-quality, secure, and consistent legal services. While the AI industry continues to evolve at ever increasing speed, your firm can remain a steady, reliable partner for your clients - confident in the knowledge that you've got your AI under control.