Emerging Topics

While ChatGPT and other Large Language Model-based systems have become quite popular, in this lecture we will discuss the different types of artificial intelligence and explore their use in veterinary medicine. This will look at large language models and how they work while also introducing machine learning and deep learning modalities and introducing how AI tools are being built with them. Finally, we will share the responsible-use and critical-evaluation approach to AI being taught to students.

Learning Objectives: 

1. Describe the difference between LLM, Machine Learning, and Deep Learning
2. Discuss what AI tools are being built using the different types of AI
3. Describe responsible use and critical evaluation approaches being taught to students.

Brief Description: As artificial intelligence rapidly enters the veterinary clinic, the legal landscape surrounding medical records and standard of care is shifting. This session defines the legal boundaries and malpractice risks of utilizing AI in veterinary medicine under current Practice Acts. We will explore the phenomenon of AI “hallucinations,” establish the legal standard for medical record documentation, and define the critical line between utilizing AI as an authorized administrative scribe versus an unauthorized diagnostic tool.

Learning Objectives: Upon completion of this session, participants will be able to:

• Identify the legal liabilities associated with AI-generated medical records and AI “hallucinations.”
• Differentiate between authorized administrative AI use and unauthorized, un-licensed diagnostic AI use.
• Determine the assignment of liability (e.g., the “Captain of the Ship” doctrine) when AI-generated errors occur, such as incorrect medication dosages in clinical notes.
• Apply strict interpretations of state Practice Acts to categorize and restrict AI tools to administrative functions, mitigating malpractice risk.

Brief Description: Building on the legal framework from Hour 1, this session provides actionable strategies for ethically leveraging AI without compromising legal compliance, patient safety, or client confidentiality. Practitioners will learn the massive data privacy liabilities associated with typing client data into public, free AI models. We will review real-world examples to help teams implement secure, auditable workflows and medical record approaches that protect the practice while maximizing technological leverage.

Learning Objectives: Upon completion of this session, participants will be able to:

• Formulate ethical guidelines and operational frameworks for safe AI adoption within a veterinary practice.
• Implement compliance safeguards and practical audit steps for verifying AI outputs, such as SOAP notes and discharge summaries, before finalizing records.
• Identify the data privacy risks and legal liabilities inherent in using free, open-source AI platforms with confidential client data.
• Recognize and prevent staff workflows that inadvertently leak protected veterinary data, ensuring strict adherence to data security standards.

Thirty years ago, sending blood out and waiting days was normal practice. A chemistry analyzer on the counter was novel, expensive, and hard to justify. Today nobody looks at it twice. Veterinary medicine has a strong record of taking in new technology and making it ordinary, and we are in the early part of that curve again with AI.

What is possible right now is wider than most people realize. You can build a working app by yourself with no software background. You can find disease patterns across thousands of records that nobody could see case by case. You can write a ridiculous poem about the surgery schedule and make your team laugh on a hard day.

Think of AI as a pocket knife with several blades: language models, image recognition, predictive models, speech tools, and agents that string steps together. Each blade does something different, and knowing which is which is what makes creative use possible.

Veterinarians are resourceful and primed to be innovative and ethical stewards of AI. This session explores present-day applications and futuristic examples of AI applications across clinical work, business growth, team culture, and more, with attention to both what you can try tomorrow and what we should be asking AI builders to create in the future.

Learning objectives:

1. Describe the range of what veterinarians are doing with AI today, from building working tools to finding disease patterns at scale to lifting the mood in a busy practice.
2. Recognize non-obvious uses of AI across clinical work, practice operations, research, and everyday life in the clinic.
3. Understand how veterinarians without software development experience are using AI to build tools of their own.
4. Imagine what is coming next for veterinary medicine, from earlier disease detection to discoveries our profession is well positioned to make first.
5. Identify at least one practical way to use AI in your life in the next week, and one way to help shape where these tools go next.