Gaining a Seat at the AI Table
“You cannot enter a world for which you do not have the language.” - David Whyte, Irish poet
Recent advances in artificial intelligence (AI) tools appear to have the attention of the entire world. Organizations, information technology companies, governments, unions, philosophers, and even our children’s teachers and professors are trying to understand what AI means for business, education, jobs, and the future. News articles and podcasts about AI describe multiple advantages and offer dire warnings. We can be confident that AI is being discussed at every level of our organizations today. This blog post is to encourage our colleagues and fellow Interprofessional practitioners to look for ways to "have a seat at the AI table." We also want to tell you about an upcoming session on AI and Teamwork at the National Center Summit on September 29 at 9:30 am Central Time to help those of you who would like a jumpstart into the world of AI and its implications for interprofessional practice and education.
Have no doubt, AI has tremendous potential to advance interprofessional teamwork and collaboration. Think about the possibilities for predicting team models that improve healthcare quality and reduce provider burnout. Or generating unimaginable learning materials that provide true-to-life team experiences. Think too, about possible unintended consequences of applications of AI to teamwork, like building outdated biases into the construction of team algorithms. Imagining this future is where the expertise of the interprofessional community comes in. The development of successful AI models and programs like ChatGPT, Claude or Perplexity, to name a few, depend on understanding the questions or prompts to ask. AI models are based on patterns (and usually exceptionally large data sets). Who better to guide the development of AI prompts for teamwork and collaboration than members of our community who live in this space.
An important message here – and one central to getting involved – is that you don’t have to be an expert in AI to gain a seat at the table. Subject matter expertise is foundational. Our knowledge and insights about teamwork and workflows make us invaluable to the people who are AI experts from information technology, engineering and many other fields.
Another important message in thinking about getting involved in AI, is that it relies on trial and error and iterative improvements. There’s time for you to try out new ideas and put your expertise in interprofessional practice and education to work.
Here are some ways to become more informed and prepare your to be an active participant in the exciting future of AI and teamwork:
Stay informed. Read articles, research papers, and attend conferences or webinars related to AI. This will help you understand the potential applications and impact of AI in your field.
Join professional organizations. Become a member of a professional organization that focuses on informatics, technology, or AI in healthcare. These organizations often provide resources, networking opportunities and educational programs related to AI.
Collaborate with interprofessional teams. AI initiatives often involve collaborations between healthcare professionals, data scientists, engineers, and other experts. Seek opportunities to collaborate with these professionals on AI projects or research studies.
Understand AI applications in your field. Familiarize yourself with ways AI can enhance treatment and patient care, automate tasks, and collect outcomes measure.
Advocate for inclusion in AI initiatives and decision-making processes. Share your experiences and knowledge with colleagues, educators, and policy makers to raise awareness about the potential benefits of AI in improving patient outcomes and efficiency of services.
AND: Plan to join us in our upcoming panel discussion, “AI and Interprofessional Teamwork” at the NEXUS Summit on September 29th. Four incredible experts will offer their observations and answer questions about the opportunities and challenges of the increasing use of AI in healthcare, its impact on teamwork and their suggestions for how we can get involved and contribute to AI initiatives. See you there!
“This present moment used to be the unimaginable future.” — Stewart Brand
Some Helpful Definitions
Artificial Intelligence (AI) – Look up the definition of Artificial Intelligence (AI) and you will not find a universal definition. For the purposes of this blog post, let’s use this one: AI is a field combining computer science and robust datasets to enable problem-solving. AI systems ingest large amounts of data, analyze the data for correlations and patterns, and use these patterns to make predictions and decisions about future states.
AI Prompt – A way to communicate with AI systems and provide instructions or input to generate specific responses or perform tasks. Prompts in AI tools are like instructions or commands that are given to an AI model.
Prompt Design or Engineering – The process of refining prompts to optimize AI performance and achieve desired outcomes.
AI Model – An AI model is a computer program that learns from large amounts of data to make predictions or decisions. It's like having a virtual assistant that can analyze information and provide insights based on what it has learned.
Large Language Model (LLM) – A LLM, such as ChatGPT, is a type of artificial intelligence system that can converse, generate readable text on demand, and even produce novel images and video based on what they’ve learned from vast database of digital books, online writings, and other media.
- July 2023: From Question to Action
- April 2023: A message from Gerri Lamb and Mary Mauldin, the inaugural Nexus Distinguished Scholars