Aging services providers are on the cusp of using generative artificial intelligence (AI). In fact, increased adoption of generative AI is one of CAST’s top 5 tech trends for 2024. If you are new to these tools, the guide below can help. Read on for examples of how you can use these powerful tools.

What is Generative AI?

First, the basics. What are generative AI and large language models?

Generative AI generates new content such as images, music, and stories. Generative AI processes are trained on a variety of types of content. They present samples and new combinations of the material they have learned, and they mimic human creativity. For example, they can create fresh materials for marketing and staff training.

A large language model (LLM) is a type of generative AI that focuses on text. An LLM is trained on large volumes of text data and excels at understanding the relationships between words. Based on a neural network, an LLM can predict the next word in a string of text and imitate human language patterns. ChatGPT, which enables you to ask questions and receive answers using natural language, is based on an LLM.

“Are Generative AI And Large Language Models The Same Thing?” provides more nuances on the similarities and differences between these advancing technologies.

How Can You Use Generative AI in Aging Services?

Generative AI can help to reduce administrative tasks and improve clinical decision-making and patient care, says “Shaping the Future of Older Adult Care: ChatGPT, Advanced AI, and the Transformation of Clinical Practice,” recently published in JMIR Aging.

The conversational capabilities of LLMs like ChatGPT are “opening new possibilities for interacting with and generating insights from data, streamlining everyday tasks, and automating routine work for clinicians,” said the article.

Because of their strong ability to find patterns in data, LLMs combined with clinical expertise can “help identify patterns, correlations, and subtle relationships in the clinical data that may not be immediately apparent.” This capability means that LLMs can assist clinicians with diagnoses and treatment, including for patients who have chronic conditions.

Generative AI tools can also improve the patient experience by remotely monitoring people with chronic conditions, giving patients personalized health information, and offering virtual companionship to those who are experiencing loneliness. These tools can also save staff time in updating electronic health records and responding to patients.

What Are Some Specific Generative AI Tools?

Microsoft 365 Copilot, introduced in March 2023 and expanded in November 2023, lets you complete a variety of tasks in Microsoft 365 apps such as Word, Excel, PowerPoint, Outlook, and Teams by asking questions in natural language. Examples include the following.

• Provide a first draft of a Word document, PowerPoint presentation, or Excel spreadsheet for review.
• Reduce administrative work by summarizing and suggesting replies to emails, taking meeting notes and recording action items, and the like.
• Provide team updates and highly customized responses by connecting to an organization’s business data.

Microsoft 365 Copilot “generates answers anchored in your business content—your documents, emails, calendar, chats, meetings, contacts and other business data—and combines them with your working context—the meeting you’re in now, the email exchanges you’ve had on a topic, the chat conversations you had last week—to deliver accurate, relevant, contextual responses,” says a Microsoft blog post.

See this video with ways to use Microsoft 365 Copilot.

“The Guide to Usefulness of Existing AI Solutions in Nonprofit Organizations” shares multiple examples of AI tools that you can use today. NetHope, a consortium of over 60 leading global nonprofits tapping technology innovation to solve the world’s challenges, prepared the guide.

With AI, nonprofits can write or edit documents and check style and grammar, says the guide. Organizations can prepare marketing content or grant applications. Additional examples include the following:

• Convert speech to text or vice versa.
• Create images, video, and music, including editing unwanted items out of images and using AI-generated faces to protect the privacy of people you serve.
• Generate code and find bugs.
• Use voice assistants for search and AI tools to take meeting notes.
• Create digital humans for customer service that can dialogue with customers in real time.

What Does AI-Generated Content Look Like?

To illustrate the efficiency of these tools, LeadingAge CAST Vice President Scott Code created an introductory video for the Generative AI session at the 2023 LeadingAge Annual Meeting.

Code used the scena.ai website, which turns text into interactive videos by using a scenario-based dialogue editor. To create the video, Code chose an avatar through scena.ai, created a video script using ChatGPT, then pasted the script into the scena.ai dialogue box. An hour later, the video was complete.

No coding is required to use these tools. The videos can apply to a variety of use cases, such as staff training and onboarding, website promotions, sales, and customer support. 

Currently, scena.ai costs between $0 and $225 per month. While many generative AI tools are free, such as the basic version of ChatGPT, upgrades bring more features and faster service. Costs vary greatly depending on the service.

Risks to Consider

While generative AI brings many positives to aging services organizations, these emerging technologies also bring risks. The NetHope guide identifies these important considerations:

• Understanding the accuracy of AI-generated results.
• Calculating up-front costs and costs in staff time as well as potential liabilities.
• Taking essential precautions around data ownership, data privacy, security, and ethics.

“Organizations must penetrate the ‘black box’ where it is not obvious how the inner workings function and where the intelligence is provided from,” says the guide. “It is key that employees implementing and working with AI understand how it works, that they can validate output and address risks, and are able to understand and explain decisions made by AI.”

The guide encourages nonprofits to find the balance in using AI, weighing when AI is most beneficial and when humans are. Nonprofits should also consider AI’s short-term impact on jobs and ethics and long-term socio-economic change that AI may bring.