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Artificial intelligence is everywhere today—from healthcare to finance—and the senior care industry is no exception. But when we talk about AI, the conversation often stops at generative AI (GenAI), like ChatGPT from OpenAI, that creates content from text prompts. As groundbreaking as generative AI is, it’s just one tool in a much larger and more complex AI toolbox. In senior living, where care, safety, and quality of life are paramount, CarePredict incorporates AI into our products to benefit older adults in unique ways that make a profound impact.
What is Artificial Intelligence?
Artificial intelligence is simply a machine that mimics human intelligence. The concept has fascinated us for centuries—from the automatons of the Greek God Hephaestus in Homer’s Iliad to Rosie, the robot housekeeper in The Jetsons. Today, AI isn’t just a fantasy; it’s a reality. We interact with AI every day through our smartphones, social media, online shopping, and even our Roomba vacuums. Self-driving cars are making significant strides thanks to AI. What once seemed like science fiction is now part of our daily lives.
Two Different Types of AI
AI falls into two categories: generative and traditional. Most people are familiar with generative AI because it’s making headlines, but traditional AI has quietly been improving senior living for years.
Generative AI gets quite a bit of attention for its ability to create content—images, text, and more. Meanwhile, traditional AI works behind the scenes, performing specific, repetitive tasks and uncovering meaningful insights. Traditional AI focuses on analyzing data and making predictions, while generative AI combines learned information to produce new variations of content.
Generative AI
Generative AI draws on massive datasets to produce content—whether a business letter or a piece of art—but always based on past examples of human creativity.
People are most familiar with generative predictive transformers, also known as large language models (LLMs), which are robust neural networks with billions of features or “tokens.” LLMs don’t create new ideas; they rearrange existing concepts based on what they’ve been trained on. For example, when GenAI creates an image, it draws upon images it has encountered before and adapts them to fit a particular style, such as impressionism or pointillism.
However, in senior living, where predicting and responding to care needs is critical, GenAI takes a backseat to traditional AI technologies that work with real-time data to support vital care decisions.
Traditional AI
Traditional AI is about data analysis. We humans design the rules, and traditional AI mimics the learning and problem-solving functions of the human brain to analyze and interpret data to achieve specific goals, recognize patterns, find correlations, and make predictions.
Components of Traditional AI include:
- Machine Learning is the branch of AI where systems “learn” from data. For instance, machine learning can help identify patterns in movement that could signal an increased risk of falling.
- Deep Learning involves layers of neural networks modeled after the human brain that can manage complex, multi-dimensional data. In senior living, we can analyze vast amounts of health and wellness data to find early indicators of illness or decline.
- Neural Networks allow AI to process information in a way that resembles human thought. These networks evaluate complex data, such as activity and behavior signals, and find correlations between a set of disparate data and a labeled outcome.
Applications for Senior Living Wearables
One of the most potent applications of traditional AI in senior living is wearable technology. We designed CarePredict’s wearable devices using traditional AI to monitor activity, behavior signals and health metrics to assess risk, analyze the data and enable proactive interventions that enhance residents’ lives, and support critical decision-making by caregivers and medical providers.
Devices such as CarePredict’s Tempo series of senior wearables autonomously monitor seniors’ daily activities and alert care staff if something seems off. A change in movement or routine prompts the system to alert care staff. Over time, these wearables “learn” a senior’s typical routines and provide personalized insights to support healthier aging.
These wearables do more than collect data. They help predict potential health issues before they arise, enabling caregivers to take a proactive approach to wellness. It’s about preventing problems rather than reacting to them.
CarePredict: An Early Innovator in Senior Living AI
With ‘the father of AI,’ Geoffrey Hinton whose experience served as an early validation of our innovative work in senior care .
Our very first wearable in 2015, Tempo Series 1, used machine learning to learn gestures of the dominant arm and to classify eating activity by modeling the fork being lifted from the plate to the mouth.
When we met Nobel Prize winner Geoffrey Hinton in 2017, his pioneering work in neural networks and deep learning validated CarePredict’s early adoption of deep learning AI in senior care. That same year, we began using deep-learning models to predict health declines based on changes in activity and behavior patterns, building upon the activity classifiers from our machine learning.
Our system isn’t just about collecting data; it’s about interpreting it. CarePredict uses machine learning and predictive algorithms to create a complete picture of each resident’s health. If a resident suddenly becomes less active or spends more time in bed, our system spots the change and alerts caregivers so they can act before a minor issue becomes a genuine problem.
Real-World Benefits of Traditional AI in Senior Living
Traditional AI tools not only improve residents’ quality of life; they also make life easier for caregivers. Here’s how:
- Helping to Prevent Falls: Wearables and monitoring systems can detect changes in movement that can signal a fall risk—helping to prevent one of the most significant risks to seniors’ health.
- Personalizing Care Services: Traditional AI learns each resident’s unique behaviors to recognize health trends. It analyzes these behaviors and helps caregivers provide personalized, proactive care.
- Boosting Caregiver Efficiency: AI technology becomes a force multiplier for care staff, supplementing human observations and reducing much of the guesswork involved in monitoring residents’ health. Using real-time data and predictive insights helps staff deliver faster, more effective care.
- Reducing Staff Burnout: AI-supported monitoring and predictive systems help care staff manage their workloads more effectively, reducing burnout.
When it comes to senior living, AI is so much more than just a buzzword. Traditional AI is revolutionizing elder care, driving innovations like CarePredicts remote-monitoring wearable systems. These innovations improve safety, enhance longevity, ease caregiver stress, and give residents and their families greater peace of mind. That is the real promise of AI in senior living.
