What is it?
Artificial Intelligence (AI) is not a single technology, but rather a field of technology able to perform tasks that normally require human intelligence by using algorithms, heuristics, pattern matching, and other techniques within the realm of computer science. AI has been an area of significant interest for the health care industry for several years, and many health systems, payers, and life science organizations have (or plan to) incorporate AI and automation into their business strategy.
AI capabilities can be broken down into Narrow AI and General AI. Virtually every AI solution today uses Narrow AI. Narrow AI algorithms solve a tightly defined task, such as finding pneumonia in an x-ray, or powering a patient portal chatbot, but have limited utility outside the task for which they were designed. General AI is a more adaptable intelligence that can understand context, quickly adapt to new situations, and apply knowledge to a wide variety of domains—but such AI may be technically impossible to achieve.
Below are a few AI-related terms that are useful to distinguish:
- Advanced Analytics: a broad category including AI, predictive analytics, and prescriptive analytics to augment processes and predict future events
- Machine Learning (ML): a range of techniques including strategies like time-series analysis, which allow computers to learn to perform tasks without being explicitly programmed. Uses advanced statistical techniques to identify patterns in data and then make predictions from those patterns with a degree of certainty
- Natural language processing (NLP): techniques which allow computers to understand human language and communicate back with similar language
- Robotic Process Automation (RPA): the use of automated robots to handle repetitive tasks, generally not highly “intelligent”
Not all AI functions have the same degree of intelligence. This statement equation can explain how to determine the extent of a system’s intelligence: