Artificial Intelligence (AI) is a broad area of computer science involving technologies that can learn to make decisions and perform tasks that previously required human action.
At its core, AI depends on two things – data and the models used to train algorithms to behave in certain ways based on the data. AI can manipulate the algorithms by learning behavior patterns from the data set. Greater quantities and higher quality data sets result in higher performance from the AI.
Some AI applications, such as facial recognition software, social media algorithms, and self-driving cars have gained notoriety and raised legal and ethical concerns. More commonly, however, AI is being used to accomplish undertakings impractical for humans, such as discerning patterns and predicting outcomes from massive amounts of data, or to perform routine tasks that take valuable time from workers whose talents might be put to better use.
Some AI applications drive common consumer experiences, such as personalized shopping recommendations, chatbots and voice assistants, spam filters, and GPS technologies. Businesses use AI for employee recruitment, security and fraud prevention, transportation logistics, and personalized marketing, to name just a few examples.
Many AI applications are built on foundational, or large language models, which can be adapted to a wide range of downstream tasks. Generative AI systems, such as ChatGPT and GPT-4, are being used to generate foundational content for reports, articles, scripts, and even musical scores.
AI technologies are advancing quickly, and the use of AI in business has been growing steadily. Since 2017, the number of organizations that report using AI has increased 2.5 times. Many, industries are using AI in some form today, as well as planning to expand its applications going forward, including the healthcare and workers’ compensation sectors.
AI Terms to Know
- Speech Recognition converts human speech into text or code
- Computer Vision scans images and uses comparative analysis to identify objects with the image
- Machine Learning builds algorithmic models that can identify patterns and relationships in data
- Expert Systems use knowledge bases to solve problems and simulate decision making of human experts
- Foundational Models are large language AI models trained on vast amounts of data that can be adapted to a wide range of tasks
- GPT stands for Generative Pre-Trained Transformer, a type of foundational AI that is trained on troves of data to generate human-like content
- Generative AI is another term common term used for GPT technologies, which include ChatGPT and GPT-4
AI And Healthcare
Currently, AI is being used by hospitals and healthcare systems in multiple ways, including adverse-event prediction, schedule optimization, and inventory control. Healthcare providers are using AI for such applications as chronic disease management and personalizing the patient experience.
However, overall adoption is still in early stages. Only 14% of healthcare professionals report using AI today, and 33% believe that AI will hurt the healthcare industry more than it helps. Industry analysts disagree, however. According to McKinsey, “AI represents a meaningful new tool that can help unlock a piece of the unrealized $1 trillion of improvement potential present in the [healthcare] industry.”
