Industries worldwide have integrated artificial intelligence (AI) into their systems as it promotes efficiency, increases productivity, and quickens decision-making. ChatGPT certainly raised eyebrows as it demonstrated similar characteristics at the start of its debut back in November 2022.
The healthcare sector alone, according to Insider Intelligence, has experienced significant improvements in its medical diagnoses, mental health assessments, and faster treatment discoveries after the deployment of AI.
Risks of AI in Healthcare
As more healthcare software systems include AI-based features, the necessity for gathering more data increases. It’s important to assess potential privacy and security issues in AI. Using artificial intelligence in healthcare poses a risk to privacy and compliance within regulatory frameworks, such as the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Security Rule.
In this article, we highlight protocols that will aid in combating these risks to ensure artificial intelligence systems remain compliant with HIPAA and maintain patient trust.
The Difference Between Artificial Intelligence and Machine Learning
When talking about artificial intelligence, oftentimes machine learning is synonymously referenced. Artificial intelligence is an umbrella term that covers a wide variety of specific technological mechanisms and algorithms. Machine learning sits under that umbrella as one of the major subfields, similar to robotics and natural language processing.
Hence, it’s important for us to highlight the nuances in this area. When we refer to artificial intelligence in this article, we’ll be referring to it generally and encompassing both artificial intelligence and machine learning.
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