New artificial intelligence (AI) solutions are improving many processes and functions. Natural language processing (NLP) is a branch of AI used by search engines to understand the text people type when they make a search. Semantic query understanding is an AI function that helps the search engine understand the intent of the query. When these processes are combined with customer data, they drive search results that are accurate and relevant. Technology Magazine brought this interesting topic to us in their article, “AI and data privacy: protecting information in a new era.”
AI models that are built on consumer data must also be built with data privacy in mind. It is understandable that some users are hesitant to use automated systems that collect and use their data, so to remain viable, AI models must incorporate privacy protection in their design as a matter of course.
Much of the most privacy-sensitive data analysis today – such as search algorithms, recommendation engines, and adtech networks – are driven by machine learning and decisions by algorithms. As AI evolves, it magnifies the ability to use personal information. Privacy may suffer if techniques for analysis of personal information grow in power and speed.
Melody K. Smith
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