How to Manage Data Risks When Using Generative AI

IndustryTrends

Generative AI is a type of artificial intelligence that can create new content or data based on existing data, such as text, images, audio, or video.

Generative AI poses various data risks, such as data privacy, data quality, data bias, data security, and data ownership.

Data privacy refers to the protection of personal or sensitive data from unauthorized access, use, or disclosure.

Generative AI may violate data privacy by using or storing personal data without consent, or by generating realistic but fake personal data that can be misused. 

Generative AI may affect data quality by generating inaccurate, incomplete, inconsistent, or invalid data that can lead to errors or poor decisions. 

Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

                                                                                                       _____________                                             

Disclaimer: Analytics Insight does not provide financial advice or guidance on cryptocurrencies and stocks. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. This article is provided for informational purposes and does not constitute investment advice. You are responsible for conducting your own research (DYOR) before making any investments. Read more about the financial risks involved here.

Read More Stories