What Are the Most Significant Risks for Employers in Utilizing Generative AI and Protecting Data?

Q: How long will it take to read this news story?

The story "What Are the Most Significant Risks for Employers in Utilizing Generative AI and Protecting Data?" has 1015 words across 55 sentences, which will take approximately 5 - 9 minutes for the average person to read.

Q: Which news outlet covered this story?

The story "What Are the Most Significant Risks for Employers in Utilizing Generative AI and Protecting Data?" was covered 1 months ago by Forbes, a news publisher based in United States.

Q: How trustworthy is 'Forbes' news outlet?

Forbes is a fully independent (privately-owned) news outlet established in 1917 that covers mostly startups and technology news. The outlet is headquartered in United States and publishes an average of 36 news stories per day. It's most recent story was published 13 hours ago.

Q: What do people currently think of this news story?

The sentiment for this story is currently Neutral, indicating that people are not responding positively or negatively to this news.

Q: How do I report this news for inaccuracy?

You can report an inaccurate news publication to us via our contact page. Please also include the news #ID number and the URL to this story.<ul><li>News ID: #21101711</li><li>URL: https://beamstart.com/news/generative-ai-and-data-protection-17167953327105</li></ul>

Forbes Logo Forbes 1 mo ago

What Are the Most Significant Risks for Employers in Utilizing Generative AI and Protecting Data? - Forbes

Quick Summary:

As a basic protection, I would recommend that any data submitted to a generative AI service should be anonymized and stripped of any personally identifiable data.

And this means it’s extremely risky to feed that data into a generative AI tool.Why?

Delve into the terms and conditions of many generative AI tools, and they’ll clearly state that data submitted to the AI could be used for training and fine-tuning or disclosed when users ask to see examples of questions previously submitted.