Remove government
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Your LLM Gets Its Data From Where??

Salesforce Marketing Cloud

The bad: Scraped data may include copyrighted or trademarked material. The risk of copyright infringement exists with corpus data too, but is more pronounced with scraped data due to its nature. The good: Anyone can access and use this data without restrictions or fear of copyright infringement.

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What Does AI Transparency Look Like? It Depends on Your Industry

Salesforce Marketing Cloud

This lack of transparency threatens privacy and security, and fosters uncompensated use of copyrighted content, according to Senate testimony by Ramayya Krishnan, dean of Carnegie Mellon University’s Heinz College of Information Systems and Public Policy. And that’s being charitable.

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Guidelines for Responsible Content Creation with Generative AI

Contently

This brings several ethical questions to the forefront, including: Who owns the copyright to AI-generated content? For example, using generative AI to produce articles or videos could allow bad actors, authoritarians, and even governments to sow division. So how is AI being governed? Who monitors the output of generative AI?

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How to craft an effective AI use policy for marketing

Sprout Social

Other well-known authors like George RR Martin and John Grisham too, are suing parent company, OpenAI, over copyright infringement. Accountability and governance Your corporate AI use policy must clearly describe the roles and responsibilities of individuals or teams entrusted with AI governance and accountability in the company.

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What does the future hold for genAI? The Gartner Hype Cycle

Martech

The other relates to copyright. These models are based on, as you said, data that includes copyrighted data scraped from the web. It’s there to help people who, say, need to go through 10 documents to get an answer to something; now they can do it in one minute. A: Yes, they are part of the thinking.

Gartner 128
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The Responsible Approach to Generative AI

Content Standard

Generative AI tools, including image generators, have a well-documented tendency to generate discriminatory outputs. Foundational models are often trained on copyrighted works but don’t provide reliable sourcing in their results. But how real are these risks for marketing organizations, and what can you do to mitigate them?

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Marketing leaders, are you actually ready for AI?

Martech

How are copyrights handled (time to engage legal)? If your department is one of these, now is the time to take action to document the details of your stack and the associated data collection, storage, sharing and distribution mechanisms and then work to ensure that everything is being collected, stored, shared and distributed as required.