Use of Generative AI


What it Generative AI?
Generative AI refers to artificial intelligence systems that can generate new content — like text, images, music, videos, and even code — based on the data they’ve been trained on.

Types of Generative AI?

By now most people are aware of generative AI and tools like OpenAI ChatGPT, Microsoft Copilot, Google Gemini, and others. Generative AI refers to software tools modeled on large amounts of data to produce text, images, video and other digital artifacts.  These models produce content based on the patterns and structures they learn from extensive datasets.  

While these technologies offer significant benefits, they also come with potential risks and concerns that must be carefully considered.  

  • One of the primary issues is the potential for disclosing sensitive information. Generative AI tools often require large amounts of data to function effectively, raising concerns about personal data privacy, the risk of inadvertently sharing confidential business information, and FERPA violations. 
  • There are also copyright and intellectual property concerns, as these models may generate content that infringes on existing works. 
  • Another significant issue is the accuracy of the information used by these models. Since generative AI systems are trained on extensive datasets, they can sometimes produce outputs that contain errors or outdated information. This can lead to misinformation and potentially harmful consequences. 
  • Bias and discrimination within the training data is also a major concern. The datasets used to train these models may contain inherent biases, which can be reflected in the generated content.  
  • Ethical use and transparency are crucial considerations as well. It is essential to ensure that generative AI is used responsibly and that the processes behind these technologies are transparent to users and stakeholders.   

 

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