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Navigating Security Concerns in the Implementation of Generative AI

While the benefits of the cutting-edge technology of generative AI are significant, organizations must safeguard against data exposure and the generation of harmful content.
Kelsey Brandt
Contributing Writer

Natural Language Processing models have taken the AI world by storm because of their impressive ability to generate natural-sounding text that mimics human language. The most advanced of these is GPT-4, a deep learning model pre-trained on vast amounts of data from the internet which it uses to create new text based on a given prompt. The more data an NLP model is trained on, the better it becomes at generating human-like text. However, as with any innovative technology, there are security concerns from data exposure to malicious content generation. If organizations want to utilize an NLP Model, IT executives must answer how they can safeguard against these concerns while reaping the benefits of this cutting-edge technology.

One of the most significant advantages of NLP models is their ability to increase the efficiency and accuracy of tasks such as content creation, chatbots, and language translation. Utilizing NLP models on tasks like these can help with time and cost savings. With generative AI, organizations can automate repetitive tasks, allowing employees to focus on more critical tasks, increasing productivity and cost savings.

“Generative AI can magnify ethical risks and concerns.”

Despite the potential benefits of generative AI like ChatGPT, there are security concerns that come with implementation. According to a recent report by Deloitte, “by expanding the reach and scale of the decisions machines make, generative AI can magnify ethical risks, such as bias, discrimination, privacy violations, and misinformation. It is important for organizations to carefully consider the implications of the use of generative AI and proactively address potential ethical risks and concerns.” While IT executives may understand the risks and faults of generative AI, training non-technical employees to place a limited amount of confidence in the results of chatbots can mitigate some of these risks.

Top Security Concerns

A leading security concern when implementing generative AI is the risk of sensitive data exposure. NLP models require significant amounts of data to be trained, including customer data, intellectual property, and other confidential information. Italy recently became the first Western country to ban ChatGPT due to privacy and bias concerns. If the GPT model is not properly secured, it may become vulnerable to hacking or other security breaches, resulting in the exposure of sensitive data.

Another security concern is the risk of generating harmful or malicious content. Since NLP models are trained on vast amounts of data from the internet, they could generate offensive, discriminatory, or even illegal content if not appropriately monitored. This could lead to reputational damage, legal liability, and other negative consequences for an organization.

How do technology leaders safeguard against these concerns?

Deloitte recommends businesses take a responsible approach to the use of generative AI models, including:

  • Setting clear guidelines for the use of the model
  • Regularly reviewing and monitoring the generated content
  • Implementing measures to prevent the generation of harmful or malicious content

It is vital for organizations to have a plan to address any issues that may arise from using NLP models like ChatGPT. These safeguards may appear simple in theory, but as generative AI evolves rapidly, they may be more complicated to carry out.

While the benefits of NLP models are substantial, IT executives must approach their use cautiously. By taking a responsible approach to generative AI, businesses can reap the benefits of increased productivity and innovation while minimizing the risk of generating harmful or malicious content. Ultimately, organizations will be looking to their IT executives to ensure that generative AI models are used responsibly and safely to safeguard the organization against the mostly unknown security implications of utilizing generative AI businesses must set clear guidelines for the use of GPT models, regularly review and monitor the generated content, and have a plan in place for addressing any issues that may arise.

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