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Safely enable the use of generative AI applications with application access control, real-time user coaching, and best-in-class data protection.

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Safely Enable ChatGPT and Generative AI
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What is Generative AI?

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Generative AI is a groundbreaking technology that is reshaping industries and driving innovation. Here you will find a comprehensive overview of generative AI, learn how it functions, explore real-world examples, delve into potential corporate risks associated with leveraging generative AI apps like ChatGPT and BARD, and discover how Netskope can safely enable usage at your organization.
Safely Enable ChatGPT and Generative AI
5 min read

How does generative AI work? link link

Generative AI is a branch of artificial intelligence that empowers computers to create original and realistic content, such as images, text, music, and more. This technology generates new outputs by harnessing the power of machine learning models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

Generative AI models learn from extensive datasets during a training phase, capturing patterns and structures present in the data. For instance, GANs consist of a generator and a discriminator. The generator produces content resembling the training data, while the discriminator distinguishes between real and generated content. Through an iterative process, the generator improves its output by fooling the discriminator, resulting in the creation of increasingly authentic and high-quality generated content.


What are examples of generative AI? link link

Generative AI showcases its versatility across numerous use cases. Here are some compelling examples:

Text Generation: Language models like GPT-3 are capable of generating human-like text based on a given prompt. These models can generate stories, articles, poems, and even code snippets based on the input they receive. They have been used for creative writing, content generation, and chatbot applications.

Data Augmentation: Generative AI can be used to augment datasets for training machine learning models. By generating new synthetic data, it helps to increase the diversity and quantity of training samples, which can improve model performance.

Coding Development: Generative AI models can be used to assist in coding tasks. For example, code completion models can generate code suggestions based on partial input, helping developers write code more efficiently. Models can also be trained to generate code snippets or templates for specific tasks or programming languages.

Image Synthesis: Generative models can generate lifelike images, revolutionizing fields such as art, design, and advertising.

Music Composition: Leveraging generative models, musicians and composers can explore novel melodies, harmonies, and even compose complete musical pieces.


What are the potential corporate risks of leveraging ChatGPT and generative AI? link link

While the advantages of leveraging ChatGPT and generative AI are substantial, it is essential to be aware of potential corporate risks, including:

Data Privacy and Security: The implementation of generative AI models involves handling vast amounts of data, necessitating stringent data protection protocols to prevent data leakage as well as to comply with any state and federal regulations. Employees may upload sensitive data like personally identifiable information (PII) and intellectual property (IP) or financial data into a generative AI app such as ChatGTP. There is the potential to lose control of that data that could lead to external exposure and therefore irreparable harm to an organization’s bottom line.

Inappropriate Content: Unmonitored generative AI models can produce content that may be offensive, biased, or unsuitable, which can harm a company’s reputation.

Copywriting Infringement: Content (text and images) generated from generative AI models could come from other public sources while it looks unique, possibly violating copyrights.

Legal, Privacy, and Ethical Concerns: Generated content may not comply with legal regulations and ethical guidelines, leading to potential infringement on intellectual property rights and irresponsible use of the technology. Additionally, the upload of private/protected information into a chatbot can violate data privacy and compliance regulations.


Blog: Build a Culture and Governance to Securely Enable ChatGPT and Generative AI Applications—Or Get Left Behind
Solutions: Safely Enable ChatGPT and Generative AI
Webinar: ChatGPT: Fortifying Data Security in the AI App-ocalypse


How can your company safely enable generative AI? link link

At Netskope, we believe in the safe and responsible implementation of generative AI. Here’s how we help organization safely enable apps like ChatGPT:

App Usage Visibility and Monitoring: Using the industry’s broadest discovery and most granular categorization of SaaS and IaaS services, the Netskope solution is designed to discover and monitor the use of ChatGPT and other generative AI apps across a company’s entire network. Using Netskope Advanced Analytics, Netskope provides app usage visibility, including context and instance identification, data movement and exposure, as well as user behavior and insider risk discovery..

Data Privacy and Compliance: Our company upholds granular data security and privacy protocols, safeguarding sensitive information, and adhering to regulatory requirements. Netskope DLP identifies flows of sensitive data with the highest level of precision, preventing any unsafe exposure on SaaS applications like ChatGPT, as well as on personal SaaS apps’ instances. With Netskope’s data loss prevention (DLP), powered by our own ML and AI models, thousands of file types, personally identifiable information, intellectual property (IP), financial records and other sensitive data are confidently identified and automatically protected from unwanted and non-compliant exposure.

Automatic user coaching and real-time data protection: While applications that are more explicitly malicious should be blocked, when it comes to access control, oftentimes the responsibility of the use of applications like ChatGPT should be given to the users. Organizations may want to consider tolerating (versus blocking) activities that make sense to a subset or to a majority of employees. At the same time, security teams have the responsibility to make employees aware of applications and activities that are deemed risky. This can be accomplished through real-time alerts and automated coaching workflows, involving the user in the access decisions after acknowledging the risk. Netskope Data Loss Prevention (DLP) offers several enforcement options to stop and limit the upload and posting of highly sensitive data through generative AI apps. This real-time enforcement applies to every user connection, ensuring data is safe anytime, anywhere.


What are precautions and key security recommendations around the use of generative AI applications? link link

Using AI models like ChatGPT in a business setting offers significant advantages in terms of productivity, efficiency, and innovation. However, ensuring data privacy and security is crucial when utilizing such AI models. Netskope has defined enhanced best practices for security teams and employees to protect their company’s data: Local Deployment, Data Anonymization, Data Encryption, Strict Access Control. Read more in our Netskope for ChatGPT and Generative AI Data Protection Solution Brief.

Netskope is a market leader in cloud security and data protection offering the broadest visibility and the finest control over thousands of new SaaS applications like ChatGPT. Learn how Netskope can help safely enable generative AI apps at your organization. Get started today!

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