Data PrivacyGenerative AI: A Threat to Data Privacy?

February 1, 20230


A branch of machine learning called Generative AI is focused with developing algorithms that can produce new data including codes, images, audio, video, texts, etc. Typically, artificial intelligence (“AI”) that can create new content, as opposed to just evaluating or acting on pre-existing data, is known as generative AI.

Commonly, text and visuals are created by generative AI models, including blog entries, code, poetry, and artwork. Such generative AI software makes use of sophisticated machine learning algorithms. In today’s digitized era, generative AI is mostly used to generate code, produce marketing content, and in conversational applications like chatbots. A well-known example of generative AI is the chatbot ChatGPT which is making the headlines recently, that employs AI to provide answers to queries and generate content ranging from answers to queries to legal solutions.

However, what is concerning is the multitude of data that is being collected by such generative AI in order to come up with answers to queries, or create new data. AI and generative AI specifically has been gaining major importance in the recent past, thereby aggravating the privacy concerns pertaining to personal and sensitive personal data.

Therefore, it is pivotal to understand whether such generative AI is actually a threat to the private and confidential data of the users?


In 2022, there was a 38% rise in cyberattacks worldwide, as compared to 2021. Healthcare and education were two of the most heavily attacked sectors, bringing hospitals and educational institutions to a complete halt and leading to public distress.

Like most technologies, generative AI has its own drawbacks, such as security hazards, risks to the privacy of user data, risks to creativity, and difficulties related to copyright. The fundamental problem is that generative AI could be utilised by fraudsters and cybercriminals to obtain sensitive material or data in a fraudulent manner.


The data sets that are used to create AI models often contain sensitive data, such as data collected from facial recognition systems or online purchase histories that represent consumer preferences and behaviors. There is a growing fear that such sensitive personal data may be compromised at any given point of time throughout the deployment of an AI system, whether during data collection, transmission, or publication of the prediction AI.

The Upheaval of ChatGPT

A complex machine learning model called ChatGPT (Chat Generative Pre-Trained Transformer) has been in the news recently. ChatGPT can perform natural language generation tasks with such a high degree of accuracy that it can pass the Turing Test.

Before 2022, enormous volumes of unlabeled data that were scraped from the Internet were used to train ChatGPT. Additional datasets with human-labeled tags have also been added to the model’s training set and is used to continuously monitor and improve it for various language-oriented tasks.

With ChatGPT’s growing popularity, the proliferation of text-to-image tools, and the appearance of avatars in our social media feeds, generative AI seems to have suddenly appeared everywhere in the mainstream media in recent weeks. Beyond entertaining smartphone apps and convenient ways for students to avoid essay-writing responsibilities, the widespread deployment of AI will soon profoundly alter how businesses function, develop, and scale.

The dynamic growth of generative AI like ChatGPT would also invite data protection issues moving forward. The data fed into the systems of such generative AI is often unregulated and in bulk, thereby increasing the chances of data breach and unlawful exploitation of personal data.

Therefore, every business has to bolster its data loss prevention measures at both the endpoints and perimeter. By doing this, the company’s digital assets are protected from leakage, and doesn’t fall in the hands of fraudsters.


Technology related to generative AI is developing at a rapid pace that it is already outperforming our capacity to foresee potential problems. If one wants to stay ahead of the curve and experience long-term, sustainable market growth, we need to find global solutions to important ethical concerns.

We may utilise generative AI as a tool to grow and improve many aspects of our lives, including cybersecurity and safety. Cybersecurity solutions can offer an intelligent system that not only detects advanced cyberattacks but also actively prevents them by integrating AI into a single, multi-layered security architecture.

The field of generative AI is currently developing expeditiously. As the public at large decides how to handle the ethical ramifications of the technology’s powers, there will be growing pains that will come to the forefront only with time. There is no doubt, though, that it will continue to transform the way we use the Internet, given its enormously positive potential.

– Team AMLEGALS assisted by Ms. Bhavika Lohiya  (Intern)

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