ChatGPT continues to create a buzz since its release in December last year. While ChatGPT can revolutionize the way we interact with artificial intelligence, it is essential to acknowledge and address the potential risks associated with its use. This blog explores the risks and challenges of implementing such technologies and strategies that organizations can apply to mitigate these.
Key Risks & Challenges in Using ChatGPT
Understanding the Challenges and their Mitigation Strategies
| Risks | Mitigation |
| Information Privacy & Confidentiality | |
| With data and models hosted in the cloud and ChatGPT models trained on enormous volumes of textual data, there is a significant risk of data breaches or unauthorized access to private information. | Companies must ensure that appropriate privacy and security measures are implemented. These measures should include using encryption to safeguard data both in transit and at rest, implementing access controls and identity management policies in place, and regularly monitoring and auditing data access and usage. |
| Inaccurate responses | |
| Responses from ChatGPT might not always be precise or reliable. Since ChatGPT bases its responses on patterns and trends, it has discovered from training data; it might not have access to the most recent or accurate information. | To increase their accuracy and dependability over time, cross-referencing the data provided with credible sources or consulting with experts in the relevant field is required to verify the correctness of ChatGPT’s responses. |
| Copyright or IP Issues | |
| ChatGPT uses proprietary data for training a machine learning model without proper authorization or consent. This could lead to legal issues, such as copyright infringement and breach of contract. | It is crucial to obtain proper authorization or consent from the owners of the proprietary data before using it for training a machine learning model like ChatGPT. This may involve signing non-disclosure agreements or obtaining written permission from the data owners |
| Misinformation or Deep Fakes | |
| Misinformation or misleading information may be spread intentionally or unintentionally. Since ChatGPT can generate large volumes of text, these could be used by malicious actors to spread fake news articles or social media posts designed to manipulate public opinion or deceive people. Deepfakes, on the other hand, are media that use artificial intelligence to create convincing fake videos or audio recordings of people saying or. | Stringent regulatory and legal frameworks must be established to address and penalize the creation, distribution, or use of misinformation and deepfakes. |
| Fraud & Abuse | |
| ChatGPT increases the persuasiveness of their emails and helps create content comparable to messages written by humans, phishing is now easier for hackers on the internet. Malicious hackers can use ChatGPT to create low-level cyber tools like encryption scripts and malware, providing an opportunity to accelerate malicious cyberattacks against system servers. | Dealing with fraud and cyber-attacks requires a multifaceted approach. It is vital to have Data Security measures in place to ensure that the data used to train ChatGPT is stored and transmitted securely to prevent unauthorized access, modification, or theft. |
| Lack of transparency and explain-ability | |
| ChatGPT models use complex algorithms and machine learning techniques to generate outputs, and this lack of transparency and explainability can be a barrier to adopting and accepting these models, particularly in critical domains such as healthcare, finance, and law. | The resolution to this issue may not be simple and straightforward but it will be prudent to identify use cases that do not have a requirement of model transparency. |
| Limitations of computing power | |
| ChatGPT is a complex language model that requires significant computing resources to operate. It often requires large companies such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure for hosting and running large-scale natural language processing (NLP) | Companies must consider the data privacy and security implications while partnering with hyperscalers and ensure appropriate safeguards to protect user data and compliance with applicable regulations. |
Closing Thoughts
ChatGPT entails several hazards, just like any other emerging technology. Businesses must assess the value they provide while evaluating the risks. The need of the hour is for a balanced approach to employing the enterprise value that ChatGPT and other Gen AI technologies bring in while putting in place frameworks, policies, and controls to manage and mitigate risks.
The risks must be addressed by adopting appropriate security measures, including data encryption, bias detection and mitigation, fact-checking and verification, and content screening. Once these measures are taken, ChatGPT will be able to provide a positive user experience free from discrimination, false information, and offensive language or content.
