AI Today Podcast: Generative AI Series: How to Avoid Getting Screwed with Generative AI
Oct 27, 2023
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The podcast discusses the negative impacts and challenges of generative AI, the importance of verifying and validating its responses, changes in the quality of responses due to moderation features, the potential negative impact of relying too heavily on generative AI, and understanding the power and challenges of generative AI.
Human verification and validation is crucial in generative AI to avoid presenting inaccurate or misleading information to users.
Generative AI systems are dynamic and can exhibit variations in performance, requiring continuous monitoring and adaptation to ensure desired outcomes.
Deep dives
Avoiding Issues with Generative AI
Generative AI has been touted as a powerful and transformative technology, but it comes with its own set of challenges. One of the main concerns is the lack of human verification and validation in the responses generated by AI systems. When humans are not involved in verifying the accuracy and quality of AI-generated content, serious issues can arise. An example of this is when generative AI systems are used to provide responses on websites without human oversight, leading to inaccurate or misleading information being presented to users. It is important to always have subject matter experts in the loop and actively validate the responses to avoid such problems.
Changing Nature of Generative AI Systems
Generative AI systems are constantly evolving, and their behavior and responses can change over time. Updates to the models and interfaces can lead to unexpected shifts in the quality and accuracy of the generated content. For example, users of GPT-3.5, a popular generative model, noticed a decrease in response quality after changes were made to moderation features. It is crucial to understand that generative AI systems are not static and can exhibit variations in performance, even if the prompts and settings remain the same. This dynamic nature of AI systems requires continuous monitoring and adaptation from users to ensure desired outcomes.
Potential Pitfalls and Unforeseen Consequences
The increasing reliance on generative AI systems can have unintended consequences and potentially disrupt workflows, job roles, and industries. As AI-powered solutions become more capable and efficient, there is a risk of rendering certain tasks and roles obsolete. This can lead to a loss of specific skills and human oversight, affecting the overall quality and validation of the generated content. Additionally, the temptation to depend solely on AI systems, particularly when they are affordable or free, can create long-term challenges. As prices increase or business models change, organizations may find themselves stuck with technologies they heavily rely on, leading to potential disruptions and increased costs. It is essential to consider the long-term implications and build resilience in the face of evolving AI capabilities.
It’s hard to have a conversation about AI these days without the topic of Generative AI coming up. People are using gen AI to help with many things from text creation, image creation, and more. But, just like with any technology, there can be a downside as well.
However, what happens when we become too reliant on technology?