What Do We Really Know About How these AI Systems Work?
It seems like all our favorite apps and software programs are racing to integrate AI into their systems. Everywhere we turn, the platforms we know and trust are hastily offering new AI features. But as with any new technology, it’s crucial to carefully vet and understand the risks of Artificial Intelligence, particularly its core component: Large Language Models (LLMs).
The rise of LLMs, like Chat GPT, Microsoft Copilot, Meta, and many others, has undeniably transformed the world of artificial intelligence. These models have demonstrated remarkable capabilities in understanding and generating human-like text, performing a variety of tasks ranging from drafting emails and composing poetry to streamlining search engines. However, as with any powerful technology, the deployment and development of LLMs come with significant downsides that warrant careful consideration.
Consider These Points Before Integrating AI into Your Business Operations
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- Data Privacy Concerns – What do LLMs do with the knowledge they consume?
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Training Large Language Models (LLMs) involves ingesting vast amounts of data, some of which may inadvertently include private or sensitive information scraped from public domains. This raises significant privacy concerns, as these models could potentially reproduce private data verbatim or use it in unintended ways. Similarly, allowing an AI system access to your database could inadvertently expose your information.
Currently, there is a lack of transparency regarding what information is being used and how it is processed by AI models. Authors, copywriters, and artists are already filing lawsuits against AI tech companies for misusing their work in these models. As we begin using programs like Copilot or other industry-specific platforms, it’s important to consider that other users outside your organization who also use these platforms might be served content developed or inspired by you. Do you have protections in place before providing LLMs access to your database?
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- Transparency and Explainability – More questions than answers.
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One of the critical challenges with LLMs is their lack of transparency. These models operate as “black boxes,” making decisions and generating outputs without clear explanations of how they arrived at those results. This lack of explainability can be problematic in applications where understanding the rationale behind decisions is crucial, such as in healthcare, legal systems, and other high-stakes environments.
Conclusion
While LLMs hold tremendous potential, it is essential to recognize and address the downsides associated with their use. As businesses tasked with ensuring data security and privacy, a balanced and conscientious approach is crucial PRIOR to launching complex technologies like AI within your organization.
We hope that with every new development in this ever-evolving tech landscape, your current IT provider is informing you of both the risks and benefits of such integrations. Your IT should be more than troubleshooting finicky printers; it should be an integral part of your business operations and strategic decision-making.
Impact Business Technology can handle both the small, mundane, everyday tech tasks you need while also providing high-level IT expertise that leverages the power of technology, positioning your business for success.
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