Rethinking AI and Data Privacy: My Take on the Cloud
Mark Presnell aka Mr Integration
What did your eCommerce website and your business software say to each other...? Nothing. They don't talk! :)
The world of artificial intelligence (AI) has been evolving rapidly, and with it, our approach to data privacy and trust in the cloud. It's a shift that's caught many by surprise.?
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For a while now, there's been a strong trend toward using cloud-based AI systems. The convenience, scalability, and seemingly endless possibilities the cloud offers have been a logical choice for businesses and organisations.??
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The issue is whether we can truly trust the cloud to safeguard our sensitive data and preserve privacy. It's a question that has prompted some to reconsider their reliance on cloud-based AI in favour of on-premises servers.??
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The capabilities of AI are undeniably impressive. It's like having an enormous library of knowledge at your fingertips, and AI can access it all in mere seconds, while a human might take days to find a specific book. But here's the thing – what AI (as we know it) excels at is recall, not creation.?
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Think of AI as a brilliant librarian who can organise and retrieve information with incredible speed and accuracy. But when it comes to original thought, AI needs to catch up. It's not about inventing something entirely new; instead, it's about rearranging known elements innovatively. Even those stunning artworks and coherent texts generated by AI are based on existing patterns and information. Original thought? Not AIs strong suit.?
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So, what does this mean for businesses and research institutions??
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1. We must focus on building internal knowledge. Businesses should develop internal knowledge bases, especially in customer service and retail. By keeping AI systems on-premise, they can create customised frameworks for service delivery, leveraging AI's recall abilities to enhance customer interactions.?
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2. Industry-specific AI exploration is crucial. Enterprises should invest in understanding AI applications specific to their fields. Staying informed about the latest trends and possibly reverting to more robust on-premise systems can help manage the extensive data requirements of AI effectively.?
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3. Data ownership and confidentiality are paramount. When you input information into cloud-based AI services, it becomes their property. Businesses must be acutely aware of this and consider the long-term consequences.?
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In conclusion, the movement to on-premises AI solutions reflects a deeper understanding of AI's capabilities and limitations. It also highlights a heightened focus on data security and privacy in an increasingly digital age. It's an intriguing shift in the landscape of AI, one that reminds us that convenience should never come at the cost of trust and data privacy.?