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A Shift In Data Privacy And Trust: Can We Trust The Cloud?

In an unexpected development in the evolution of artificial intelligence (AI), many companies may reconsider using cloud-based AI systems in favour of on-premises servers. This shift, spurred by increasing concerns over AI's capacity to safeguard data confidentiality and privacy, signifies a notable reversal from the previous trend towards cloud computing.

Mark Presnell, Managing Director of Convergence, an eCommerce integration firm based in Auckland, said that most people were under the impression that the days of on-premise servers had passed. Yet, now we're seeing a potential comeback.

"The abilities of AI are certainly impressive, but they have also posed some worries about entrusting sensitive information to the cloud," he said. "If companies use AI on site, they won't want to be sharing the insights, ideas and plans they generate on an open platform - which is currently the case. It may be that companies keep their AIs on site."

AI: Mostly recall, nothing original

Presnell said that what is often perceived as AI intelligence is advanced recall.

"Consider AI as an immense library. AI can achieve this in mere seconds, whereas a human might take days to find a specific book. However, this is recall, not creation. Generative AI, which produces outputs such as text or images, relies on pre-existing data. It's not inventing something new; rather, it's rearranging known elements in innovative ways."

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Presnell said that while AI can create artworks or compose a coherent text that appears unique, these are based on existing patterns and information.

"AI lacks original thought. It's a potent tool for processing and recalling information but not for originating it."

Implications for Businesses and Research Entities

Understanding AI as primarily a recall tool has implications for businesses and research institutions.

Presnell identifies three critical areas of focus:

1. Building Internal Knowledge

"Businesses, particularly in customer service and retail, should concentrate on developing internal knowledge bases. By maintaining AI systems on-premise, they can create bespoke frameworks for service delivery, utilising AI's recall abilities to enhance customer interactions," he said.

2. Industry-Specific AI Exploration

Presnell suggested enterprises should invest in comprehending AI applications specific to their fields.

"This includes staying abreast of trends and possibly reverting to more robust on-premise systems to manage the extensive data required by AI."

3. Data Ownership and Confidentiality

Data ownership is critical.

"When you input information into cloud-based AI services, it often becomes their property. Businesses must be keenly aware of this and consider the long-term repercussions."

Presnell said the movement back to on-premise AI solutions reflects a more profound comprehension of AI's capabilities and limitations, alongside a heightened focus on data security and privacy in an increasingly digital age.

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