Artificial Intelligence (AI) is become an increasingly integral part of our lives, shaping our interactions and experiences in many ways. Even if we do not use AI directly, it is likely that the services we rely on will. As AI technology continues to evolve, it is crucial to consider the potential implications and risks associated with this dependence, particularly in terms of cost, portability, and resilience.
AI technology, like other advanced technology, comes with a hefty price tag. This is primarily due to the specialized hardware required to run AI systems, which is both expensive and energy-intensive. As competition in the AI space increases, we may anticipate an upward trend in hardware and electricity costs, which will invariably be passed on to the consumers.
The mobile phone industry provides an interesting comparison. Initially, mobile phones were a luxury item, but as subscriber numbers grew, prices dropped. However, AI might follow a different trajectory, akin to home internet service, where each subscriber requires a physical connection, thus maintaining a high cost for subscription.
Scalability is another crucial factor. Mobile phone services, built to scale from the start, allow subscribers to connect to any of several towers in an area, even roaming to another network on the same tower. Mobile operators need only add more towers to expand their footprint. AI, on the other hand, is entirely cloud-based. The robustness and cost-effectiveness of the cloud infrastructure will play a significant role in determining the scalability and affordability of AI services. It is not a simple matter to add gigawatts of capacity to an electric grid as expanding data centers may require.
A significant concern for consumers is the potential risk of being priced out of access to an AI service. Switching to a lower-cost AI service may seem logical, but the absence of a system to port user history to the new provider can be a significant obstacle. The consumer-AI relationship is akin to a working relationship. Changing AI is as disruptive as losing a key employee, requiring time and effort to adapt to the new AI's interface, workflow, and algorithms.
Furthermore, even when sticking with the same AI provider, upgrades can significantly impact the user experience. Each iteration of an AI model will have different emergent properties, which could be better or worse for the user. It's akin to getting to know a person all over again after a brain injury, with each new version bringing its own set of strengths and weaknesses.
Finally, the reliance on AI raises the question of resilience. What happens when we are cut off from the AI service? As AI becomes integrated into our daily lives, much like mobile networks, loss of AI service can be critical. This could be particularly true if the AI had served as your emotional support or business operations backbone.
In conclusion, as we embrace the convenience and advantages brought about by AI, it is crucial to be mindful of the potential challenges and risks. From cost considerations to portability and resilience, these are important factors that will shape our future relationship with AI. It's becoming a new world, and we must navigate it with care, foresight, and a mindful foresight of potential pitfalls.