As the popularity of artificial intelligence (AI) grows, so does the likelihood that poor long-term planning will become more commonplace. While AI has the potential to make planning more efficient, it also has the potential to exacerbate the problems associated with poor planning.
There are a number of reasons why AI may lead to poor long-term planning. First, AI systems are often designed to optimize for short-term objectives rather than long-term outcomes. This can lead to sub-optimal plans that may not be apparent until it is too late to change course. Second, AI systems lack the ability to effectively handle uncertainty. This means that they are often not well-equipped to deal with the complex and ever-changing nature of the real world. As a result, their plans may be based on inaccurate or out-of-date information. Finally, AI systems are often biased in favor of the status quo. This can lead to plans that are stuck in counterproductive routines or that fail to take advantage of new opportunities.
Fortunately, there are a number of ways to address these problems. One approach is to explicitly incorporate long-term objectives into the goals of the AI system. Another approach is to design AI systems that are better able to handle uncertainty through techniques such as reinforcement learning. Finally, it is possible to debias AI systems by training them on data sets that are free from bias.
With proper design and implementation, AI can be a powerful tool for solving problems and achieving goals. However, it is important to be aware of the potential pitfalls associated with AI-based planning in order to avoid them.
References:
https://www.nature.com/articles/s41598-019-49167-0