Artificial intelligence is revolutionizing industries, driving innovation and enhancing productivity. Paradoxically, it also has the potential to undermine the very companies that adopt the tools.
Nothing is inherently flawed with this, and it is only natural that as we transition from theoretical or academic knowledge into applied knowledge, we gain a lot of practical work experience. From the perspective of the teams maintaining the AI tools, this conundrum can fail to optimize AI systems properly. When AI systems lack high-quality input for training, their outputs deteriorate over time. Consequently, this cycle perpetuates itself, leading to progressively poorer outcomes.In the short term, the effects of this dependency on AI may not be immediately apparent. Current workforce structures still include experienced professionals who manage and supervise production effectively.
Many drivers, for example, now rely on GPS devices. This reliance can lead to a loss of important skills like reading maps and following directions. What happens when technology fails? A 2020 study showed thatrelied less on hippocampal-dependent spatial memory. Not only did they have a reduced sense of orientation, but lesser grey matter in the hippocampus.
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