To some degree, the opacity of AI products can be seen as an extension of this balancing. But AI can introduce additional complexity because many AI tools and models develop analysis, arrive at conclusions, or recommend decisions that may be hard to explain. For instance, some AI approaches are able to identify patterns that were previously unidentified and are intuitively quite hard to grasp.
Depending on what algorithms are used, it is possible that no one, including the algorithm’s creators, can easily explain why the model generated the results that it did. The challenge of explainability can translate into a higher level of uncertainty about the suitability of an AI approach, all else equal.