What is the result of poor algorithm complexity?

Poor algorithm complexity leads to longer execution times and higher resource consumption because it often indicates that the algorithm is inefficient in terms of how it processes data. When an algorithm has a high time complexity, it may require an excessive amount of time to complete its tasks, especially as the size of the input data increases. This inefficiency can result in delays, making the algorithm slower and less responsive.

Additionally, algorithms with poor complexity may consume more computational resources, such as CPU time and memory, as they may have to perform redundant or unnecessary operations. In practical applications, this can cause significant slowdowns and affect the overall performance of the software or system.

In contrast, more readable code, increased security risks, and greater collaboration opportunities are not direct results of poor algorithm complexity. Readability often stems from good coding practices rather than complexity, while security risks relate more to vulnerabilities in the code itself rather than how complex an algorithm is. Lastly, collaboration opportunities are more associated with clear coding conventions and good documentation rather than the algorithm's efficiency.