Leader election is a critical and complex component in distributed systems, essential for maintaining consistency and avoiding issues like split brain, where a system becomes divided into disjoint clusters with separate leaders. The article explores various strategies for leader election, such as the simpler bully algorithm and the more robust, albeit complex, Paxos protocol. The bully algorithm assigns leadership to the node with the highest ID but struggles with reliability if that node frequently fails, whereas Paxos ensures consistency and progress as long as a quorum is maintained, but is more challenging to implement. The importance of quorum size is emphasized, as it prevents scenarios where multiple leaders might emerge, leading to data inconsistencies. The text also highlights the practical considerations for implementing these algorithms, suggesting that adopting a well-established method is preferable to developing a new one from scratch due to the potential for unexpected challenges.