1. Security Vulnerabilities

•   Hacking and Tampering: EVMs can be vulnerable to hacking, which could alter the election results. Malicious actors could potentially gain access to the machines to change vote counts or disrupt the voting process.

•   Software Bugs: Flaws in the software used by EVMs could lead to incorrect vote counts or other malfunctions, potentially affecting the integrity of the election.
  

2. Lack of Transparency

•   Proprietary Software: Many EVMs use proprietary software, making it difficult for independent auditors to verify the accuracy and integrity of the voting process.

•  No Paper Trail: Some EVMs do not provide a paper record of each vote, which makes it challenging to conduct reliable recounts or audits.

3. Technical Failures

•   Malfunctions: EVMs can experience technical failures, such as screen freezes, power outages, or hardware malfunctions, which can disrupt voting and lead to delays or loss of votes.

•   User Errors: Voters or poll workers may encounter difficulties operating the machines, leading to potential errors in vote casting or recording.

4. Accessibility Issues

•   Design and Usability: EVMs may not be designed to be user-friendly for all voters, including those with disabilities or limited technical skills. This can create barriers to voting for certain populations.

•   Language Barriers: EVMs may not support multiple languages, making it difficult for non-native speakers to understand and use the machines effectively.

5. Cost and Maintenance

•   High Costs: The acquisition, maintenance, and upgrading of EVMs can be costly for governments. This includes the cost of training poll workers and providing technical support during elections.

•   Obsolescence: EVMs can become outdated, requiring expensive replacements or upgrades to keep up with technological advancements and security needs.

6. Public Trust and Perception

•  Mistrust: Concerns about the security and reliability of EVMs can erode public trust in the electoral process. Misinformation or lack of understanding about how the machines work can exacerbate these concerns.

•  Perception of Bias: If certain groups believe that EVMs are more prone to errors or manipulation, it can lead to perceptions of bias or unfairness in the election process.