Reduces Pressure On Your In-house Talent PoolWhen you employ your existing team members to collect data and annotate it, you are either asking them to work additional hours or compensating them for it. Or, you are asking them to accommodate this task amidst their work hours and tight deadlines.Regardless of the case, it adds pressure on your employees and it would spoil the quality of both the tasks they are trying to juggle. This could lead to attrition and more expenses on training new recruits. In this instance, crowdsourcing data collection arrives as a reliable alternative as your team has standardized data in their hands to work on.Highly ScalableRelying on internal sources to generate more volumes of data than the current numbers could prove expensive. While collaborating with data collection and annotation companies would be a better alternative. (Read: Points to be kept in mind while shortlisting a data collection vendor.)Crowdsourced work comes as a relief by allowing you to scale your data volume requirements. You could both increase your data volume or decrease it at any given time. All you have to do is ensure there are adequate QA processes set to ensure quality output.Cons Of Data CrowdsourcingMaintaining Data ConfidentialityMaintaining data confidentiality is a huge task ahead of you when it comes to crowdsourcing. Now, it is on the vendor and crowdsources team to maintain and respect data integrity and confidentiality by adhering to protocols and data privacy standards. If the data is related to healthcare, additional measures and compliances like HIPAA should be met as well. This could take a significant portion of your team’s time setting the protocols up.Wavering Data QualityThere is no guarantee that the final quality of the data you receive will be airtight and impeccable if controlled properly. One of the major drawbacks of crowdsourcing data collection is that you will encounter wrong and irrelevant data. If your process is not set up right, you could end up spending more time and money on this than working with data vendors.That’s why we recommend checking out our crowdsourcing guidelines. Lack Of Data Standardisation
When you work with data vendors, there is a specific format or standards followed when they send final datasets to you. You would understand that they are machine-ready files that could be uploaded without second thoughts.With crowdsourced work, that’s not the case. There is no proper standard followed and it all depends on individual contributors and how experienced they are at participating in crowdsourcing data. You could receive both haphazard and clean files from time to time, making it difficult for you to establish standards.So, What’s Better?It depends on your urgency and budget. If you feel you have a very limited time and crowdsourcing data collection is the only inevitable way forward, it would work because you would be willing to compromise on a few aspects as we discussed.However, if you feel your AI ambitions are more important and that you wouldn’t offer any scope or space for concerns to crop up, the best way forward is to look for ideal data vendors like us how can help you reap the benefits of crowdsourcing.