Behind one bit of technology stands another piece of technology that can make a process happen even more effectively.
Our last video touched on how microtasking—breaking up larger tasks into smaller pieces— makes crowdsourcing possible through snippeting.
But what technology makes snippeting possible? How is certain information identified and snippeted before it’s sent to crowd contributors?
This is but one part of the process where ScaleHub crowdsourcing solutions fuse artificial intelligence (AI) with human intelligence. But before we show how AI applies to the crowdsourcing process, it’s important to understand where this technology stands in today’s market, and why it’s essential to enterprise scalability.
OCR: Once novel, never foolproof
For many companies, automated document processing relies on optimal character recognition (OCR). Revolutionary for its time, OCR was a building block for document processing automation.
But OCR has never been sufficient for a company to achieve fully automated document processing, (much less the holy grail of hyperautomation). OCR is helpful, but it’s not 100% accurate. The technology has a studied error rate that’s hard to ignore.
The problem is that OCR, as the initial step of document processing, struggles with exceptions like characters, symbols, handwritten text, or any kind of defect such as a torn or poorly scanned document. Any error introduced into the process will need to be fixed later on via manual intervention.
OCR + People: An undeniable bottleneck
One solution is to have people double-check the accuracy of OCR processing. This “human alert” is activated when OCR reports a predefined low level of confidence in data processing. That’s when a team member must step in to review the data manually.
But if you’re utilizing employees to perform manual reviews, how is that effective or scalable? If your data volume increases, you’re likely to end up with a processing mess on your hands.
AI + People: The best of both worlds
Too often, it seems like the goal of new technology is to eliminate the human element. When you’re limited team-wise or need employees focused on more important tasks, it makes sense to explore options that can shift your team’s focus off a task entirely.
But without human involvement, data doesn’t come out as clean or accurate. The combination of people and technology is vital for high-volume data processing accuracy. So why not use a more sophisticated approach that helps you elevate your capacity without putting the responsibility on your team—making the human element of the work scalable?
It’s time to use the best of both worlds to process data. That’s what we’ve done at ScaleHub. Watch this short video to explain how we combine AI and human ingenuity to leverage crowdsourcing for high-volume data processing tasks.