Tasware is now live 🎉
Skip to content
Get in Touch

Why Today's Best AI Solutions Have Humans in the Loop

One of the biggest misconceptions in the field of artificial intelligence (AI) is that machines can do all the work themselves. The exact opposite is true. Yes, AI and machine learning have advanced...

 Toggel Table of Contents

One of the biggest misconceptions in the field of artificial intelligence (AI) is that machines can do all the work themselves. The exact opposite is true. Yes, AI and machine learning have advanced capabilities to automate processes and tasks that would take humans tens and hundreds of hours to accomplish. But human intervention is necessary to guide the process. 

In fact, most machine learning and artificial intelligence solutions rely on data prepared by humans. But the best solutions allow humans and AI solutions to interact to power ongoing learning. This model is called Human in the loop (HITL) and provides an incredibly effective way to create the best AI algorithms for your every business need. 

Why Human Insight is Necessary for Effective AI Solutions

The way AI and machine learning work is by using a model to train technology. The more training data there the better the technology performs. Companies don't have the time and resources to build an exhaustive dataset so the obvious solution is to have a human intervene and guide the model on a regular basis. 

What happens when humans and machines work together to improve AI models? This approach creates a continuous feedback loop that creates better algorithms that can solve problems more accurately and quickly. There are two ways that companies can integrate HITL into their AI processes — supervised and unsupervised learning. Each one has its unique advantages. 

  • Supervised learning. This occurs when experts use labeled data sets to oversee machine learning. This is the hands-on version of HITL and is more resource-intensive but well worth it for complex projects. 
  • Unsupervised learning. With this approach, machines use unlabeled data sets to learn on their own to find the structure. It takes fewer resources as the expert needs to create the structure initially and then let the AI run and learn on its own. 

Without a helping hand, machines can't create an algorithm that is sophisticated enough to produce accurate results on a consistent basis. So you need an expert to intervene and tweak the model from time to time. 

How a Human in the Loop Approach Benefits Companies AI Initiatives

There are many benefits to a HITL approach. It dramatically decreases inaccuracies in the algorithm and helps improve the user experience. What's more, a HITL approach is relevant across many AI scenarios. 

  • Digital customer service. You could have human customer service agents train AI models to help chatbots deliver more effective responses to customers. Over time, chatbots can develop a sophisticated model of responses based on specific keywords that the customer uses and can better respond to customers' needs. 
  • Content moderation. You could also outsource content control and help improve moderation and fraud prevention for content teams. This is especially useful for sites that have a lot of user-generated content and need to uphold quality standards and community rules. 
  • AI training. Another option is to use HITL in traditional AI applications such as video annotation, image processing, data tagging, and natural language processing (NLP). These are very common tasks that get complex as the size of the organization grows and the complexity of the data increases. 
  • Back office operations. Another great use for HITL is in back-office operations such as order processing, quality assurance (QA), data entry, and account setup. These are simple tasks that can be automated with AI but may still need human input to keep the accuracy high and adjust results to industry-specific criteria. 

Making the Most of AI with a Human-in-The-Loop Approach

It's highly unlikely that you'll consistently gain the results you need if you leave your AI algorithms to run on their own. Train your models with human intervention and tagged data sets to improve accuracy and the customer experience

To get the most out of the human-in-the-loop approach, you should use a service provider that specializes in this form of machine learning and has experts in your industry. Here at Helpware, we can provide a team of experts that can help you take advantage of HITL and improve your AI. Get started today! 

Related Posts

How Machine Learning Can Help Elevate Your Customer Service

Artificial intelligence (AI) used to be the stuff of science fiction, as writers and filmmakers alike tried to imagine how such advancements might change our world. Today, AI is ...

Automated Data Labeling vs Manual Data Labeling

Artificial intelligence (AI) continues to push the boundaries of our technological capabilities. One radically transformative AI field is computer vision, where computers and ...

How AI Image Recognition Is Transforming eCommerce Marketplaces

Image recognition is transforming the way online users shop for products. In the past, you had to physically go and look for products that you wanted to buy that looked similar to ...
Nick Mannella
Chief Revenue Officer

Helpware expertise

Core Services

Explore Helpware

Let’s chat about business process outsourcing for success

Let’s Get Started