Many decisions in our lives require a good forecast, and Artificial Intelligence (AI) and Machine Learning (ML) are almost always better at forecasting than their human counterparts. Yet, for all these technological advances, we still seem to lack confidence in AI predictions. Recent cases show that people don’t like relying on AI and prefer to trust human experts, even if they are wrong.
Why don’t we have the best out of both Worlds?
Understandably, people are apprehensive and reluctant to trust the machine; how can we verify that the machine is not making mistakes, doing its tedious job?

In the following paragraphs, we are going to explain this step-by-step.

Augmented Artificial Intelligence (A2I)

Easily implement a human review of machine learning predictions.

Some machine learning applications need human oversight to ensure accuracy with sensitive data, provide continuous improvements, and retrain models with updated predictions. However, in these situations, you’re often forced to choose between a machine learning only or a human only system. Companies are looking for the best of both worlds — integrating machine learning systems into your workflow while keeping a human eye on the results to guarantee a needed precision.

Use Cases

Healthcare Sector

Medical insurance claims, intake forms, prescriptions and many other healthcare documents have valuable information locked inside, which needs to be extracted quickly and precisely. You can now use A2I and Textract to process documents, extract the data and have a human review the critical data. This saves time and money with document processing and allows for a human to review any nuanced or sensitive data or audit predictions on an ongoing basis.

Banking and Financial Services

Loan or mortgage applications, tax forms, and many other financial documents contain millions of data points that need to be processed and extracted quickly and effectively. Using Textract and Amazon A2I, you can extract critical data from these forms, whether structured or unstructured and have a human review the output. DealNet Capital uses Textract and Amazon A2I to process their financial records, which have reduced the amount of time spent manually reviewing documents by up to 80%.

Advantages and Benefits

Quickly implement a human review of ML predictions.

A2I gives you the flexibility to incorporate human review into ML applications based on your specific requirements. Low-confidence predictions are sent to humans to review and take action. If needed, you can also require multiple reviewers to check a forecast to achieve consensus. Additionally, to audit models, you can randomly sample predictions for human review so that you can regularly evaluate if the model is still performing well. A2I helps people and machines do what they do best.

Integrate human oversight with any application

A2I provides you with an easy way to integrate human oversight into your machine learning workflows, with no machine learning experience required. No need to go with an all-human review system vs machine learning only. A2I brings together machine learning and humans to provide you with automation while keeping a human eye on the results to offer needed precision. Amazon A2I makes it easy to integrate human judgement and AI into any ML application, regardless of whether it’s run on AWS or another platform.

Get to market quicker.

Deciding between machine learning vs humans doing manual processes can choose to market today vs months from now. Integrating Amazon A2I into your workflow not only aids in getting to market with your machine learning quicker, and you can also update and retrain your models over time. As your business needs change, so can your workflows, and Amazon A2I can help provide you continuously improve your models at whatever stage you are in your machine learning journey.

AI Verification & Augmentation Lead: Transforming the Landscape of Artificial Intelligence

Examples of how others adapted this method successfully

T-Mobile US, Inc. is redefining how consumers and businesses buy wireless services through leading product and service innovation. Their advanced nationwide network delivers wireless experiences to 84.2 million customers who are unwilling to compromise quality and value.

“Providing relevant information, such as account details and available discounts, in real time to our customer care agents while they are in live conversations with customers is one of the ways T-Mobile uses machine learning to improve customer experience. Using A2I, we will be able to ensure that our models continuously deliver top-quality insights by having humans validate random samples of model predictions. Trust is the hardest thing to build when it comes to machine learning, and A2I will allow us to make sure that our models are making the fewest mistakes.”

— Heather Nolis, Machine Learning Engineer, T-Mobile

Change Healthcare is a leading independent healthcare technology company that provides data and analytics-driven solutions to improve clinical, financial and patient engagement outcomes in the U.S. healthcare system.

“At Change Healthcare, we help accelerate healthcare’s transformation by innovating to remove inefficiencies, reduce costs and improve outcomes. We have a robust set of integrated artificial intelligence engines that bring new insights, impact, and innovation to the industry. Critical to our results is enabling human-in-the-loop to understand our data and automate workflows. Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions. With A2I becoming HIPAA eligible, we are able to involve the human in the workflow and decision-making process, helping to increase efficiency with the millions of documents we process to create even more value for patients, payers, and providers.”

— Luyuan Fang, Chief AI Officer, Change Healthcare

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Intelligent Cognitive Search – Working AI Product that leverages AI and NLP to read and understand the most complex legal, financial, and medical documents to discover insightful information. The end user asks questions to find answers – like ChatGPT only for your internal data organisation.

Document Comparison (Data Review) – Working AI Product. Enables legal professionals to review thousands of contracts and legal documents by comparing them against a master copy and by answering set lawyers’ questions. AI and NLP comprehend the questions, and answers are delivered in a single report. Our Document Comparing eliminates time-consuming tasks.

Please take a look at our Case Studies and other Posts to find out more:

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Intelligent Search and Artificial Intelligence: Transforming Legal Research and Empowering Lawyers