AI Operations: Human-Enriched Machine Learning
Strategic Insights
AI Operations: Human-Enriched Machine Learning
Akash Pugalia · 11.30.2021

Artificial Intelligence (AI) has come a long way since the late 1950s, when Katherine G. Johnson – “the computer” – manually validated the calculations made by the newly installed IBM computer made for the Apollo 11 flight to the Moon. Today, one can say AI capabilities have reached new heights, changing our lives in unimaginable ways.


Consider, for a moment, the sheer number of people using digital platforms each day from around the world. Imagine all the images, videos, messages, posts, and other content types flowing across numerous digital channels, generating more than 2.5 quintillion bytes of data. No surprise, it has become challenging for companies to manually process, analyze, and monitor user-generated content from around the world and in real-time across their digital platforms. Ensuring accurate content tagging and labeling while also flagging inaccurate or harmful content has become a business imperative for any company with an online presence.


As the conversation around AI, automation, big data, and Machine Learning (ML) models continues to gain momentum, business leaders must ask what they can do to address the growing need for online data management? And, most importantly, consider what it would take to bring them professional piece of mind?


Due to the urgent nature of online data management and content moderation services, there are many benefits to partnering with organizations that can offer extensive service experience, operational expertise, and the latest in advancements in Artificial Intelligence (AI) and machine learning technologies. Teleperformance has been strategically combining technology and human understanding for more than 40 years. Many organizations have already turned to Teleperformance for our Content Tagging, Labeling, and Moderation Services that combine efficient ML algorithms with human oversight and validation.

 

Our content moderation and big data labeling operations continuously optimize ML models to achieve human-level intelligence, allowing the automated recognition and removal of any content that’s explicit, abusive, fraudulent, or harmful. We also accurately tag and label content to ensure accuracy in search results and content categorization. For example, when someone searches for cats online, they don’t want to receive pictures of dogs. So, the image tagging must be correct. Or, on your own website, it’s important to ensure that customer searches deliver the most relevant content, or risk them abandoning your site for a competitor’s.


At Teleperformance, we have more than 8,000 content experts to help improve the accuracy of automatic takedowns by continuously validating datasets and helping ML models gradually increase accuracy to over 95%. Improvements in Natural Language Processing, sentiment analysis, object detection, scene understanding, and eliminating bias are some of the areas where human validation can be critical.


On one hand, our content experts review and tag millions of items each week, including text, videos, pictures, ads, among others. This manual validation is fundamental to keep ML models up-to-date while meeting the local rules and requirements.


On the other hand, AI Operations automate simple tasks like data labeling and annotation by recognizing and adding meaningful and informative labels to large volumes of raw data.


In today’s digital era, companies cannot afford to sacrifice accuracy for the sake of speed. Therefore, the only way to achieve both is to keep humans in-the-loop to make the correct decisions and allow AI algorithms to detect and block the most offensive content before it harms a brand’s reputation or its customers. That is why hiring a diverse, gender-balanced workforce helps mitigate biases in AI models and cultural understanding.


Partnering with Teleperformance will result in an integrated digital business solution, managed with human operational rigor, and personalized according to the companies’ global and local needs.

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