Google Maps Utilizes Machine Learning To Block Nearly 100 Million Fraudulent Edits

Google Maps Utilizes Machine Learning To Block Nearly 100 Million Fraudulent Edits

In their recent post on how Google keeps Maps information reliable, the company elaborates how they use machine learning and human operators to block nearly 100 million attempted fraudulent edits to Google Business Profiles. Machine learning, in simple terms, is a sort of artificial intelligence (AI) that lets software applications improve their accuracy at predicting events without having to be explicitly programmed to do so. Machine learning algorithms use past data as input to forecast new output values.

The world changed with the introduction of vaccinations, revisions to mask regulations, and new COVID variations in 2021. Accordingly, their Maps community updated Google Maps with further information about their nearby areas. Their contributions have helped Google provide updated company information, such as a location’s hours of operation or its health and safety regulations, for 30% more firms in 2021 than 2020.

However, sometimes fraudsters have used abusive modifications to alter business information on Google Business Profiles. In 2021, it took down around 7 million fake profiles. Six hundred thirty thousand of these removals were based on user reports. Moreover, Google reports that it also stopped 12 million attempts to impersonate a company and took down 8 million fraudulent attempts to claim a company’s profile. Additionally, Google shut down 1 million accounts concerning policy violations.

Machine learning also aided the Google Maps team remove about 200 million photographs and videos of low quality or violated rules. They could do so as continued advancements in machine learning models improved their ability to catch bot activity and unearth suspicious activity patterns.

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