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Privacy Laws
Nov 22, 2021
Min Read

Confidential Information is Risky—So Automatically Redact It

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Sina Youn
Privacy Tech Lead

Sensitive or confidential information is a natural byproduct of doing business for many companies. From internal and external communication via email, chat, and other channels to various databases, document repositories, and legacy systems—the sheer volume of data, especially within documents, is overwhelming. Managing this information effectively becomes a significant challenge, particularly when ensuring that private, confidential, or otherwise sensitive information within these documents is secured against unauthorized access or accidental disclosure.

An unfortunate consequence of this information overload is that private, confidential, or otherwise sensitive information can be left unsecured or accidentally disclosed. With the number of data breaches this year already surpassing last year’s total, data privacy and security has never been a more pressing issue. However, it isn’t just data breaches that pose a threat. According to a survey conducted by Consilio, 64% of legal technology professionals feel that inadvertent disclosure of sensitive data is the biggest data security risk companies face today.

Data privacy laws are on the rise globally

Regulations aimed at data privacy have become more commonplace and increasingly strict due to mounting concern around how information is gathered, stored, used, and shared at scale. The General Data Protection Regulation (GDPR), an EU legal framework that went into effect in 2018, is widely considered the toughest data privacy law in the world. Although the U.S. has not yet adopted such stringent regulation at the federal level, things are shifting.

The California Consumer Privacy Act (CCPA), a state-level regulation that went into effect in July of 2020, was modeled after GDPR and has set a precedent for data privacy regulations in America. This trend is global, with Gartner estimating that “by 2022, half of the planet’s population will have its personal information covered under local privacy regulations in line with the General Data Protection Regulation (GDPR), up from one-tenth today.”

Not only is proactively safeguarding data the best way to avoid becoming the subject of an unwanted headline, it’s increasingly mandatory for compliance with global data privacy laws. For companies dealing with large, complex sets of documents, identifying where sensitive information is stored can be a daunting task. Fortunately, artificial intelligence (AI) has made it possible to efficiently locate and automatically redact sensitive information from documents. This focus on automating document redaction is crucial for maintaining compliance and protecting data privacy in an increasingly regulated world.

What is automated document redaction?

What is automated redaction? Automated redaction refers to the process of concealing information in documents by masking, deleting, or using other methods to hide sensitive details. This practice is essential for protecting personal identifiable information (PII) like social security numbers, addresses, and financial information within textual documents. With the advent of AI, Intelligent Document Processing (IDP) has significantly enhanced the efficiency and reliability of this process.

Super.AI's IDP tools utilize artificial intelligence to meticulously identify and redact sensitive information from documents. This AI-driven approach ensures a high level of accuracy and speed, allowing for the automation of redaction tasks at scale. Whether dealing with a handful of documents or thousands, users can easily upload their files, specify the information that needs to be redacted, and rely on Super.AI's IDP solutions to securely and efficiently anonymize their documents, safeguarding the privacy of individuals and complying with data protection regulations.

Automated redaction minimizes risk in most applications

Unstructured data is an increasingly important component of information management. According to research from AIIM International, 26% of information management professionals feel that integrating new data types into governance programs is the biggest information management challenge for their organization. As unstructured data grows to become the largest data type businesses store, the risk of unintentionally disclosing confidential or sensitive information increases.

Automated redaction makes it possible to ensure sensitive information remains protected as the types and quantity of company data grow. It also minimizes human error in governance programs by allowing artificial intelligence to automatically redact sensitive information across any data type by default. This allows enterprises across most industries to more efficiently and effectively mitigate compliance risks. Automated redaction has wide (and likely unforeseen) applicability, with some specific examples including:

  • Preparing data for computer vision training and serial production.
  • Researchers collaborating across organizations while automatically preserving data privacy.
  • Insurance companies running analytics on customer data while remaining GDPR compliant.

Check out these additional automated redaction and AI resources:

If you think automated redaction sounds like it might benefit your business, or you simply want to learn more about the technology, check out the following resources:

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