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May 16, 2022
Min Read

The Role of AI-powered Redaction in Global Privacy Law Compliance

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super.AI
Chief AI for Everyone Officer
SUMMARY

There is a patchwork of global privacy laws that businesses must contend with. These laws vary in terms of their scope and applicability, but all have the potential to impact companies across a wide variety of industries. In general, these laws seek to protect the personal data of individuals from being collected, used, or disclosed without their consent.

General Data Protection Regulation (GDPR)

One of the most well-known privacy laws is the General Data Protection Regulation (GDPR), which is a set of regulations that member states of the European Union (EU) must implement in order to protect the privacy of digital data. The GDPR replaces the 1995 Data Protection Directive, and went into effect on May 25, 2018. The regulation applies to any company or entity that processes the personal data of individuals within the EU, regardless of whether the business is based inside or outside of the region. The GDPR imposes strict requirements on businesses in terms of how they collect, use, and disclose personal data, and compliance failure can result in significant fines.

The GDPR requires businesses to take steps to protect the personal data of EU citizens, and it gives individuals:

  • The right to know what personal data is being collected about them
  • The right to have that data erased
  • The right to object to having their data used

Failure to comply with GDPR can result in severe penalties, including fines of up to 4% of a company’s global annual revenue or €20 million (whichever is greater), and imprisonment of up to two years. Between 2020 and 2021, GDPR fines increased sevenfold to an annual total of $1.25B (vs. $180M in 2020). The GDPR also gives individuals the right to file a complaint with the supervisory authority if they believe their rights have been violated. GDPR makes it clear that the entity responsible for determining the purposes and means of processing personal data is also responsible for personal data handling compliance. The principles relating to personal data processing compliance include:

  • Lawfulness, fairness and transparency: Personal data must be processed lawfully, fairly and in a transparent manner in relation to the data subject.
  • Purpose limitation: Personal data must be collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes.
    Data minimization: Personal data collection should be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed.
  • Accuracy: Personal data must be accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that personal data that are inaccurate, having regard to the purposes for which they are processed, are erased or rectified without delay.
    Storage limitation: Personal data must be kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processed.
  • Integrity and confidentiality: Personal data must be processed in a manner that ensures appropriate security of the personal data, including protection against unauthorized or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organizational measures.

The European Union's GDPR is considered the world's most comprehensive and strict data protection regulation. It includes the concept of 'adequacy,' which allows the European Commission to decide whether or not a country outside the EU provides an adequate level of data protection. This means that personal data can flow from the EU to a country outside the region with no additional protections if the external country offers an adequate level of data protection. As a result, GDPR is used as the basis for phrasing privacy regulations around the world.

It’s worth noting that none of this applies to anonymous data, which makes removing or modifying personal information one of the quickest and most effective forms of GDPR compliance in many scenarios.

California Consumer Privacy Act (CCPA)

Other global privacy laws include the California Consumer Privacy Act (CCPA), which was enacted in the United States in 2018, and the Personal Information Protection and Electronic Documents Act (PIPEDA), which was enacted in Canada in 2000. These laws have similar requirements to the GDPR, although there are some important differences. For example, the CCPA applies to businesses that process the personal data of California residents, regardless of whether the business is based inside or outside of the United States.

Privacy regulations in Asia

In China, the Personal Information Protection Law (PIPL) regulates the collection, use, and disclosure of personal data. The law requires companies to get consent from individuals before collecting their data and gives individuals the right to know what data is being collected and how it will be used. In Japan, The Act on the Protection of Personal Information (APPI) establishes rules for the handling of personal data and provides for the appointment of a data protection commissioner to oversee compliance with the law.

In South Korea, the Personal Information Protection Act (PIPA) protects individuals' personal data by regulating its collection, use, and disclosure. The act also gives individuals the right to access their data and correct any inaccurate or incomplete information. These are just a few examples of data privacy laws in Asia that are designed to protect consumers' data, there are many more in the region and elsewhere around the globe.

Redaction is key to privacy law compliance

Global privacy laws typically apply to businesses that collect, use, or disclose the personal data of individuals. In some cases, these laws may also apply to businesses that process the personal data of individuals on behalf of other businesses. A common component of privacy law compliance is data redaction, which is the process of removing or obscuring personal data from a document or dataset. For example, if a business is required to disclose data that contains the personal data of individuals, it may need to redact certain information in order to comply with the law.

There are a few different ways to redact data. One option is to physically remove the information from the document or dataset. This can be done manually or by using a software application that streamlines and automates part or all of the redaction process. AI and automation are playing an increasingly important role in data redaction.

Automated redaction tools can help to identify and remove sensitive information from documents quickly and efficiently. AI can also be used to train models that can flag potentially sensitive information for manual review. In addition, a number of different approaches can be used to actually redact the data, including blacking out text, blurring images. Each approach has its own advantages and disadvantages, so it is important to choose the right approach for the project at hand. Ultimately, AI and automation are transforming the data redaction process, making it more efficient and effective.

Data redaction examples by industry

Data redaction is typically used to protect the personal data of individuals from being collected, used, or disclosed without their consent. However, it can also be used for other purposes, such as to protect trade secrets or other confidential information.There are a variety of industries that may need to redact data, including healthcare, finance, and education. Here are a few examples of specific data redaction needs in these industries:

  • Healthcare: In the healthcare industry, it is often necessary to redact patient information from medical records. This is done to protect the privacy of patients and to comply with laws that regulate the disclosure of medical information.
  • Finance: In the finance industry, businesses may need to redact customer information from financial documents. This is done to protect the confidentiality of customer data and to comply with laws that regulate the disclosure of financial information.
  • Education: In the education industry, schools may need to redact student information from transcripts and other documents. This is done to protect the privacy of students and to comply with laws that regulate how education records are disclosed.

Common data redaction obstacles and how to overcome them

There are a few challenges that can be associated with data redaction. A primary one is ensuring that all of the personal data is removed from a document collection or dataset. If even one piece of information is left behind, it could potentially jeopardize the privacy of the individual and put the company at risk of violating privacy protection regulations. This makes accuracy paramount to any data redaction technique.

Another challenge is ensuring that the redacted information cannot be easily reconstructed. For example, if a business redacted the names of individuals from a dataset, but the dataset also included their ages and addresses, it would be relatively easy to identify the individuals. In fact, researchers from two European institutions have presented a technique they claim may correctly re-identify 99.98 percent of people in anonymized data samples with just 15 demographic variables. As governments and consumers alike increasingly realize the limitations of existing data protection methods, there will be a surging demand for fast, affordable, and effective redaction solutions.

Here are a few tips for overcoming these challenges:

  • Use multiple layers of security: Using multiple layers of security can help to ensure strict access controls are enforced (e.g. multi-factor authentication).
  • Use trusted data redaction software: Using data redaction software can help to automate the process and ensure that all of the personal data is removed. Make sure to choose a software application that is from a trusted source and that has been designed specifically for data redaction.
  • Work with a professional: If you are unsure of how to properly redact data, you can always work with a professional. Data redaction is a complex process, and working with someone who is experienced can help to ensure that it is done correctly.

Follow these tips to overcome the challenges associated with data redaction and protect the personal data of individuals.

An accurate, automated redaction solution that scales

AI-automated data redaction software is a new solution that is being used for data privacy compliance and protection. This type of software uses AI to automatically redact sensitive information from documents, images, video, and other unstructured data. It is an effective solution because it can accurately identify and remove sensitive information at scale, while still preserving the integrity of the source data. In addition, AI-automated data redaction software is much faster and more efficient than manual redaction. As a result, it is a valuable tool for companies that need to comply with data privacy regulations.

Additional AI-automated redaction resources

Global privacy laws are complex and vary from country to country. However, businesses need to be aware of these laws and comply with them whenever possible. Data redaction is a critical part of compliance for many industries, and can be challenging to execute correctly. New AI-automated technology has made data redaction much easier, so make sure your business is using the latest tools to keep customer data safe and in compliance with the global privacy regulations.

For more information about how AI-automated data redaction can help your business, check out some of our other resources on the topic:

Disclaimer: This article is for informational purposes only and does not constitute legal advice. If you have any questions about data redaction or the GDPR, you should consult with a qualified attorney.

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