How AI Automation Can Help Non-Profit Organizations Deal With Highly Sensitive Data

How AI Automation Can Help Non-Profit Organizations Deal With Highly Sensitive Data

Sorcha Sheridan

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Many people worry about the repercussions that automation might have on the workforce. The common misconception is that it will cause a sharp decline in available jobs. The truth is, AI automation should be viewed as a great companion for businesses and organizations rather than an enemy.

Organizations, especially those that are not-for-profit, store sensitive data that should be handled with the highest degree of protection. This includes protected information related to human rights, child protective agencies, and animal welfare.

By taking out some of the human interaction involved with transferring highly sensitive data, organizations can avoid it being inadvertently sent to the wrong individual(s) and reduce the number of people that view these documents to only the strictly necessary.

Integrating automation within processes that involve highly sensitive data can lift a very big weight off the organizations involved. Especially considering the important causes most non-profits and their workers have as their missions – and the limited time and resources they often have to work with – easing their workload could mean making an even bigger impact on the causes they are trying to help.

Do you want to know more? Let’s dig in!

What is highly sensitive data?

Highly Sensitive Data (HSD) is a very broad category, but for purposes of this article it is best defined as, “data that require restrictions on access under the law or that may be protected from release in accordance with applicable law or regulation.”

To simplify this concept, HSD is usually data that, if intercepted by criminals, can be used to commit identity theft. This includes any number sequences that are related to your banking account(s) and debit/credit cards.

Of course, HSD includes your passwords and any healthcare information protected under United States’ HIPAA (Health Insurance Portability and Accountability Act) as well.

Files including sensitive data
Highly sensitive data - Source : GDPR Informer

What is required from the incoming data?

Data security systems are working behind the scenes far before sensitive information is directed to the appropriate individual(s) or department(s).

For example, many NGOs (non-governmental organizations) typically have systems that allow people to submit information anonymously. This is usually done through a general email address, app, or messaging service. When a person sends in information, it will include specific names, addresses, and/or locations.

If any of this information were to be leaked, serious consequences would likely arise. Fortunately, there are AI (artificial intelligence) and NLP (natural language processing) systems that direct information to a specific office or a group of individuals with relevant data clearance levels, without the need for human interaction.

Why it is important to handle sensitive data correctly

Organizations are required by law to handle sensitive data in an appropriate manner.

Failure to comply with regulations poses a serious risk to the future of a company or organization.

When a data leak occurs, it can permanently scar an organization’s reputation – not to mention the implied violation of privacy towards the people whose data would have been leaked. Furthermore, the organization may face legal consequences related to any damages that occur as a result of the leak.

Penalties will depend on the type of breach (e.g., HIPPA for U.S.-based healthcare violations). Some events can even cause an organization to have to shut down indefinitely.

How automation can help you handle incoming sensitive data

The daily operations of non-profit organizations involve large volumes of paperwork and multi-level approvals. This results in workers spending too many hours on paperwork, long case-processing times, and many eyes accessing sensitive data.

In many cases, artificial intelligence will automate workflows and reduce unnecessary tasks for individuals within an organization. However, some cases may require a degree of human oversight.

Levity Workflow automating an email process
Levity Workflow automating an email process

In both circumstances, automation helps save time and money while also reducing the risk of protected data leaks as well as protecting people’s privacy and data security. By saving time automating these processes, the professionals at NPOs can spend their time on valuable tasks, ensuring to make as much of a difference as possible within their respective causes.

It’s important to keep in mind that non-profit workflow automations are certain to make people’s jobs easier. Still, implementing them does not mean that jobs will be replaced entirely by machines. It simply means that job roles may need to be redefined. Instead of focusing on never-ending piles of paperwork, people can provide more value through groundwork.

Essentially, non-profit workflow automations are a way to bypass the “gatekeeper(s)” and get information directly to the appropriate party. For example, say the non-profit organization you work for uses a general email address that anyone can submit anonymous tips to. Once a tip is submitted, it is sent to a receptionist who reviews its contents and directs it to the correct department. From there, the tip might reach 3-4 more pairs of eyes before getting to the appropriate person.

Wouldn’t it be easier to use something like Natural Language Processing to automatically direct the anonymous tip to the appropriate party? Not only is this approach better for protecting data, but it also saves a ton of time and effort.

Below are some examples of how some of these non-profit organizations have used automation to streamline their processes involving sensitive data:

Automate text-messaging donation systems

When Haiti experienced a major earthquake back in 2010, non-profits worked vigorously to collect as many donations as possible.

The Red Cross managed to raise a whopping $41 million through a text message campaign. Each donor sent in just $10 with the message “Haiti.”

Red Cross working in Haiti
Red Cross working in Haiti - Source: Red Cross

There are several automations that can be used for a text-messaging donation system.  The Red Cross used the following to generate donations:

  • Allowing donations to be made to a specific phone number
  • Text-to-voice donations that allowed users to call in with a credit card payment
  • A system that sent out several text messages each month to reinforce information
  • Donations via their mobile website
  • Sales from apps that included:
  • Sales at $1.99 per app
  • In-app sales
  • Sponsored apps.

Automated accounting and data audits

Non-profit workflow automations allow fund accounting to be done with ease. Fund accounting is a system that non-profit agencies use to keep track of their cash and manage how it needs to be designated.

By using an automated workflow, non-profits can dive deeper into purchasing requisitions via their mobile device in real-time. Financial data, like fund accounting, is sensitive, protected data.

Auditing can also benefit from workflow automations. It’s much like having an additional department within your office space. The primary difference is that automation can offer real-time data via a single dashboard. Instead of multiple departments scrambling to gather documents and reports, data is readily available, quickly and efficiently.

Automated message categorization - Text analysis

Text analysis is a branch of AI that can be very helpful for non-profit organizations handling highly-sensitive data.

Many incoming emails need to be forwarded to various departments. AI software allows this step to be automated, which can be especially helpful for automatically getting information to appropriate departments.

By classifying emails based on their content and sending them directly to who these emails are relevant; or extracting certain data from an email and filling in a form, the number of hands this sensitive data needs to pass through could get dramatically reduced.

Levity Flow - Email Categorization
Levity Flow - Email Categorization

Levity is an AI workflow automation platform that helps eliminate the need for human intervention by reducing unnecessary tasks.

Levity can also help these organizations reroute their emails to the right people. By tagging messages based on their content, organizations increase their data security by ensuring they’re getting sent directly to the right department and/or being flagged appropriately (confidential, urgent, personal, etc.).

Levity’s AI software can analyze text messages through text analysis. Non-profits reap a benefit here by using NLP to understand messages sent into an organization. It’s particularly helpful because NLP flags urgent messages that require immediate attention.

Data extraction

Very often, non-profit organizations need to fill out many forms until a case can be processed correctly. Through automating these processes, not only could their efficiency be dramatically increased, but the people involved would be assured an extra level of data privacy.

Levity can help organizations with these processes through data extraction.

This would include extracting highly sensitive data from an email and automatically filling in a form, reducing the number of steps needed to complete this task. Data extraction takes out extra paperwork and reduces unnecessary tasks while also limiting the number of eyes that have access to confidential information.

The benefits of AI automation with highly sensitive data

Many non-profit organizations can safely rely on AI automation to protect their data through machine learning and pre-set rules.

AI email technologies are a big player in security automation because they minimize human error in businesses and organizations. In addition, these technologies are vital for raising awareness and preventing data breaches.

Instead of relying on individuals to protect sensitive information, AI tools essentially provide their very own data protection shield that requires minimal human intervention. After all, employees shouldn’t have to bear the weight of managing an organization’s entire security protocol.

Reducing unnecessary tasks & prioritizing important tasks

Non-government organizations are typically limited on their resources, which leads them to be constantly looking for new ways to save time and money.

Because highly sensitive data must be handled with care, it’s no surprise that it takes a lot of time to get incoming queries read, sorted, and directed to the appropriate party. This process often proves to be tedious work for team members.

So, what if information could be automatically sorted and redirected? With AI machine learning capabilities, it certainly can, in a matter of seconds.

One great example lies within the healthcare industry. NLP systems can automatically tag categories like “lab results” and “anonymous violation reports”, which allows issues to be solved faster than ever before.

This way, by reducing the amount of time spent going through documents and files, the professionals involved can instead invest their time in helping the people their organization is working with.

Ethical aspects to take into account

The process of handling sensitive data is held to a much higher standard than general information, with very few exceptions. Said exceptions include information that is readily available to the general public, such as a recorded deed to a home or personal property taxes. Some might argue that this data is “sensitive”, but it is actually made available both online and at local county offices.

Basically, any information that the government or regulatory agencies view as being sensitive is required to be handled discreetly and confidentially.

Concerns regarding the use of AI with highly sensitive data

Although machine learning algorithms can offer many benefits such as reducing repetitive tasks, concerns arise when it comes to sensitive information related to minor children.

Possible issues that should be considered include:

  • Database readiness – machine learning algorithms require a large amount of data to be collected from multiple departments within an organization. Inputs must be error-free and any corrections have to be made prior to implementation.
  • Identifying bias – if an algorithm picks up on any existing bias within an organization, it will continue to use that bias and intensify it.
  • Shared knowledge – both data scientists and child protection experts must be on the same page as to what information can and cannot be shared. Without integration, a great risk is posed to the protected data of minors and other individuals.
Importing data onto Levity to train an AI Block
Importing data onto Levity to train an AI Block

Most ethical concerns arise with more in-depth tasks, such as case assessments. However, it is important to make sure that your organization is ready to implement AI within its processes before taking this step. Otherwise, complications could arise even before sensitive issues like case assessments.

Automation of tasks, not final decision making

It’s important to note that AI technologies are only one part of an organization’s process. They are put in place to aid an organization and assist with reducing repetitive tasks.

In the case of child protection workers, AI systems are merely an aid and do not tell them what they need to do. These systems are in place to protect the privacy of the children involved to reduce any potential risks when processing their cases.

Very often, if this sensitive data was leaked, it would reveal information such as their identity or location, which could put children or victims of abuse in grave danger.

Automation can be a game-changer for non-profits

Whether your organization is trying to ease its workload or simply reduce unnecessary tasks, AI-powered automation may be the answer. Many times, it’s a simple integration that can change everything from how an organization operates to its efficiency.

More importantly, AI is a game-changer when it comes to protecting sensitive information. It means fewer eyes on potentially distressing data, thus less human interaction and fewer potential leaks. It also reduces the number of errors within workflows.

For this reason, no-code AI tools are an extremely useful asset for non-profit organizations, which typically operate on limited means and don’t have a team of developers who could implement and maintain a custom-made system.

Now that you're here

Levity is a tool that allows you to train AI models on images, documents, and text data. You can rebuild manual workflows and connect everything to your existing systems without writing a single line of code.

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