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Explainable AI Tools: Four Industries Where It Will Be Critical

Published by Ani Mosinyan at June 30, 2022

The world is quickly moving into an artificial intelligence era. And while we are far from child robots and terminators, the world has been feeling the positive effects of AI applications. But, of course, some industries feel the impact of it most, and that’s a reassuring thing. 

Artificial intelligence revenue is predicted to hit $62 billion by the end of 2022. Accordingly, people in innovation and technology are trying to find out how to leverage AI applications more to improve people’s lives. Hence, the demand for explainable artificial intelligence has grown exponentially.

What is Explainable Artificial Intelligence?

IBM defines explainable artificial intelligence this way: 

“Explainable artificial intelligence (XAI) is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms.”

In other words, explainable AI, or XAI, is a way to get computers and programs to think and make decisions just as a human being would. The explainable AI principles that govern our technology today allow machines and software to process information and execute commands with little human intervention. For instance, an application in your email address can read messages and determine whether it’s spam or not. That is one of the many examples of explainable AI we benefit from today.

Industries Where Explainable AI is Crucial

While we are not yet at a point where we have 100% XAI driving our technology, we’re seeing some glimpses of it. Some industries see and benefit most from these developments, and artificial intelligence should start advancing in various industries more urgently. Let’s look at the four most crucial sectors where AI is gaining traction. 

Cybersecurity

Cybercrime has grown over the years and impacted many people’s lives. Individuals lose retirement funds and savings to phishing scams. Organizations lose crucial data and money to hacks. It’s estimated that it costs companies up to $2.9 million every minute worldwide. 

Malware and bots are now starting to overwhelm cybersecurity staff and managers. So the best way to respond to automated hacking systems is to create automated security systems. And that’s what explainable artificial intelligence in cybersecurity hopes to do. In addition, we need faster and more efficient ways to deal with cybersecurity threats as time passes. 

Hence, artificial intelligence trends in security have been growing and should continue to grow over the years. Accordingly, businesses and individuals should start depending on explainable AI deep learning applications such as malware and ad blockers, user authentication, Touch ID, and Face ID capabilities to combat malicious scammers. If malware is detected, you can use XAI to verify how the AI came to that determination.

Marketing

Marketing has seen a massive increase in AI capabilities, and that’s doing more good than most people think. Small businesses have and will continue to benefit the most from XAI in marketing. Amidst the COVID-19 pandemic, many solopreneurs and mom-and-pop businesses felt the grueling effects of lockdowns and health protocols. It taught us that we must take better care of our small-to-medium businesses (SMBs). 

AI in small businesses empowers the small player. Gaining access to customer relationship management (CRM) software, chatbots, and email marketing tools will help these businesses ramp up their marketing and improve their sales and performance. Some CRM platform features and examples that benefit small-to-medium enterprises (SMEs) include lead generation, customer management, and task management tools. In addition, XAI eliminates the unconscious bias in AI data sets. For example, Amazon’s failed attempt to use AI for job application vetting resulted in prioritizing hiring white males due to AI’s look at hiring trends.

Healthcare

Healthcare is also starting to get a big boost from artificial intelligence. When the human workforce has been overwhelmed with healthcare needs, automation and explainable artificial intelligence alleviate the load. Paul Appleby, the CEO of Kinetica, once said that “a machine using explainable AI could save the medical staff a great deal of time, allowing them to focus on the interpretive work of medicine instead of on a repetitive task.”

Explainable artificial intelligence can also help lower human errors that could lead to severe injury or medical conditions. With the advancement of explainable AI projects in healthcare, we will be able to cure more patients, as well as develop vaccines and medications faster.

Finance Technology

Artificial intelligence has also greatly improved the finance sector, banking, e-commerce, insurance, and mortgage brokering. “There are several potential use cases for AI in insurance, such as customer acquisition, agent productivity, claims prevention, underwriting, customer service, cross-selling, policy adjustment, and improving risk and compliance,” shares Matt Sanchez, founder and CTO of CognitiveScale.

Empowering financial experts and consultants with better tech can now educate and serve more people who want to get into better financial standing. And with better fiscal and monetary systems through explainable AI, people can be more prepared for the financial troubles that may weather down on them.

Explainable Artificial Intelligence Advancing

We’re only starting to see the positive effects of XAI across various industries. And as the technology continues to improve, the only logical thing to do is jump on the trend and start maximizing the capabilities and conveniences that these innovations now afford us.


Ani Mosinyan

Ani Mosinyan

Content ManagerAni Mosinyan is the Content Manager for PLAT.ai. She has worked for publications such as Rare Bird Books and The Hollywood Reporter. She has a background in English literature and film studies, as well as creative writing and experience in literary publishing. In her free time, she enjoys hiking, writing poetry, and watching old films.