AI everywhere: How AI is being applied in 4 different fields

June 30, 2021  |  Devin Morrissey

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This blog was written by an independent guest blogger.

Historically, the idea of artificial intelligence (AI) saturating our world has been met with suspicion. Indeed, it’s one of the more popular tropes of science fiction — learning machines gain sentience that helps them take over the planet. While we’re not even slightly close to that dystopian reality, we have reached a point at which AI has been significantly integrated into various aspects of our society.

While this isn’t without its risks, largely from a security standpoint, there are huge benefits. Indeed, some of those cybersecurity risks are even being mitigated by utilizing AI to predict and combat breaches. Machine learning, while still very much in its infancy, is proving to be an agile tool to increase efficiency and assist innovation. 

It’s always important, though, to have a good understanding of how we are using such tools and why. So, let’s review a handful of the industries that AI is already making a prominent presence in, and where it is likely to head soon. 

Shipping and logistics

One of the most prominent areas for AI use at the moment is in the shipping and logistics industry. The internet has given rise to e-commerce, resulting in more people ordering goods online and having them delivered. This requires processes that enable companies to provide goods efficiently and safely, and AI-supported logistics management software has stepped in to take the strain.

These software platforms, combined with sensors in the internet of things (IoT) — in this case, the ecosystem of connected technology throughout warehouse and shipping environments — gather information on all the processes that go into getting items into the hands of customers. This includes inventory replenishment, packing, fleet availability, the journey, even the condition of the delivery vehicles. This information is then analyzed by the AI software and logistics managers are provided with recommendations on the most efficient routes, safer practices for staff and drivers, and in some cases up-to-date alterations based on road conditions. UPS is one of the more prominent companies utilizing AI in this way, for both shipping and internal optimization.

Medicine

The way AI is currently being embraced by the medical fields is a prime example of how technology can be used to enhance our lives. One of the issues faced by the medical industry is that patients attending with symptoms can wait for significant periods to receive effective diagnosis and treatment — that is because it is not always clear to doctors with the limited information at their immediate disposal what might be the route cause of a medical problem and what the solution might be. Not to mention that misdiagnoses can occur due to human error. As a result, AI is seeing increasing usage in diagnostic medicine.

Machine learning software is fed large amounts of international shared data — including symptoms and radiographic imaging — and being taught how to distinguish between different types of diseases. Doctors can then use this software to more quickly and accurately classify illnesses and design treatment plans. Perhaps most interesting is that while one research program found that an AI system was able to diagnose some types of cancer with accuracy comparable to a physician, when professional expertise and AI were combined, the accuracy of diagnosis rose to 99.5%.

However, it’s just as important to recognize that systems that require a large amount of patient information to function also present points of vulnerability to cybercrime. This is particularly concerning as methods to breach systems are becoming increasingly sophisticated. As such, medicine is among the industries also exploring the potential to utilize AI and machine learning to combat such threats. As the industry adopts more connected tech in the IoT for patient monitoring and sharing medical records via the cloud, we are likely to see more use of security tools that analyze systems in real-time and provide alerts and automated security responses when threatening behavior is detected.

Education

Teaching, perhaps more than ever before, is an administration-heavy role. Education professionals aren’t simply able to spend their time passing valuable knowledge onto students — there’s lesson planning, budget considerations, grading papers, evaluations, and that’s barely the tip of the iceberg! As such, AI has become an important tool in helping to take some of the burdens of repetitive, analytical tasks.  

For the most part, this is integrated into the collection of educational technology (EdTech) trends that has become a familiar part of the classroom environment. Software can review more empirical papers — multiple-choice exams, fill-in-the-blanks exercises — and grade them swiftly and accurately. AI-driven data analytics also has a place in assessing students’ progress; tracking their grades, noting areas where individual students appear to be struggling, highlighting the learning styles that resonate with the class. This cuts down on the time teachers spend reviewing assessments, allowing them to devote more of their valuable energy to using the information provided by AI to assist students directly.      

Entrepreneurism

Our current globally connected digital landscape offers incredible opportunities for entrepreneurs. As such, there is a growing number of software options and tech tools that are geared toward supporting businesses, including some that are AI-driven.

One of the most rapidly developing business machine learning ecosystems is known as enterprise AI. This refers to the automated tools that utilize the algorithms produced through analyzing business operations to help leadership make more prudent and efficient decisions about the direction of the company. Some of these are used in a practical, real-time sense, such as intelligence-driven protocols that analyze production data and adjust operations automatically to improve efficacy. The trends in this area are also leaning toward increased adoption in marketing, chatbots, and even financial planning.

Conclusion

When we talk about AI now being everywhere, it’s important to understand that its role is generally one that is supportive of human talent rather than replacing it. Whether it’s helping improve efficiency in shipping or diagnostic accuracy in medicine, there is great potential for machine learning to integrate with our activities in positive, productive ways. Though more sectors are adopting it, we’re still only at the threshold of what AI has to offer us.

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