Srikanth
When we hear about artificial intelligence applications, we usually think of those that have become a part of our daily lives or has become embedded in mainstream consciousness, such as the personal assistant apps in our phones (i.e., Siri and Cortana) or Google’s self-driving cars.
We may also think about how they’re being used to control robots and manufacturing equipment in assembly lines. But what about the more unique and uncommon implementations of AI, the ones that we don’t hear that much about? Are there any at all? The answer to that is a resounding yes, and you may be surprised at just what some of them are. Here are some surprising ways that AI is applied that you may not know about.
Detecting and Preventing Money Laundering
Depending on just how closely you keep up with business and technology trends, you may have already heard about big businesses that are using artificial intelligence to help them grow their operations and improve their business processes. AI-powered analytical programs sift through the volumes of information stored in these companies’ global servers, predicting trends, drawing conclusions, and developing strategies based on patterns in the data.
Big banks and financial institutions are also doing the same thing with AI. However, besides having AI analyze their databanks for new ideas and insights, they’re also using a specific kind of artificial intelligence-powered solution to detect instances of money laundering: AML artificial intelligence solutions.
How is this done? The AI solution scours a bank’s customer information database and continuously sweeps it for suspicious signs or trends that could hint at an ongoing money laundering scheme. One common pattern of activity that the AI can be programmed to look for is an account that seems to be depositing a large amount of money into the bank and then taking the exact amount later on a regular basis. This is highly indicative of money laundering, one that the AI solution would immediately flag for the bank’s investigating team to look into.
A small bank may be able to do this without the help of AI solutions. But for huge banks with branches all over the world, with thousands if not millions of customers, then the task becomes much more difficult. AI solutions can manage such a job in a more efficient, effective manner.
Creating Hit Contemporary Music
Song-writing is one of those jobs that has long been perceived to need the human touch. Lately, however, AI has played a key part in the creation of contemporary hit music. That’s just what happened when London-based music producer and artist Alexander Grant (aka Alex Da Kid) came out with his debut single ‘Not Easy’, a track that reached Number 4 on iTunes’ Hot Track List.
How was AI able to compose a song? In this case, it was more of giving the artist specific elements he needed to create the hit. In the creation of ‘Not Easy’, Grant explained that he used an AI solution to scrape millions of conversations, newspaper headlines, lectures, and speeches to find a theme that has resonated with humanity in the last five years. The result that the AI solution got? Heartbreak.
Grant would go on to use that as the theme of the song he was writing, as well as using musical elements that the AI solution also came up with while using its machine-learning music generation algorithms. Grant picked the ones he liked the best and used them for his song, and the rest is chart-topping history.
Preserving Wildlife
Preserving wildlife may seem like something that’s usually left to scientists, biologists, and nature-loving individuals more than happy to trek through jungles and wilderness in order to help. More recently, however, AI has found a role in environmental protection and preservation as well.
Keeping track of so many animals in such vast swaths of land – especially when jungles, mountains and deserts are concerned – can be quite challenging. Not only would wildlife conservationists need to track down, subdue, and tag every endangered species, but they’d also have to have enough satellites in the sky to track each and every one.
This is where AI comes in, introduced to the scene by Tanya Berger-Wolf, a professor of computer science at the University of Illinois in Chicago. Berger-Wolf and her colleagues developed Wildbook.org, a website that houses an AI system and algorithms. The AI system installed in the website is programmed to automatically inspect photos uploaded online by wildlife experts, enthusiasts, and even the public. With its algorithms, it is able to recognize the animals captured in the photographs through their unique markings, and from there track its habitat range by using GPS coordinates provided by each photo. It’s also able to estimate the photographed animal’s age as well as its gender.
With the help of Wildbook.org, the endangered Grevy’s zebra that’s native to Kenya was saved through a huge photo campaign in 2015. Through Wild books analysis, it was found out that lions were killing too many babies of the endangered zebra species, which prompted the local officials to make changes to their lion management program in order to stop any more undue killings.
These solutions are only a few of the many possibilities of AI. In truth, we are barely scratching the surface as far as the potential artificial intelligence is concerned. But with AI being heavily researched, developed, and invested into nowadays, it is likely that we will be seeing more unexpected ways in which AI can be applied to everyday life.
