Let’s discover tomorrow’s world today with the help of contemporary trends in emerging technologies! Sounds fascinating right? It’s no clandestine that emerging technologies are splendid and mind-boggling. Just imagine, one fine morning you wake up and grab your mug of hot coffee/tea, and while you’re sipping your coffee/tea in serenity, you suddenly notice that your coffee/tea mug is monitoring your caffeine intake and sending this data to your doctor/physician in real time. Awe-inspiring right? But, does this sound like a talk of distant future? Well, to me it seems that it is not something which is going to happen in the distant future in fact it’s approaching very fast. As technology is constantly evolving, we are getting bombarded with fresh and astonishing innovations every day. These innovations are inspiring our imagination, reshaping the world, and changing the way we live. From Artificial Intelligence (AI) driven robots to quantum computing, the potential of technological advancements looks infinite!
So, are you scared or ready to embrace future and emerging technologies with open arms? And when I say the future, I mean the tangible future with stuff like flying cars, robot assistants, self-driving cars, and even beyond that such as time travel who knows! Though we are not there yet but, we’re getting closer to it by each passing day, and this all seems imminent. So fasten your seatbelt, grab your hot coffee or chilled juice and get ready for a furious ride because we are indulging in captivating world of emerging technologies by discovering some of the most thrilling emerging technologies that are influencing our dear world and our lives.
Without any further delay, let’s begin with the first blog of my miniseries on emerging technologies, and take a closer look at one of the most auspicious emerging technologies which is AI.
What Is AI?
We all are aware of the term AI but, just as a refresher, AI is a branch of computer science dealing with creating smart and intelligent machines, that are capable of performing activities and tasks that, normally, require human brain. AI has tremendous potential to change the way we live, in both positive and daunting ways. AI is already here knocking at our doors! But, are we ready for the looming AI storm?
What AI Can Do?
AI experts say that the upsurge of AI will put many people in advantageous position over the next decade or so. In my opinion, those people will definitely be the ones who will welcome, embrace, and learn AI. However on the flip side, there are many concerns as to how the upsurge in AI will affect the humans at large
So basically the positive impact of AI would be that it will augment human efficacy but, at the same time will also intimidate human autonomy, activity, aptitude, and capability. There are extensive likelihoods that computer machines might match or even surpass human intelligence in performing tasks such as intricate decision-making, coaxing, analyzing & recognizing patterns, graphic acuity, speech recognition, and translation of languages. This sounds appealing right? And why not, the smart computer systems in vehicles, buildings, utilities, agricultural farms, manufacturing, aviation, and in business processes will bring efficiencies, while saving time and money. Moreover, they will carry opportunities for individuals and businesses to enjoy a more tailored future.
Why AI Is An Emerging Technology?
A question may pop-up in your mind that AI exists since some decades now so, how it can be an emerging technology? Well it’s true that it exists since some decades but, still it’s an emerging technology because only in the recent past it has witnessed phenomenal growth and expansion. Given the potential of AI to transform businesses and societies as a whole, it is a safe bet to state that AI will remain an emerging technology in the near future, and researchers, technology experts, and developers will continue to push the boundaries of what is possible with AI.
What Are The Real Life Applications Of AI?
Now let’s see some real life applications of AI and try to visualize how our lives are going to transform in the future.
Use Of AI In Credit Card Fraud Detection
Conscientious people are asking questions like where AI fits into fraud detection. What are the benefits of AI, and where to start if we want to get benefitted from AI in detecting fraud? Are similar type of questions baffling you as well? Don’t worry; I am here to answer your questions.
One thing is for sure, you can’t compete with AI when it comes to big data examination/analysis. So, why not leverage the power of AI and use it for detection of fraud in credit card transactions, which is very common these days. As per estimates, fraudulent credit card transactions across Europe are more than €1 billion. Mind it! This is only Europe; imagine how big the number could be for the entire world if I extrapolate it. If your credit card is stolen or its details are captured by a fraudster, and the credit card or details are used to carry out some fraudulent transactions at either some online platform or at a point of sale, the AI with its advanced machine learning algorithms can aid in identifying these fraudulent transactions.
But first, how the advanced machine learning algorithm can be created and trained? The algorithm can be created in the form of a Neural Network. The Neural Network behaves like a human brain and produces swift results after examining/analyzing the complex and suspicious transactions. For training the algorithm, some real historical credit card transactions of the credit card holder (with his/her consent) can be used or publicly available dataset such as the IEEE-CIS Fraud Detection dataset can also be used.
Machine learning algorithms can be trained on this dataset(s) to recognize patterns and features of fraudulent credit card transactions. Once the machine is trained to recognize patterns and detect anomalies that indicate potential fraud, the Neural Network can be deployed in banks/financial institutions to analyze credit card transactions in real-time. Now, the Neural Networks are of various types. Among these, there’s type called the Multilayer Perceptron (MLP). This Neural Network is comprised of multiple layers of interconnected neurons. It is a widely used Neural Network architecture in detecting fraudulent credit card transactions.
In MLP, the neurons in each layer are connected to the neurons in the contiguous layers. So, what happens is that the input layer receives the data, and the output layer delivers the output of the Neural Network. While, the layers in between the input and output layers are called the “hidden layers”. The hidden layers actually perform the complex examination/analysis of data/transaction(s) which was/were being inputted.
When the bank/financial institution deploys MLP in real environment, it automatically starts detecting fraudulent credit card transactions in real-time. Normally, the banks/financial institutions set a threshold and the MLP analyzes incoming transactions and assigns a probability of fraud to each transaction based on that threshold. If any transaction exceeds the established threshold, the computer system automatically occludes the transaction. MLP is an effective Neural Network which is being used by banks/financial institutions for detecting credit card related frauds. So, by using MLP banks/financial institutions protect their credit card holders from financial losses and consequent mental distress. See this is how powerful and beneficial AI technology is for us!
In addition to credit card fraud detection, MLP is extensively used for image recognition, language processing, predicting flight delays, refining airline timetables, enhancing the quality of air traffic controls, elevating airport security processes, baggage handling operations at airports etc.
Use Of AI For Content Recommendation
Have you ever noticed that when you watch certain drama series or movies on platforms like Netflix, YouTube, Amazon Prime Video etc., you start getting recommendations for watching other similar types of drama series or movies? How this happens? Is someone sitting at the backend and sending you recommendations manually? No, basically it’s the AI algorithm which is working at the back and recommends content to you based on your tastes, preferences, viewing history, search history, and any explicit feedback provided by you.
There are multiple types of algorithms which are used to recommend content. Among these, two well-known algorithms are collaborative filtering and content-based filtering.
First let me explain collaborative filtering with a simple example. Let’s say your friends are following certain TV shows or movies on Netflix which resemble with your taste and preferences. So, in collaborative filtering the algorithm will analyze your taste and preferences based on your viewing history and since they are resembling with the tastes and preferences of your friends, the algorithm will begin recommending you the content which your friends have been following/watching.
On the other hand, content-based filtering algorithm will not provide you content recommendations based on what your friends followed. In fact, here the algorithm will analyze your historical actions and any explicit feedback you provided after following/watching the certain content. On the basis of this, content-based filtering algorithm will recommend you the content. For example, if you’re watching movies/TV shows of comedic genres, content-based filtering will note these actions and interests, and will recommend you movies/TV shows related to comedic genres, irrespective of what other viewers are watching.
Use Of AI For Detecting Money Laundering
In modern-day’s digital era financial services industry is facing a daunting challenge to prevent new types of financial crimes, such as money laundering, with the old technologies. AI is such a powerful technology of modern-day that it can be used for detecting complex money laundering transactions. Does it mean that currently financial services industry doesn’t have any systems in place to deal with money laundering? No this is not the case, even without AI, financial services industry has processes and systems in place whereby red flags are raised if any suspicious activities implying money laundering take place. Some of the processes and systems are even mandated by laws but, the issue is that these systems and processes are dominated by high levels of manual, monotonous, and data-intensive tasks that are inefficient and often decision-makers get flooded with too much information/alerts generated by these processes and systems, which makes them pondering where to put scare resources. Now, here AI can intelligently help the decision-makers. So, how AI can help with detecting suspicious activities implying money laundering?
AI can impart the computer systems to identify suspicious behaviors/actions and generate alerts but, classify the alerts in categories such as high risk, medium risk or low risk. So by applying AI, the false alerts will automatically be filtered out. This will facilitate decision-makers and their teams to emphasize and scrutinize on the small number of remaining alerts where there is a strong possibility of an illegitimate transaction/activity.
The use of AI for detecting money laundering is still nascent and in order to well explore and tap the potential of AI, the financial services industry needs to continue discovering capabilities, risks and limitations of AI. Moreover, there is a need to establish an ethical framework by which the use of AI can be governed and the efficacy and impact of AI can be proven and trusted.
Where Else AI Can Be Used?
AI has such an immense potential and it is transforming everything we do today. The list of above mentioned applications of AI is not exhaustive and there are numerous other areas where AI can be used for good. Few examples are healthcare, retail chains, manufacturing processes, transportation & logistics, customer services, agriculture, education, and many more.
The Time To Act Is Now
Emerging technologies are changing the world at an unprecedented pace. These technologies are transforming the way we work, communicate, and interact with each other. They’re also creating new opportunities for businesses, entrepreneurs, content creators, writers, innovators, photographers, movie makers, celebrities, accountants, auditors, etc. by disrupting traditional industries and markets by creating new & innovative ways of doing things. If we envisage and ponder about the future, it’s clear that emerging technologies will continue to play a significant role in shaping our lives and the world.