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Applications of AI for day to day work
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13 Applications of AI You Can Relate to Your Day to Day Work

Introduction

Artificial intelligence has created hype and excitement due to constant media attention. This has made it quite difficult to see its effects on our day-to-day lives. The general perception of many people is that artificial intelligence is still considerable years away from causing any effects on our lives. However, it is already having an enormous impact on our everyday lives by impacting how we live and also how we make decisions.

Today, in the digital era where the internet has become one of the most basic needs, people are using AI without an actual acknowledgment. They use AI for communicating online, on the commute to work, searching the web, making online purchases, and for so many other activities.

Nevertheless, according to an article published in The Guardian based on Pew Research, as many as 72% of Americans concerns about machines performing human jobs. Despite all the concerns and worries around the advancement in technology, AI is already connected to us in several ways such as Siri, Watson, Alexa, and so many others.

More and more companies are investing in machine learning and some statistics can give an idea about its growth. According to the prediction by Gartner, by the end of 2018, customer digital assistants will recognize customers by face and voice across channels and the percentage of deployment will increase from 45% in 2018 to 55% in 2019. According to Forrester, by 2025, artificial intelligence will replace 16% of American jobs.

The general perception remains that AI is not limited to the IT or technology industry rather it is being extensively used in other areas including business, healthcare, law, education, and manufacturing. Let’s see some of the ways it is changing our lives and some of its day-to-day uses.

Application of AI at Home

1. Smartphones

Today, the smartphone has become one of the most indispensable technologies of all time. A smartphone is the simplest example of interaction with AI due to its inbuilt features such as smart assistants, portrait mode in cameras, and others. Many smartphones and big chip manufacturers are including more and more AI to produce chips with AI capabilities.

The integration of AI with smartphones helps them enable features such as mixed and virtual reality elements, scene detection, and more. There is already a great emphasis on AI with the latest iOS and Android updates. Several common features we see in phones today have been made possible with AI such as splices, app actions, and adaptive battery in Android, and Siri shortcuts and Siri suggestions are made possible with AI.

2. Smart Home Devices

Today’s new homes are increasingly becoming smart with multiple gadgets to make lives ease. These smart devices include smartwatches that track daily steps, thermostats that learn about our heating/cooling preferences, smart refrigerators that create lists as well as offer wine recommendations, and many other smart appliances.

smart home devices

There are also home voice-based AI assistants such as Google Home, Echo, and Cortana which use natural language processing (NLP) to generate answers. Digital voice assistants are quickly becoming our go-to for everything from getting directions to inquiring about the weather. These AL-based voice assistants even learn our behavior to adjust the settings themselves.

Application of AI in Commuting

3. Navigation and Predictions

AI-powered tools such as Google Maps calculate speed by the movement of the traffic and construction to predict routes to the destination. In 2013, Google acquired a crowd-sourced traffic app named Waze which made user-reported traffic incidents such as construction and accidents easy.

Google proprietary algorithms are fed a huge amount of data to reduce commutes by suggesting the fastest routes. This AI plowed application is used in the daily life of many people and for many occupations. It has replaced the need to carry a hard copy of maps even when venturing into a new city or location.

4. Ridesharing Apps

Ride-hailing apps have become indispensable to many as they have simplified daily commute. People have been using them without realizing that they use AI to determine the price of your ride, minimize the wait time, optimally match passengers with each other passengers to minimize, and others. They all use ML to make your ride easy, convenient, and smooth.

In an NPR interview, the engineering lead for Uber, Jeff Schneider discussed in an interview how the company uses ML to predict rider demand to ensure a surge in price.

Also Read: Top 10 AI Trends In 2022

Application of AI in Banking and Payments

5. Mobile Check Deposits

Unlike the traditional method of physically delivering a check to the bank, today, some of the world’s large banks offer the option to deposit checks through a smartphone app. The vast majority of such banks rely on Mitek technology which uses AI to decipher and convert checks that are handwritten into text via OCR. Banks are using AI to personalize user’s experience on mobile apps with reminders and alerts for bill pay, pre-overdraft, and transfer prompts.

6. Fraud Prevention

The daily transaction volume in financial institutions is enormous and manually reviewing each transaction is impossible. This makes determining fraudulent transactions complicated, hence, these institutions utilize AI-based systems to determine the transaction type. AI takes several factors into account to determine a frequent action such as transaction size, recent frequency of transactions, and the kind of retailer involved. They are also utilizing AI by sending mobile alerts. For instance, the customer receives a message alert if an unusually large transaction.

7. Payment

AI-based apps such as Google pay, Paypal, and many others have helped financial institutions streamline the functionality of payment technology. Today, many consumers use convenient payment with the help of personalized banking. These apps use machine-vision AI, store credit, and debit card data with biometric to secure payments.

Application of AI in E-commerce

8. Search

Histories of a customer’s previous searches help e-commerce websites determine and predict the most relevant products. For instance, Amazon searches return a list of the most relevant products related to your search. It utilizes an AI-powered product search technology. Its algorithms work by automatically learning to combine multiple relevant features through its catalog structured data. It learns from past search patterns and adapts according to the customers.

9. Personal Recommendations

On any e-commerce website, customers usually get personalized recommendations for products. This list is generated with the help of AI algorithms that learn the pattern of customer searches. It also notes similar patterns from other customers and shows the option of “customers who bought this item also bought”.

10. Fraud Protection

There is again a chance of fraud during online credit card transactions. E-commerce websites use machine learning for fraud prevention. AI is deployed by e-commerce websites not only for fraud prevention but also to minimize legitimate transactions being declined due to being false identification.

In a press release, MasterCard elaborated on how false declines due to fraud threats lead to 13 times more revenue being lost. AI can help prevent this issue as it learns purchase habits and credit card processors to help minimize the probability of declining.

Application of AI in Social Networking

Social media has greatly impacted our society, even more than some of us might like. According to the Global digital overview, more than 4.5 billion people were using the internet at the start of 2020. Social media users have passed the 3.8 billion mark and nearly 60% of the world’s population is already online. The latest trends suggest that by the middle of this year, more than half of the world’s total population will use social media.

11. Facebook

Facebook utilizes advanced machine learning for almost everything from serving customers content to facial recognition of photos and target users with advertising. Instagram which is also owned by Facebook, uses AI to identify visuals. For example, when someone uploads a photo the server automatically suggests a friends tag.

They also use AI to personalize content and showing ads to the consumer by learning their interests from history. These targeted ads are shown only to those people that are likely to click, meaning more sales from the advertisers. The company has enormously invested in facial and visual recognition through the years to understand the technology better. They also acquired facial-recognition startups Face.com in 2012, Masquerade in 2016, and Faciometrics in 2016.

12. Pinterest

Pinterest uses an AI-powered computer vision application that enables computers to see. It allows them to automatically identify objects in images to recommend visually similar pins. Many other applications of machine learning are being utilized by Pinterest to better serve its consumers such as spam prevention, ad performance, search and discovery, monetization, and email marketing.

13. Snapchat

Snapchat leverages similar AI-powered tools of computer vision. This AI technology tracks features and overlay filters. These filters also move with faces in real-time allowing users to add animated effects or digital masks. It introduced facial filters, in 2015, called Lenses.

Conclusion:

Artificial intelligence has already become an integral part of our day-to-day life. It is often said that AI is the future of technology; on the contrary, it is the present. In this blog post, we have tried to scratch the surface of the applications of AI, but they reach far and wide. This blog post not even covers those industries that have habitual interaction with AI. For example, bloggers and other advertisers often use mailing-list services which are powered by ML to optimize reader engagement. The tale of AI and ML doesn’t seem to have an ending. People have embraced it for years and with its current advancement, we can only tell so much.

Linda Hadley

Tech Insights Digest

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