You interact with artificial intelligence on a daily basis and you don’t even know it!
AI is everywhere! If someone came up to you and said that you’ve spent all day interacting with artificial intelligence, you’d probably try and recall any potential instances of accidentally running into a robot.
AI comes in many forms, shapes and sizes – some of which may surprise you. Not only has artificial intelligence been made mainstream within a number of industries, but it is also allowing us to streamline our businesses and optimise our lives. From social media to public services, we are all coming across some form of AI every single day and it may surprise you on how broadly it is being incorporated without us even taking notice.
According to a 2015 report by the Texas Transportation Institute at Texas A&M University, commute times are steadily climbing year-on-year, resulting in over 42 hours of rush hour traffic delay per commuter in 2014 – more than a full work week per year carrying an estimated $150 billion loss in productivity. This presents a valuable opportunity for AI technologies to be implemented in order to create a tangible, visible impact in everyday life.
Reducing real-time commute times for each individual person, 24 hours a day and 7 days a week is something a human being is simply not capable of. A single trip may involve multiple transportation methods (i.e. driving to the train station, taking the train and using ride-share services to get to your final destination), not to mention the expected and unexpected events which constrict traffic flow: traffic, road works, accident, diversions and weather conditions. Here is how you interact with AI:
1) Google’s AI-Powered Predictors
By using anonymised location data from smartphones, Google Maps can analyse traffic flow at any given moment in time. Not only that, but with its acquisition of crowdsourced traffic app Waze, Google Maps can easily incorporate user-reported traffic incidents. The access to these vast amounts of data being uploaded into its proprietary algorithms results in Google Maps diverting and warning you beforehand about any unexpected incidents to ensure your commute remains efficient.
2) Ridesharing Apps (Such as Uber and Lyft)
Ever wonder how these apps determine the price of your fare, reduce wait times and how they pair you with other passengers to minimise detours? Thank Machine Learning (ML). It is what allows us to create such efficient transportation services available at your fingertips.
Jeff Schneider (Uber’s lead engineer) discussed how the company uses ML to predict the rider demand which ensures that the “surge pricing” (short periods of sharp price increases to decrease rider demand and increase driver supply) is relative to the supply and demand of passengers and drivers. Not only is machine learning used in Uber’s taxi systems, it is also used for ETAs, determining optimum pickup locations and fraud detection within its payment services.
3) AI in commercial flights
A surprisingly early use of AI technologies which dates as far back as 1914 comes from the autopilot systems used within the aviation industry. The New York Times reports that the average flight of a Boeing plane involves only seven minutes of human-steered flight, which is typically reserved only for take-off and landing.
Banking and Personal Finance
Machine learning is playing an integral role in the many phases of the financial ecosystem which range from loan approval, asset management and risk assessments. There are now more uses for machine learning in the banking and finance sector than ever before which is made available by the SMART technologies we create.
1) Mobile Banking
Most banks now grant you the ability to deposit and transfer cheques and funds via their smartphone and web apps – eliminating the need for us to physically go to the bank. According to the Security and Exchange Commission, the vast majority of banks now heavily rely on AI and ML technologies to decipher and convert handwriting on cheques into text via OCR in order to ensure authenticity and prevent fraudulent activities.
2) Fraud Detection
Due to the volume of financial transactions being far too high for humans to manually review each transaction (correlated to the popularity of online banking and fast payment systems), AI and neural networks are implemented to work in conjunction; learning what types of transactions are fraudulent via specific algorithms. This works by detecting factors which affect the neural network’s final output such as transaction frequency, size and parties involved.
3) Credit Decisions
Every time we apply for a loan or credit card, financial institutions quickly determine whether they accept or decline our application to be entitled to access their services. Their use of AI and ML technologies essentially determines your credit and risk scores, ultimately influencing interest rates and credit amounts for each and every individual customer. MIT researchers found that machine learning could be used to reduce a bank’s losses on delinquent customers by up to 25%.
So how do we interact with artificial intelligence through our social media? The truth is, AI is what helps our everyday user experiences on social media platforms get better. The development of deep learning technologies to sort through large amounts of data helps adjust the platforms’ suggestions, news feeds, trending topics, hashtags and even tagging your appropriate friends in photos – all without spending too much manpower in data analysis.
When you upload your photos to Facebook, the platform automatically detects faces and suggests tagging the people in it. How does Facebook do this? Well, Facebook uses AI and neural networks to recognise faces and power the facial recognition software. Their use of AI doesn’t stop there. Facebook also uses AI to personalise your newsfeed, ensuring that you see posts which match your interests and from paid advertisements. Better targeted ads mean that you’re more likely to purchase something from these advertisers because of your matched interests, avoiding ads which are not relevant to you.
Instagram uses machine learning to identify the contextual meaning of emojis which have been steadily replacing slang (for example, a laughing emoji could replace the word “lol”). By algorithmically identifying the sentiments behind emojis, Instagram can create and auto-suggest emojis and emoji hashtags. Although this may seem like a trivial application of AI, Instagram has seen a substantial increase in emoji use amongst all demographics, therefore, being able to understand and analyse this emoji-to-text translation at a large scale sets the basis for further analysis on how people use Instagram.
For those not familiar, Snapchat introduced their facial filters back in 2015. These filters tracked facial movements, allowing users to add animated effects and digital masks which adjusted when their faces moved (similar to Apple’s animoji concept). So how does this work? The filters are powered via machine learning which tracks movements in real-time video which allows us to interact and personalised our “selfies” in ways never before imaginable.
To wrap it up
We have just scratched the surface of the abundance of AI, ML and neural networks encountered in our everyday lives. Many industries still form a greater habitual interaction with artificial intelligence far beyond what’s explored in this article. But AI doesn’t necessarily have to be limited to corporate uses. AI can also be applied to activities such as our own hobbies. For example, casual chess players are now using AI-powered chess engines to analyse their games and practice custom tactics. But it doesn’t stop here. Bloggers often use their ML optimised mailing lists to optimise reader engagement and open rates.
As you can see, AI is developing an important role in our current and future lifestyles. Without it, arguably, we would feel a bit lost seeing as so much of these technologies are implemented into our daily activities.
ARTIMUS is a Bespoke Solutions company based in the South West region of the UK. They Specialise in Artificial intelligence solutions and pride themselves on being able to provide the best, highest quality development and project management services that you can find on the market.
Their mission statement is to “Focus on innovation: we want to create unique, outstanding technologies that will help us get one step closer to the simplest future possible. We are fully committed to bringing in artificial intelligence and multi-use solutions that work for companies all over the globe.”
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