The cutting edge of technological advancement seems out of reach for most of us, and that’s particularly true when it comes to artificial intelligence (AI). AI remains a strange concept, something that’s difficult to picture in our minds with any clarity.
AI conjures up conflicting visions for humankind: will it produce a dystopian future for us, or does it offer the prospect of better days ahead for our species? Do we face being subordinate to a non-human form of intelligence, or will we master this technology and create a future world where poverty and disease are things of the past; where road accidents no longer happen; and where everyone has their own digital assistant?
Either way, for most people the world of AI is shrouded in mystery. But how do we begin to understand this murky world?
Whatever narrative we decide to attach to it, perhaps the first thing to understand is that AI does not refer to one piece of technology. In fact, AI encompasses a wide range of research fields and technologies where advances are being made every day.
It isn’t the case that AI is being used to create either the utopian or dystopian scenarios mentioned above. As always, the truth lies somewhere in the middle. AI is an evolving science that affects us in lots of different ways, and with just a little bit of understanding we can start to see what it actually is – and what it may become.
In our introductory article, What is AI?, we touched on some of the ways we interact with AI during a typical day. In this article, we’ll expand on those examples and discuss their impact on our lives in more detail.
Chatting With AI
Have you ever asked Amazon’s digital assistant, Alexa1, to play a song while you’re cooking? Maybe you ask Apple’s Siri2 what’s on your calendar on the way to work each morning, or dictate messages to your phone when your hands are full?
If you do any of these things, you’re already talking to AI. Digital assistants3 have become such an integral part of our lives that we already take their capabilities for granted.
But if you pull back the curtain, you’ll find technology that relies on key aspects of artificial intelligence, such as natural language processing (NLP)4 and machine learning5. They are the reason your device is able to obey your voice commands and improve its performance over time.
When you give Alexa or Siri a command, it’s recorded and sent over the internet to a computer which then generates a response and sends it back. As you give the device more and more commands, it feels like it’s getting to “know” you better.
This is because every time you make a request, the device “learns” a little bit more about your behavior and adjusts itself accordingly. So the more commands you make, the “smarter” your device will seem.
Watching TV With AI
The way we watch TV has changed a lot in a relatively short time – you don’t have to be very old to remember the days of having to wait a whole week for the next episode of your favorite show.
Fast-forward to the present day and you have a practically limitless choice of viewing options available at the click of a button. And you can binge6 them, too – no longer do you have to agonize for a whole week over who might’ve killed your favorite character!
What’s more, these days your TV comes bundled with a “best friend” that knows what you like and suggests shows it thinks you’ll enjoy. Given the vast number of TV shows and films there are on streaming services7, imagine how long it would take to find something to your taste by scrolling through all the available options. Sure, you might get lucky, but chances are you’d be there for hours. So how does your new “best friend” know what to suggest?
This TV pal is actually a recommendation engine, and it has a vast library of data to call upon when making decisions. This engine has an extensive record of not just your viewing history, but everyone else’s too. It knows what you watched, how long you watched it for, whether you binged it in one night or whether you gave up after a few episodes, and based on all of this data it offers recommendations.
By the way, a similar friend can also be found in your music streaming service, and it is doing something very similar. What do you listen to on repeat? When do you turn up the volume? What sort of music gets you going in the morning? What helps you relax in the evening?
All of these data points combine to make up your personal profile and place you in a group of similar, like-minded people. If a few people in a group like a particular show, there’s a high chance most of the others will too.
Recommendation engines have automated the old fashioned “word of mouth” principle: you’re now providing indirect recommendations to your peer group via the decisions you make as you watch or listen.
This personalization and curation of the viewing experience has transformed how we consume entertainment, but the technology won’t stop there. The way we watch TV will continue to be optimized across all of our media channels by technology that knows exactly what will appeal to us at any given time. Eventually, it will even be able to create content on its own, specifically tailored to your current mood.
Remember how we talked about the good and the bad of AI earlier? This optimization of the viewing experience might provide us with a never-ending supply of delightful entertainment, but it won’t point us towards things outside of our comfort zone. Opportunities for fresh discovery and surprise may start to diminish. This is a classic example of AI working both for and against us.
Reading the News With AI
Once you understand how these recommendation engines work, you can start to see lots of uses for them. So you shouldn’t be surprised to learn that your news and social media consumption is being filtered for you in much the same way as your TV and music.
News and social media platforms gradually get to know your habits, interests, and preferences as a reader. They gather information on which stories you looked at, how long you looked at them, what you clicked on next, and whether you shared them with your friends or on other platforms. AI-enabled personalization then uses this data to guide you towards content you will find relevant.
Here again we find ourselves weighing up the positives and negatives of this technology. Yes, it makes for a really pleasurable reading experience that feels personalized and keeps you engaged. However, increased engagement also exposes you to more advertising which is employing its own sophisticated algorithms to figure out your interests.
We also have to consider the effect that the personalization of everyone’s newsfeed will have on the population when people only ever see content they agree with. When everyone lives inside their own little “filter bubble”,8 society as a whole risks becoming very polarized.
Being aware of these forces when you consume your news and social media gives you greater control over your overall social and news media experience. The totality of what’s really happening in the world is likely to be much more complicated and nuanced than what you see on your newsfeed.
Hitching a Ride With AI
Ridesharing9 is a great example of how technology is disrupting society by introducing big changes in the way we travel.
The idea of ridesharing apps is something we now take for granted. However, using GPS to track and organize every available vehicle, manage logistics, and take payments all in a simple application required a huge amount of ingenuity and automation.
This “miraculous” technology has completely changed how we think of transportation in our cities. At the touch of a button, a car arrives at your location within a few minutes and takes you directly to where you need to go. These ridesharing apps were ingenious at their inception, but thanks to AI they’re becoming even smarter over time.
Have you ever wondered how it’s possible that there always seems to be a vehicle available in your area whenever you need it? It’s because ridesharing apps like Uber use AI technologies to improve every aspect of their service. They use AI to determine arrival times, set prices, and forecast user demand to work out where they should deploy drivers and at what times.
Only a few years ago, such a convenient and cost-effective way of organizing our travel would have seemed like something from science fiction. But it’s already an accepted part of our daily lives.
Shopping With AI
AI is already a big part of your online shopping experience, influencing everything from your weekly groceries to your Amazon orders.
Sellers online and on the high street use data gathered from your buying patterns and loyalty cards to personalize your shopping experience. Predicting what you might want to buy before you even realize it yourself, and the personalized offers to incentivize you to buy it, are based on calculations made by AI.
And it won’t stop there. As this technology becomes smarter, the way we shop will change beyond recognition, becoming increasingly personalized and experience-based. It could become so effective at identifying what we want that we simply allow it to make purchasing decisions for us.
Imagine a future where your fridge is able to place an order for your groceries on its own, based on what’s in the fridge, what’s running low, and what’s out of date. It may even make purchasing decisions based on the time of year, the weather, how you’re feeling, or what you have planned in your social calendar.
Imagine an app that could recommend the perfect pair of shoes for your feet, or a mirror that shows you what different suits or dresses look like on you. This will be the reality of AI and shopping in the near future.
The washing machine and dishwasher revolutionized domestic life by taking care of mundane and time-consuming tasks. AI will do exactly the same for tasks like making shopping lists, or scrolling for hours on retail sites looking for the perfect item.
It sounds almost too good to be true, but again we must consider the positive, as well as the negative and potentially harmful consequences of experience-based shopping. When AI is able to delight us on a daily basis with purchases it makes on our behalf, it could create a completely new form of consumerism - a dangerous one, where there’s always a reason to come back for more.
Protecting Your Money With AI
In a relatively short period of time, we’ve gone from standing in line at the bank to conducting our financial transactions online. We’re now banking from the comfort of our own homes, at the click of a button, any time we choose.
The downside of this convenience is the potential for fraud. Having your credit card information – or even your whole identity – stolen can be an emotionally distressing experience. It also leads to a frustrating waste of your time as you try to resolve the fraud with your bank. You’ll probably get your money back, but only after hours spent on the phone and filling out paperwork.
But as fraudsters get more creative, so do the banks. Security systems in financial institutions use AI technologies to improve the safety measures that keep your money secure.
How does AI protect you from fraud? It begins by analyzing all of the data from your previous transactions to identify patterns: where are you spending? How much do you usually spend? How often do you travel? How often do you buy online? Which sites do you buy from? Do you shop using different devices?
With every transaction you make, the AI technology used by your bank learns a little bit more about your behavioral patterns. It then uses that knowledge to identify any transactions that look particularly unusual and sends an alert to the bank.
Fighting Crime With AI
AI identifies organized crime in much the same way. What’s actually going on when three unconnected accounts perform similar transactions within a few seconds of each other? What’s really happening when money is being rapidly passed through multiple accounts? These behaviors would be practically invisible to the human eye, but AI technology is able to spot them and alert human administrators so they can investigate further.
The interplay between humans and AI becomes ever more complicated as our habits change continuously, and criminals adapt to new technologies. Sophisticated criminal activity leaves patterns that humans would find incredibly difficult and time-consuming to discover. AI doesn’t have this problem – it is flexible and, more importantly, is able to operate at scale by looking at many, many patterns with increasing speed and efficiency.
In summary, AI is being used to prevent crimes and ensure our money is safe. It may even achieve a level of sophistication that will eventually make financial crime almost impossible.
Artificial intelligence is considered to be the defining technology of the early part of the 21st century. As you have just discovered, it is already an integral part of our lives and affects us in many different ways each and every day, whether we realize it or not.
AI is no longer a plotline in science fiction. It’s already here, and its power and influence will continue to grow rapidly in the coming years.
AI’s biggest advantages are built over time as algorithms collect more and more data and “learn” how to apply it. But the same applies to its disadvantages and potential dangers.
Ultimately it is human behavior – our collective influence on the world around us – that will determine the future role of AI in our world. It learns from us, so we should be careful what we teach it and how we use it.
The degree to which AI will influence our lives will not be decided by any individual. Rather, a collective understanding will be required if we are to make AI a force for good in the world.
Knowledge is power. And as we guide you through the articles of That's AI, it is our ambition to give you as much of this power as we can.
A digital assistant, sometimes also referred to as virtual assistant, is a computer program that can perform tasks or services based on commands or questions. The interaction with the user is usually in the style of a conversation. ↩
Natural language processing covers the scientific field that studies how computers can understand and interact human language. We will cover this topic in a later article, but for now please read this Wikipedia article for more information. ↩
Machine learning is a subfield of AI and will be explained in later articles. For now, know that machine learning describes a computer program’s ability to learn from data to improve how it functions. ↩
To binge describes a period of excessive consumption. For example when you consume a huge amount of food, drinks or in this case, many episodes of a TV shows. ↩
Streaming services, like Teleclub, Netflix, Amazon Prime, Apple TV+ or Disney+ allow you to select a TV show or a movie from a huge collection of choices, and watch them whenever you want. Within seconds, the content is streamed live to your device and therefore doesn’t require you to buy a physical copy of it, nor to fully download the whole content before you can watch it. ↩
A filter bubble describes the state of intellectual isolation, due to personalized search results and selectively chosen social media content. Like in a small bubble, you are only exposed to things that agree with you or which please you and therefore shaping a very unique experience, disconnected from our collective, social reality. ↩
Ridesharing describes the circumstance where a person uses an application or website to order a car to a specific location, for the purpose of being driven somewhere else. Like a standard taxi service, with the important difference that passenger and driver can validate and grade each other to improve future experiences. ↩