Think AI ‘spies’ are new? Nine ways we have been tracked for decades

Worried that your privacy is being eroded by the advent of AI? It might shock you to learn that technology has been ‘spying’ on us for decades. Here are nine ways we’ve been tracked.

In late 2022, Artificial Intelligence (AI) seemed to appear out of nowhere with the launch of ChatGPT. It achieved almost instant widespread acquisition, with businesses racing to leverage their products and test out new features, while the rest of us enjoyed the fascinating novelty.

Over the years there has been a decrease in human intervention in all aspects of our lives. We’ve slowly gotten used to chatting to robotic operators, and asking our phones for directions. But while the future of AI feels unknown and exciting, there is still a lack of understanding around the technology and its potential. 

But despite it appearing to burst into our lives unexpectedly, AI and machine learning has actually been operating in the background for decades now. Surprised? Prepare to have your eyes opened as domain and hosting provider Fasthosts share nine ways AI has been profiling us – long before we may have even been aware of it. 

1) Predictive text 

Predictive text has been around for over a decade. A step beyond autocorrect, when typing on a keyboard or device, the software being used will suggest words and text the user may want to insert. The suggestions are generated through natural-language processing (NPI) and machine learning to create a database of words and phrases the user uses regularly to develop future recommendations. 

2) Car navigation

Whether in your car’s GPS device or on your smartphone, the idea behind automated navigation systems is to emulate how a person would already drive if they knew these roads. GPS uses machine learning – as more data is collected over time, the better the system gets at selecting the right route, continuously analysing the users habits, road, and traffic environments. 

3) Social media feeds

Algorithm. A popular yet disliked term in the world of social media which uses social profiling and cookies to learn as much about us as possible. The algorithm does this so that it can recommend content it thinks we may like to keep us engaged on a platform for as long as possible. Gotta keep you scrolling.

4) Smart home devices 

Tech such as the Amazon Alexa or Google Home also use a type of machine learning where they analyse the data they collect about their users, to learn about their habits and preferences. That way, they’re able to predict users’ future decisions and choices, and apply these with minimal human intervention. 

5) Facial recognition

You know that handy little phone unlock tool that only needs a flash of your face? Yep, that’s also machine learning. The algorithm can detect and locate the human face, extract unique features, and then match these for authentication reasons. The system uses continuous learning to keep learning and improving its accuracy when incorporating various factors such as angles, lighting, and facial expressions. 

6) Streaming recommendations 

Amazon has supposedly been using algorithms since its inception. Much like social platforms, streaming services – whether that’s Netflix or Prime – have been using machine learning to offer their users tailored recommendations, and guide them to make choices based on what the algorithm has learnt of them and their interests. 

7) Adverts

Ads that you see online use personalisation by collecting your data to increase the relevance of the ads you’re shown. Using machine learning and audience segmentation, ads can be targeted to a certain type of individual, who meets particular demographics, geographic, or psychological characteristics. 

8) Home security

Traditional home security systems are good at detecting motion but that’s about it. Anything from pets, deliveries, and potential outside triggers can activate detectors and set off false alarms. With the implementation of AI, home security systems are able to recognise specific people, and filter out different sounds and behaviours. 

9) Smartphone assistants

Those little assistants in your pocket – like Siri or Google Assistant – use voice recognition and natural language processing (NLP) to do just about anything from understanding and responding to voice commands, to controlling devices, and actioning various tasks without requiring any physical input.

To improve their accuracy, smartphone assistants also gather more info about their user, that way they can better recognise voices and preferences, offering a further personalised experience. 

Photo by Mollie Sivaram