The advancements in technology is enabling businesses across the world to better target their audiences. We live in the digital age where companies like Google, Facebook, Instagram and more, collect information which feeds and informs their algorithms, potentially advancing their knowledge of us to an almost uncomfortably intrusive extreme. When it comes to digital AI and algorithmic predictions, when do we say enough is enough?
The purpose of an algorithm is to sort, predict and filter any types of information in a similar way that the human brain does. Websites across the internet are using this to their benefit, and you’ve probably noticed Google predicting your searches and Netflix recommending what to watch.
Essentially, they are strings of information that flow into a computer to advance machine learning. As well as helping personalise the internet through recommendations and suggestions based on your actions online, algorithms can have more nefarious uses. Search algorithms, for instance, could be used to predict the likelihood of you committing a crime in the future. You’d be surprised by how rife algorithms already are within our society.
How businesses are using algorithms?
Businesses like to personalise the experience for their customers, and most are using algorithms to achieve this. However, this can very quickly end up out of control and cause controversy instead of brand loyalty.
One example of this is the American superstore, Target. It quickly discovered how potentially detrimental its algorithms could be when they began compiling user purchase data to create an account of customer knowledge.
According to the data they were gaining, women consumed more calcium, zinc and magnesium within the first 20 weeks of their pregnancy. This enabled them to predict when their customers were pregnant and begin marketing coupons and offers at them for baby-focused products.
In one incident, the company predicted a teenager’s pregnancy before her parents knew about it — after issuing marketing materials such as baby coupons to her family home. This soon became a topical PR disaster and the store was forced to make an apology.
How UK police are using algorithms?
Police forces in Britain are beginning to adopt futuristic technology that enables them to predict the areas where criminal activity is about to occur — something that was once the realm of sci-fi cinema. Helping to reduce crime across the country, Kent Police is leading the technological movement using predictive crime mapping that is already being used in the US.
According to the Royal United Services Institute for Defence and Security Studies (RUSI), police in Britain already have access to massive amounts of data but don’t know how to effectively work with the volume and use it to their advantage.
Previously, police would just monitor communities and drive around in their vehicles waiting to be directed by the call centre to deal with 999 calls. However, it has been found that in the UK, it’s ten times more likely to accurately predict future crime rather than random beat policing — which is beneficial when it comes to command centres distributing their resources where they’re most needed.
Using maps that were originally used to detect earthquakes, these systems have the ability to pin a series of locations on a map — and every 15 minutes spent in a 500ft square equates to a two-hour crime free area. With this revelation in policing, the Home Office has invested more than £1bn into national law enforcement digital programmes.
But what does the future hold for policing in the UK? Well, an algorithm used by US parole boards has the ability to forecast the likelihood of a person committing a violent crime to help decide who to release and how to decide on an appropriate prison sentence. This system has a 75% accuracy rate, which may seem high, but in actual fact means that the system is wrong one out of every four times.
What is Google’s stance on user prediction?
Google has said that it is a machine-learning corporation. Its algorithms combine and evolve to feed an ever more complicated system that decides how to present information to the user. As it grows, Google won’t even know everything that its algorithm is made of. In the near future, the Google search engine will be able to decide where a website ranks with no human input.
Google wants to enhance the user experience overall and uses purchase and travel information to give searchers a more personalised journey — helping them find what they need almost instantly. As a post on SEO marketing agency Mediaworks’ website indicates, personalised results could become intrusive, with a recent Google update displaying product information in more generic searches. This is somewhat jarring for a user, who may be searching for a CRM system like Capsule but be presented with purchase information from their last coffee capsule purchase.
There is a lot of debate around how personalised our searches should be — with some saying its intrusive and others stating that it helps their decisions. In a world where habits shape 45% of the choices we make, behavioural research and predictive analytics are gold dust for businesses.
For eager entrepreneurs that are starting up their own company, machine learning and algorithmic AI can give you access to a great deal of knowledge. You can use data gathered from user behaviour and purchases to predict how they may act in future or tailor marketing efforts to their likes, dislikes and buying habits.
What does the future look like for AI and Google?
Google Brain is the world’s leading branch of AI after starting in 2011, and the research team is constantly learning new things by combining open-ended machine learning and system engineering.
To showcase the power of machine-learning capabilities, scientists presented the brain with ten million video stills. Without any human input, the machine figured out what a cat was. For a system which had no previous conception of the feline race, this was monumental — it had developed its own concept of a cat. It also did this with human faces, delivering 81.7% accuracy in detecting human faces despite not being fed information that defined what one was.
With AI growing in popularity, 2013 saw Google acquire a British artificial intelligence company named DeepMind. DeepMind’s program played millions of Atari games and, in a system similar to algorithmic learning, began analysing strategies — ultimately inventing techniques to help it win that no living being had ever tried before.
The impact businesses face
Unarguably, Google is the most used search engine in the world. There are over 3.5 billion searches a day through Google, which is a massive 74.54% share of the market. If you run an online business, you cannot afford to not rank on Google.
Not only that, if your business’ website is not properly optimised for mobile use, you will be penalised. As this machine-led style of learning begins to determine rankings independent of users, how will businesses find a way to rank effectively — or are we all at AI’s mercy when it comes to displaying our businesses online?