How far is too far when it comes to machine learning? We live in the digital age where companies like Google collect information which feeds and informs their algorithms, potentially advancing their technology into the realm of the uncomfortable. When it comes to digital AI and algorithmic predictions, when do we say enough is enough?
Algorithms are digital codes that sort, predict and filter information in a fashion that is similar to the way the human brain works. They are in effect all over the internet, from Google’s search predictions to Netflix’s recommendation section.
Algorithms help advance machine learning, as they are, at a basic level, strings of information fed into a computer. 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…sounds eerily like the film minority report? You’d be surprised how rife algorithms already are within our society.
Businesses using algorithms
Businesses already use algorithms to boost their profits by personalising their marketing at customers. However, this can very quickly end up out of control and causing controversy instead of brand loyalty.
As an example, we’re looking at US retailer Target. They quickly discovered how near the ‘uncanny valley’ their algorithms could be when they began compiling user purchase data to create ‘buckets’ of customer knowledge.
They used this data and ran tests to see which trends emerged – discovering that in the first 20 weeks of pregnancy, women consumed lots of calcium, zinc and magnesium. This enabled them to predict when their customers were pregnant and begin marketing coupons and offers at them.
This ended in a damaging PR issue when the company ended up predicting a teenager’s pregnancy before her parents knew about it, sending coupons and other baby themed offers to their family home. Target were forced to apologise.
Algorithms in law enforcement
What was once the realm of sci-fi cinema is starting to become more and more of a reality. Modern day policing is using machine learning to help snare criminals…
In 2014, the LAPD fed 13 million crime incidents to the University of California. Using this data, an algorithm was produced that predicted areas where crime was likely to occur on a ‘mission map’. The trial of this algorithm saw a 36% drop in crime rate.
This kind of data can cause issues if relied on completely. For example, an algorithm used by US parole boards can 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 1 out of every 4 times.
How Google is pushing the boundaries of prediction
Google itself has openly stated it is a machine learning company. 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 themselves won’t even know everything that their algorithm is made up of. In the near future, the Google search engine will be able to decide where a website ranks with no human input.
Google also uses user information such as your purchases and travel information to present a more personalised experience. As a post on marketing agency Mediaworks’ website indicates, personalised results could become intrusive, with a recent Google update displayed 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.
This degree of personalisation can be intrusive, but it can also be very useful. In a world where habits shape 45% of the choices we make, behavioural research and predictive analytics are gold-dust for businesses.
If you’re setting up a business, the world of machine learning and algorithmic AI allows you to tap into vast 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.
Google’s future – true AI?
Aside from their search engine, Google is actively part of a ‘deep learning project’, once named the ‘Google brain.’ This is the world’s leading branch of AI and it is one that is constantly learning new things.
To illustrate this machine learning capability, scientists presented the ‘brain’ with 10 million YouTube 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 a 81.7% accuracy in detecting human faces despite not being fed information that defined what one was.
In 2013, Google acquired DeepMind, a London-based AI company. 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.
Recently, Google has begun incorporating elements of DeepMind and their brain project into search engine rankings. Where this kind of autonomous AI will lead remains to be seen.
How a business is effected
Google is undoubtedly the most popular search engine in the world. There are over 100 billion searches a month through Google, which is a massive 75.2% share of the market. If you run an online business, you cannot afford to not rank properly on Google.
Recent updates have penalised sites with poor mobile optimisation and introduced an AI ‘RankBrain’, which can determine how relevant your site is to a user’s query. 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 the AI’s mercy when it comes to displaying our business online?
Sources:
http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=1&_r=2&hp
https://backchannel.com/google-search-will-be-your-next-brain-5207c26e4523#.143v9oq5q
http://expandedramblings.com/index.php/by-the-numbers-a-gigantic-list-of-google-stats-and-facts/
