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Can AI Help You? Digital Intelligence in the Workplace

The ability that search engines like Google have is astonishing — with the power to predict your search by one single phrase. The TV you checked out whilst online shopping pops up again in your Facebook newsfeed as an advert. The more information we feed into digital companies' algorithms, the more relevant and precise results we receive. But at what point does assistance become intrusive?

With a similar performance to the human brain, search engines use algorithms which interpret information and bring you a relevant result. You can see them in action everywhere on the web, such as recommendations from shopping websites, or suggested videos from YouTube.

Simply put; these machines are learning — you will input information, and this is received to deliver a conclusion. This can be helpful by the ways outlined above, but as is the norm with advanced technology, privacy becomes a concern.

Can algorithms be used in business?

Businesses are beginning to use algorithms to enhance the customer experience — a common practice of this is by tailoring discount codes to a user’s preference. However, this can very quickly end up out of control and causing controversy instead of brand loyalty.

However, this isn’t always beneficial for retailer; and this was proven by Target’s experience. 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.

In the first 20 weeks of pregnancy, Target’s data was able to see that women consumed a considerable amount of magnesium, calcium and zinc. This enabled them to predict when their customers were pregnant and begin marketing coupons and offers at them.

This went drastically wrong when Target sent baby product offers to the home of a teenage girl; before her parents knew. Target were forced to apologise.

Can we predict crime?

Artificial intelligence has made its way into our police forces; and is beginning to create change. Modern day policing is using machine learning to help snare criminals…

The Los Angeles Police Department (LAPD) issued the University of California data of 13 million crimes. 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.

However, it must be stressed that police forces shouldn’t become fully dependent on it. 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.

Although; the system has a 75% accuracy rate. But this accuracy comes into question when you consider that it means the system is incorrect 1 in every 4 cases.

Understanding prediction

Tech-giant Google has always been transparent in being a machine learning organisation. 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. Soon, the Google search engine will be able to decide where a website ranks with no human input.

Google has a core focus to offering a more personalised service to every user; and does this incredibly well already.

As a post on digital 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.  

Although there can be some dangers to precise levels of tailoring, it is beneficial. In a world where habits shape 45% of the choices we make, behavioural research and predictive analytics are gold-dust for businesses.

Start-up businesses can be taking advantage of this too. 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. 

Where will Google take us?

Google has a side project titled Google Brain which launched in 2011. This is the world’s leading branch of AI and it is one that is constantly learning new things.

To understand further, scientists involved with this project have fed over ten million YouTube stills to the Brain. 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 an 81.7% accuracy in detecting human faces despite not being fed information that defined what one was.

Two years after the Google Brain’s launch, DeepMind were acquired to the network. 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.

Google has begun implementing parts of DeepMind and their 'deep learning project' into their ranking of search engine results. Where this kind of autonomous AI will lead remains to be seen.

The impact on businesses

You’ve probably figured out that most people use Google as their default search engine. 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.  

Using AI, search engines have been issuing out strikes to websites that have a poor mobile presence. 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?