Artificial Intelligence and business application

There’s no doubt about it, Artificial Intelligence (AI) is all around us, whether we register it’s presence consciously or subconsciously, we will interact with AI systems daily. From recommendations on what to buy next online, to virtual assistants in our phones or at home, to facial recognition in a photo, identifying spam in an inbox, or the detection of credit card fraud, it’s ever-present.

Did you know we’ve been talking AI about since the 1950s? Yep, the ‘Father of the Field’ John McCarthy described AI as "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it".

Since then, there have been numerous debates on whether something is ‘truly AI’ or not, due to this fairly broad definition. To give you some more context, AI systems will typically demonstrate some of the subsequent behaviours associated with human intelligence: planning, learning, reasoning, problem solving, knowledge, representation, perception, motion and manipulation, and to a secondary degree, social intelligence and creativity.

It’s whether or not a system can emulate these types of behaviours that will determine whether it’s ‘Narrow AI’ or ‘General AI’.

Narrow AI (also known as weak AI) is the only form of artificial intelligence that humanity has achieved so far. Simply put, narrow AI is an intelligent system that has been taught how to carry out specific tasks without being explicitly programmed to do so.

Language and speech recognition of virtual assistants, Google’s translation engine, the suggestion of products you may like (based off of previous purchases), sales predictions and weather forecasts; are all examples of the intelligence evident in narrow AI systems. The technology within self-driving cars is still considered a form of narrow AI, or more specifically a coordination of several narrow AIs.

In summary, narrow AI is good at routine jobs, both cognitive and physical, it’s even threatening to displace/replace human jobs, due to the fact it can identify patterns and correlations within data that would take considerably more time for humans to find. However, narrow AI operates within a limited context and cannot take on tasks beyond its field, so you cannot expect the same engine that transcripts audio and video files to order your favourite pizza for you - that’s a task for another AI.

General Intelligence, known as Artificial General Intelligence (AGI) is very different, it’s the type of adaptable intellect found in humans. AGI is a flexible form of intelligence that is capable of learning how to carry out vastly different tasks by understanding and reasoning its environment, just like a human would. AGI is elusive, it’s the type of intelligence we typically see in films like The Terminator and i-Robot, but which doesn’t exist today, and AI experts are fiercely divided over how soon it’ll become a reality.

Some AI experts believe that such predictions are extremely optimistic, given how little we understand of the human brain, they believe true AGI is centuries away.

You just need to look at how the human brain perceives things, juggles between multiple thoughts some related/ some unrelated, and often draws back on memories before making a final decision. This process of thought is very difficult for a computer to emulate.

It’s true, humans in most instances might not be able to process data as fast a computers, but they can think abstractly, generate ideas plan and problem-solve without precedence; all on a general level without going into the details. Just think about the invention of the telephone, email, social media, gaming, virtual reality and more - it’s very difficult to teach a computer to invent something that doesn’t exist yet.

Some experts, such as Google’s Peter Norvig and IBM’s Rob High believe we don’t and won’t even need human level AI.

So, by now you should have a good understanding of what AI is, the different types of AI, the daily ways in which AI is used around you and the potential future of AI. We will now explore the practical application of AI in business. Let’s start with some examples;

Ocado

Ocado have have created ‘the world’s first AI-based fraud detection system for online grocery purchases’. Their system identifies orders that are delivered but haven’t been paid for and determines whether it’s the result of malicious intent by analysing data from previous orders.

Ocado engineers have implemented a deep neural network using Google’s open sourced TensorFlow software library and uploaded the fraud detection system to a data lake in Google Cloud. Ocado claim that the system has significantly improved their precision of detecting fraud.

Ocado are also using a combination of TensorFlow machine learning tools and cloud APIs to support multiple internal AI projects. Including automating the management of the influx of customer service-related emails the supermarket receives.

Virgin Holidays

Virgin Holidays are using AI-powered software called Phrasee to automate and optimise the writing of their marketing email subject lines. By loading 3 years worth of email subject lines, email results and brand guidelines into Phrasee, the machine has learned and gathered digital insights as well as understood the brands tone of voice. Phrasee now feeds back optimised subject lines for the marketing teams to use in their email campaigns.

Since using this technique the AI-powered software has outperformed a human by up to 10% when it comes to email open rates, thus resulting in an addition of several million pounds in revenue.

The Zoological Society of London

The Zoological Society of London (ZSL) are utilising Google’s new Cloud AutoML platform to track wildlife by automatically analysing images captured by cameras in the wild.

The ZSL cleverly uses these cameras to capture the motion of animals and humans and identifies poaching threats. The imagery needs to be ‘tagged’ in order to analyse the data, which the ZSL conservationists have to do manually.

The ZSL supplied Google with around 1.5 million tagged images to help enhance the Cloud AutoML platform. The charity is now working with Google to create a complete auto-tagging tool by feeding it data on conservation details such as environment, region and species.

Tesco

Tesco is implementing machine-learning algorithms within its business, from driver routing for deliveries to the integration of Google’s home assistant device within their customer-facing app.

Tesco have also started to open up their APIs to create ‘recipes’ so online shoppers can start to personalise their shopping, receive price-drop alerts and order groceries through AI-powered home assistants.

EDF Energy

EDF Energy has been experimenting with AI to conduct character recognition to select and process the figures on meter readings sent in by energy customers. EDF will then use machine learning to carry out pattern recognition to identify trends in the usage data being gathered.

EDF are also investigating the use of AI for real-time condition monitoring to provide advice to power station operators. The AI would monitor various systems within the power station and provide real-time advice, advising on what they should do in the future and possible ways of automating the power station.

Our thoughts;

There is no doubt about it, AI is definitely an emerging and growing technology of the future. More and more companies will be looking at how they can introduce AI into their organisations to improve overall efficiencies and experiences, some will replace and some will displace human inputs and efforts, others will use AI to complement or further enhance human efforts.

For the time being chatbots seem to be the most often used form of AI within recruitment – they are being used to get that first engagement that takes recruiters a lot of time, we feel that most people know when they are being chat botted and we don’t like it! So for now, we are sticking with the old fashioned human approach.

What are your thoughts on AI? Is it something you’ve worked with before? Is it something you want to work with? Or is it something you’re not keen on at all? No matter your experience or thoughts, we’re very keen to hear from you, do leave your comments below.

#artificialintelligence #ai #technology #software #digital #digitaldevelopment #digitaltransformation #engineering #development #scienceandtechnology #productivity #cognitivescience #businessintelligence #data #bigdata #complexity #internetofthings #unitedkingdom #computersoftware #buckthetrend