What is AI, where did it come from and what does it mean now?

“Artificial Intelligence, or AI, is one of the biggest buzzwords of the modern era, seemingly used to help sell every product or solution on the market while simultaneously being used as the ‘supreme’ villain in most modern sci-fi movies. It can both help transform how we interact and engage with the world i.e. via self-driving cars or allowing students to virtually engage with their college or university via chat bot as easily as they talk to their friends.

AI can also intelligently analyse data to support councils deliver better more meaningful citizen services or assist the NHS to spot patterns in patients to pre-emptively diagnose potentially lethal diseases. Yet AI is also one of the most misunderstood applications and therefore an ‘unknown’ for many organisations. In this blog series I hope to address some of these misunderstandings while hopefully providing additional insights into what AI actually is and how it can be used as a force for good.

To understand what something is, I think it’s often best to go back to where the phrase or modern definition comes from. In my opinion this dates back to McCarthy and Minsky and the famous Dartmouth Conference in the Summer of 1956. AI back then was described as any task performed by a program or a machine where, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task.

As this is quite a broad definition of AI, we have developed two definitions for what AI is: Narrow AI and General AI. Narrow AI is intelligent systems that have been taught how to carry out specific tasks without explicitly being programmed to do so. General AI is very different, and much more powerful – it’s a flexible form of intelligence capable of learning how to carry out vastly different tasks on a wide variety of topics, based upon its accumulated experience in different fields. This General AI is what’s often shown in movies i.e. Skynet from the Terminator franchise. Unfortunately (or maybe fortunately, depending on your point of view), this type of AI is a long way away and modern estimates place the time that this will be developed from between 2040 to 2090.

I’ll talk further about how AI actually works and flips the computer programming paradigm on its head in a future blog, but what I’d like to touch on is how this Narrow AI that we have currently can help organisations achieve their objectives. We’ll also look at where to start and how to do so in way which avoids being overwhelmed. AI can help in numerous ways, but the use cases that I see most often focus on two key areas – either transforming the way an organisation’s customers (i.e. students, citizens, patients) interact with that organisation, or transforming the way that data is used and insights developed within that organisation.

Take for instance changing the way people engage with the organisation – we’re all used to the likes of Siri, Alexa and Cortana, but more and more public sector organisations are embracing bots as a way of communicating with their customers. This is a great way of allowing your citizens or students to access data without causing an increased workload for your employees and is also a way of making static forms that often need filling in much more engaging by having the questions answered and interpreted much more organically. Think how tedious the process can be to fill in a 10 or 20 question form vs how easy it is to fill out whilst having a conversation with a person or, in this case, a bot.

When using a bot as an entry point or first point of call for your customers to engage with your organisation you can actually start to a) develop insights into patterns of behaviour within your citizens or students so you can direct resources or develop those areas accordingly and b) start to apply some of the cool things AI can do such as sentiment analysis. By applying this to a bot, your bot can learn how to understand and gauge the emotional state of the individuals conversing with it, this means that your valuable and skilled human resources can be brought in when it begins to suspect that the person may be suffering mentally or getting frustrated with the process. Rather than burdening your employees with a vast number of enquiries they can instead focus on the engagements that have the biggest benefits and most preferential outcomes.

You can also begin to not just improve the engagement process but also to look at automating some of the simpler processes using tools such as power automate or power shell scripts. For instance, if you’re engaging with students – tasks, such as resetting passwords, can all be automated so that your in-house team are freed up to focus on tasks which will drive better business benefits.

This blog has hopefully helped as an introduction to AI and in later blogs we will go on to talk through how it’s designed and also look at each of the elements and use cases in more detail.

If you’d like to find out more about where to start in your AI journey or would like to talk through what’s possible and how these technologies can be applied to your organisation to drive the outcomes which are important to you, please contact [email protected] or call 01904 562200.”

Ben Gannon – Data and Ai Specialist, Phoenix Software