AI – are we looking at the future, or should I say immediate future? Part 1

How many of you read the words ‘artificial intelligence’ and immediately pictured robots? It’s okay, I do the same and it is hard to break the habit. What happens when we do have robots working with us, along with self-driving cars and completely human-less warehouses? After AI, what will be the next phase of technology we all picture in our heads?

cranberry panda had the pleasure of attending the Big Data Week London Conference last week and it was a pleasant surprise to learn so much and to leave with numerous new questions.

The Big Data Week is a worldwide initiative to bring together analytical communities and focus on the political, social and technological impacts of data in multiple industry settings. The event is hosted across major city hubs including Europe, the Americas, Australia and Pacific Asia.

Our focus for the day gave us a chance to be exposed to innovative ideas, showcasing the best practices from leading data and AI professionals to increase productivity. Looking at the growth of trends and new technology, solving analytical issues and working towards an efficient process of marketing.

The first speaker of the day was David Hulme, CEO of Satalia – a company that provides and works on AI inspired solutions to solve the industry’s most challenging problems. Having never heard of David Hulme before attending this event, (put down the pitch forks analysts, I am new to the game!) I was immensely impressed not only by his credentials and achievements but his empowering speech and obvious passion for what he believes in. Any presentations that starts with ‘My aim for the world’, you know will be a good talk!

Now down to business, for those who are experienced in the data analytics and AI world, you will have various views regarding the following opinions and information, which is amazing and very much encouraged. For the newbies out there, this will give you an insight into the real discussions that are going on daily worldwide, regarding the future of business and how it is run. As consumers that will affect us immensely, down to our shopping habits and what is available to us.

The extent at which we accept AI and data into our everyday business, depends entirely on the industry and the knowledge at which our employees have. There is an increasingly large gap in what companies want to do with data and AI, compared to the expertise of what professionals can deliver. Universities are opening data science departments, especially in the US, so students leave capable of being at the top of their profession. Unfortunately, that means those who are out in the professional world are inevitably playing catch up in an evolving industry.

To put it simply, ‘Demand is outgrowing the supply’ … now, when have we not heard that before!

To break it back down to basics, data is giving fabric to our universe; it fills the gaps in what we see between sales reports, trending patterns and customer/competitive behaviour.

Apart from taking over the world and killing all the humans, (just kidding) AI is very talented at predictive data. AI can analyse and predict producing results at a much faster rate than humans could. Remember an AI system does not need to eat, sleep, feel emotion or go home at the end of the day. It is critically important to bridge the gap between human and AI, with humans providing the data and deciding on what results are required, to AI collating and analysing all that is provided.

Let’s be honest, humans are terrible at making decisions. Do not roll your eyes at me, you know this is true! We allow so many factors to influence how we feel and think daily, it is no wonder you walk past people day dreaming, lost in their trail of thought or just asleep.

“Thinking, Fast and Slow” is a brilliant read for those who want to prove otherwise, and it explains how humans have 2 brains – a slow brain and a fast brain. Humans cannot deal with more than 7 decisions at one time. If you give a human 7 questions, their brain will automatically assess and answer the least challenging. We do not really help our reputation do we.

AI is superb at handling large scale quantities of data and it assesses this at a rate that would take humans hundreds of years.

Machine learning is positively revolutionary! It is helping us take lots of data and find the patterns we might miss as humans. Data Analyst’s agree that over the coming decade we will see a renaissance of these skills in predictive analytics, prescriptive analytics and data engineering.

Now, I am not slating humans but, we have the annoying habit of doing the same thing repeatedly and expecting the same answer. It is probably obvious that AI will do certain tasks much better than humans ever could, it would be naïve of us to think otherwise.

I understand it is wrong to bench mark AI against humans because it would be an unfair competition, and both have their strengths that the other could not comprehend on mastering.

Make sure to read part 2 of this blog!