One of the major trends I have been researching recently, has been the shift in interest towards Artificial Intelligence (AI) in its multiple forms and guises, and the potential it has to analyse vast quantities of data and quickly derive actionable insights. As we all know, AI, Machine Learning and Deep Learning are not new. However, there has been huge investment in the space in recent years and the ability to automatically apply complex mathematical calculations to Big Data – over and over, faster and faster – is a recent development. With steady advances in digitisation and cheap computing power, no wonder people are excited about the possibilities.
One of the areas of AI that gets the most attention is Deep Learning. Researchers have been attempting to train algorithms since the 1970s but limitations, be that computational or data related, slowed that progress. Whilst the algorithms we use today were, for the most part, created decades ago, we were unable to use them effectively. It wasn’t until new technology became available, that they could be applied to massive amounts of data, cheaply and quickly enough that they had the chance to live up to their full potential and help Big Data live up to its promise.
One area which will be interesting to observe is the relationship between Data Scientists and AI. As AI and Machine Learning progresses and evolves, some of the more basic and straightforward tasks that Data Scientists perform routinely will become automated and will yield great results in productivity. AI is certainly not going to replace Data Scientists any time soon, and can in fact be a massively helpful tool to utilise, however how will they view it: Friend or Foe? Could this also be one of the many ways that the industry can combat the talent deficit, automating the more basic tasks and reserving the more complicated Data Science processes for the Data Scientists?
Today, AI enables computers to communicate with humans, autonomously drive cars, write and publish sport match reports, beat them at board games and find terrorist suspects. The possibilities are endless and will no doubt change the ways in which we will live our lives in the future. Not only does AI present new possibilities in our day to day lives but also within wider reaching areas such as national cyber security, and special projects to combat human trafficking and arms dealings such as the collaboration between NASA and DARPA . When speaking with an expert recently, we were discussing one algorithm which predicts the likelihood of a criminal reoffending and the ways in which this was being used in a courtroom setting to help judges determine a sentence and future parole opportunities. There are also huge opportunities within healthcare, and with recent technological advancements, in some instances, we are able to predict whether an individual will develop a certain disease before they even show any symptoms, just by analysing different aspects of their lives. The possibilities for this technology are endless, and whilst for some this is truly exciting, for others, it is a step too close towards a Minority Report, iRobot, 2001: A Space Odyssey type future.
No matter what your philosophical view of our future, increasingly, the focus on AI/Machine Learning in analytics corresponds to the next logical step, which is gaining advanced insights from Big Data.
No matter what your philosophical view of our future, increasingly, the focus on AI/Machine Learning in analytics corresponds to the next logical step, which is gaining advanced insights from Big Data, the ability to accurately predict outcomes, improve productivity, and gain competitive advantage. Whilst it’s taken a few years to build the right infrastructure to store and process massive amounts of data, this was just the first step. Now, AI/Machine Learning is driving us forward and the combination of Big Data and AI will present incredible opportunities and drive innovation across almost all industries.
AI, Machine Learning and more will be discussed at the Chief Analytics Officer Forum, Fall on October 5-7 in New York. Join us on October 5 for our dedicated Pre-Conference Focus day Machine Learning, Deep Learning and AI for Strategic Innovation and hear about the ways in which leading companies are using AI in innovative ways within their companies. For more information, visit www.chiefanalyticsofficerforum.com
By Vicky Matthews: