BY SAMEER RAHMAN, ANALYSIS DIRECTOR.
In the field of data and analytics, the rise of Artificial Intelligence and Machine Learning is nothing short of a revolution.
When it comes to analysing data, its speed, accuracy, processing power and pattern recognition capability is something that excites me and my team immensely.
Undoubtedly, AI is fundamentally going to change the way we do things.
But, what really excites me isn’t the technical and analytic abilities, but how AI will unlock our human intelligence and creativity, removing mundane tasks to allow Data Scientists to focus on the stuff that really matters.
The job specification of a data scientist is about to change. No longer will we just churn through data to make sense of it. Machine learning will allow us to become innovation agents – drivers of business change.
Machine learning will help us to reallocate time and resource towards tasks that require thought.
As I always say to my team, ‘You get paid to think, not just to do’. Now they will genuinely have time to think.
For example, we no longer have to worry about the best statistical methodology or testing one against another - machine learning does this automatically.
In fact, most machine learning tools have a leader board based on outcome and suggest blended techniques which increase predictive accuracy. If you’re a data scientist, this is a huge monkey off your back, releasing your time to think about tasks that can make a real difference.
The time savings help us concentrate more on the input and the output.
Input, in terms of better understanding and formatting of the data (‘Feature Scaling’ in statistical terms) and the macro and micro factors impacting the business.
Output, in terms of focusing on how best to use the results - in essence, the stuff that matters and makes a difference on the ground.
This is revolutionary because it will allow data scientists to come out of the realm of statistics and bring them closer to the business, pushing them to think along commercial lines and concentrate more on the deployment of solutions to ensure maximum ROI.
They will be pushed to understand more about the context of the work they are doing and the complex consumer behavior which lies at the heart of it.
My advice to anyone setting up Data Science and Machine Leaning teams is to let machine learning do what it does best, churning, processing and analysing piles of data. Free your people up to do what humans do best - innovating and suggesting actions from insight.
Successful data science teams let machines do the routine, cognitive tasks and use the human brain to infer, reason, solve and truly add value.
Some have termed this as new concept of ‘Hybrid Intelligence’, human intelligence complemented by the speed, accessibility and accuracy of technology. Whether you like the term or not, the principle works for me.
Human judgment and intelligence will always be at the center of successful data analysis. It will be the stand-out trait that separates the winners from the also-rans in the new age of data.
Get ready for your data scientists to become agents of change.