Only You Can Prevent AI Failures; The Critical Role of Business Analysts in Delivering Machine Learning and AI
Thursday, November 14, 2019
Great Hall 4 & 5
Predictive Analytics, Machine Learning and Artificial Intelligence are hot topics everywhere you go. Every organization wants to turn its digital data into gold. Data scientists are being hired, software is being purchased, clouds are being provisioned. Lots, and lots, of money is being spent to move to a new era of algorithmic, data-driven business!
And yet… not much is actually happening. Most data science projects are still experiments, trials or pilots – some have become shelfware. Outside of big-name internet firms, demonstrated success at scale is remarkably hard to find. Most companies make decisions the same way. Data science is over-promising and under-delivering.
The problem is that data scientists don’t know how to talk to business people or IT professionals. They can talk to the data just fine. They can’t talk to the business to find out what problems need to be solved. They can’t talk to IT to get their algorithms across the last mile of operational adoption.
They can’t talk to the business or to IT – but you can.
- Why decisions matter to ML and AI – and you
- Business rules AND machine learning not business rules OR machine learning
- Why and how to define decision requirements