Bias is everywhere -- even in analytics. The best way to control for bias is to incorporate a diversity of experiences and perspectives in the teams we use to design and maintain predictive, machine learning, and AI systems.
Predictive analytics, machine learning, automated decision rules, AI, and other security analytics technologies have transformed how we handle malicious hacking activity. Are they adequate?
As AI matures, be on the lookout for AI service platforms, including some that will be able to develop a strategy on the fly for specific problems.
- By Brian J. Dooley
- June 29, 2017
These five competencies are required to build a successful predictive model.
- By Fern Halper
- June 26, 2017
New info about data science salary trends, data quality and skill shortages are still a problem, and the impact of bad data on training algorithms.
- By Lindsay Stares
- June 22, 2017
We are headed toward a future populated with AI and machine learning, where machines take on more of the work people have traditionally done. What does that mean for the business analytics professional?
- By William McKnight
- June 20, 2017
The prospect of chief machine learning officers, the future trends affecting data integration and cloud computing, and the problems with storing all data indiscriminately.
- By Lindsay Stares
- June 15, 2017
MBA programs adding data science classes, Google fights spam with machine learning, and the pros and cons of using machine learning in hiring decisions.
- By Lindsay Stares
- June 6, 2017