The Value of Explainability in Artificial IntelligenceAI applications are finding a role in many business processes. Machine learning algorithms add speed, precision and automation to enable companies to drive improved
As a CMO, who has been supporting CMO’s for 25 years with hundreds of analytic and data driven marketing campaigns across multiple industries, I am all too familiar with the latency inherent in the CRM campaign process of large enterprises.
Predictive analytics plays an important role in the banking industry when it comes to fraud prevention, risk assessment, and more. Discover how explainable AI can enhance the functions predictive analytics serves in banking.
Facebook recently announced that it will no longer support 3rd Party Data Partner Categories or enable advertisers to create campaigns against custom audiences in their platform due to privacy regulations.
According to CIO Magazine, May 2nd, 2018, major brands are intensely searching for explainable AI solutions for several reasons spanning guarding against ethical and regulatory breaches to understanding when to override machine based decisions or how to improve them in the future.
In Cognilytica Research’s briefing note on simMachines, January, 2018, it highlights the black box challenge of today’s AI machine learning technologies and the fundamental problems lack of explainability causes.
Similarity is a machine learning method that uses a nearest neighbor approach to identify the similarity of two or more objects to each other based on algorithmic distance functions.
It’s well known that the “Amazon effect” is wreaking havoc on retailers’ ability to lure and retain shoppers because of their inability to predict what motivates customers to buy and to be relevant in the moment of interaction.
Marketers are missing opportunities when they use static segmentation, which is not predictive of customer behavior and fails to take customer context into account.
Most marketers are just beginning to explore machine learning applications. Machine learning is already providing tremendous analytic efficiency gains and increased precision.