Problem solve

Problem solve

Get help with specific problems with your technologies, process and projects.

• Algorithmic bias top problem enterprises must tackle

  No enterprise today would roll out an obviously biased AI tool, but many remain unaware of the risks of unconscious bias in algorithms, which can produce equally dangerous results. Continue Reading

• The threats of AI must be taken seriously to prevent harm

  The risks of AI use are growing as the technology becomes more pervasive. Rather than laugh off the threats, businesses should move to mitigate them before they become headaches. Continue Reading

• Combination of blockchain and AI makes models more transparent

  Blockchain technology could play an important role in helping enterprises develop more explainable AI applications, something that is frequently lacking today. Continue Reading

• GDPR regulations put premium on transparent AI

  As the EU's GDPR regulations go into effect, enterprises must focus on building transparency in AI applications so that algorithms' decisions can be explained. Continue Reading

• Machine vision makes paper a thing of the past for insurers

  The insurance industry is buried in paper-based processes. Former MetLife CIO Gary Hoberman aims to change that with a platform that runs on AI and machine vision. Continue Reading

• Why machine learning models require a failover plan

  Flawed machine learning models lead to failures and user interruptions. Expert Judith Myerson explains the causes for failures and how a failover plan can improve user experience.Continue Reading