This week, we explore the need to scientifically study machine behavior. We learn how artificial intelligence can complement human interaction to deliver better customer communication and customer experiences. We examine the ways in which predictive analytics and artificial intelligence are stronger when used together. And we cover an incredible data sharing initiative lead by St. Jude in order to cure pediatric cancer.
Researchers: AI Behavior Should Be Studied
by Jessica Davis, contributor for InformationWeek.com
There are brilliant minds currently studying machine behavior—computer scientists, robotics experts, and engineers. However, while these scientists are experts, their focus is on tuning algorithmic performance, and not on behavior. It is for this reason that researchers are calling for a new scientific discipline called “Machine Behavior”. When it comes to AI, enterprise organizations and society as a whole are really just at the very beginning of exploring the value, potential, and greater overarching implications of these technologies.
Complementing Customer Expectations with AI
By Drew Sheahan for MarTechAdvisor.com
Artificial Intelligence is an incredible technology that can improve your communication with your customer base. But it shouldn’t replace human interaction. It should complement it. Leverage technology to cultivate human interaction by offering immediate communication options to your customers. Using AI in your business works when combined with other technologies to provide additional touch points for your customers. This allows for a customer-centric experience, allowing customers to communicate with you in many different ways.
7 Ways Predictive Analytics Can Improve Customer Experience
by John Edwards, contributor for CIO.com
AI-powered analytics can drive sales to higher levels by helping organizations anticipate customers’ needs and exceed their expectations. Predictive analytics gives companies a powerful, competitive edge. It allows you to use data in order to understand what might happen and prepare for a response ahead of time, rather than having to react after-the-fact. This can be done in so many useful ways in many aspects of your business. Learn seven ways to use predictive analytics to improve customer experience, along with examples, in this helpful article.
Better Together: Predictive Analytics and AI Boost Each Other
by Kathleen Walch, contributor for SearchEnterpriseAI.com
Companies in many industries are seeing the benefits of predictive analytics tools through machine learning models. They’re able to predict customer behavior, foresee equipment failure, improve forecasting, and more. Enterprises have long seen the value of predictive analytics, but now that AI is starting to influence forecasting tools, the benefits are starting to become even more compelling. They’re now finding that combining predictive analytics and AI can help them stay ahead of their competitors and provide the best experience possible to their customers. Learn how and read several examples of real-world applications in this article.
St. Jude Cloud: Sharing Data to Cure Cancer
by Jessica Davis, contributor for InformationWeek.com
It’s not surprising that there were major challenges associated with sharing terabytes of data with researchers in an effort to cure pediatric cancer. The Pediatric Genome Project gives access to all of the cancer research that St. Jude has done over many years to researchers. It is the largest public repository of pediatric cancer and genomics data. But there were challenges: the huge volume of data, the network bandwidth required, and the tools that researchers would require to gain an understanding of the data. With the help of Microsoft Azure and DNAnexus, they’ve enabled data discovery for outside researchers by offering data mining, analysis, and visualization tools, all accessible in the cloud via the web without the need for downloading data.
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