Microsoft says it wants to make it easier for organizations to use and build AI technology responsibly. During its "Put Responsible AI into Practice" digital event on Dec.7, the tech giant, with Boston Consulting Group, released 10 guidelines that product leaders can use to implement AI responsibly, without bias and with visibility into the intentions of AI and machine learning algorithms. Enterprises can use the guidelines before, during, and after of the process of building AI models. Microsoft outlines the guidelines in a three-step framework that starts with using transparent processes to assess and prepare the model and weigh potential risks and benefits. The next step is design, build, and document.

As AI becomes more deeply embedded in our everyday lives, it is incumbent upon all of us to be thoughtful and responsible in how we apply it to benefit people and society. A principled approach to responsible AI will be essential for every organization as this technology matures. As technical and product leaders look to adopt responsible AI practices and tools, there are several challenges including identifying the approach that is best suited to their organizations, products and market. Today, at our Azure event, Put Responsible AI into Practice, we are pleased to share new resources and tools to support customers on this journey, including guidelines for product leaders co-developed by Microsoft and Boston Consulting Group (BCG). While these guidelines are separate from Microsoft's own Responsible AI principles and processes, they are intended to provide guidance for responsible AI development through the product lifecycle.

Many organizations struggle with both identifying and prioritizing what sales leads to pursue. Where do you start when you have a large stack of leads to go through? What do you when your leads have gone cold? For Product Leaders, it's often a challenge to get a broad spectrum of feedback from their customers. How do they know where to focus next?

The Sisense analytics platform is known for its augmented analytics capabilities and ease of use, and as it moves forward it will do so with a new leader in charge of its product development. Just over a year after its acquisition of Periscope Data, a purchase that added capabilities aimed at data scientists to the features geared toward business users Sisense was already know for, the New York-based vendor is focused on third-generation analytics in which AI and business intelligence embedded throughout the workflow will be prominent. Most recently, Sisense updated its analytics platform with new natural language query capabilities and introduced Knowledge Graph, a graph analytics engine the vendor developed that was trained on more than 650 billion past analytic events and informs the machine learning capabilities of the query tool. Now, to help shape its vision, Sisense has added Ashley Kramer as its first chief product officer. Kramer began her career as a software engineering manager at NASA.

Everyone from chief executive officers to product managers to venture capitalists wants to understand machine learning better. They know it has the potential to take their software to the next level. They feel the excitement around it. They've read the TechCrunch or Fortune articles, and they've maybe even done a quick linear regression or two. But the primary issue that many product leaders grapple with when it comes to machine learning is that they want programs that don't just crunch the numbers, but can also think for them.

Some industries are quicker to adapt to technological advancement. The insurance industry may have a mixed record on how well it has used the Internet and various communications platforms but it does not appear to be hesitating on deploying tools that rely on Artificial Intelligence (AI). In fact, it almost looks like every significant player in the insurance industry is picking up efficiencies with AI; especially the providers involved in claims processing. The management of insurance claims is being improved mostly by product leaders within various companies, and their jobs are never simple. In virtually every field, a product leader is tasked with keeping an eye on tectonic shifts in markets and technology, finding resources to address those changes, and manage the day-to-day of the customer experience and engagement. Tracking the almost profound transformations underway in the insurance industry is difficult even for the experts.