Rich get richer: inequality in the like economy -- Bonnie Barrilleaux

Following metrics blindly can cause perverse incentives: situations in which our efforts to increase the metric cause unintended negative side-effects. At LinkedIn as we encouraged members to join conversations in the feed, we found ourselves in danger of creating a "rich get richer" economy in which the top few content creators got an increasing share of all attention and feedback on the platform. Highly skewed distribution of feedback occurs naturally in any system that distributes content virally, but that doesn’t mean it’s good for our creators. As a result, we took action to ensure that all creators have a fair chance to get attention and responses on their content. This example reminds us that metrics are just a tool for humans to use; it's our job to ensure that the metrics incentivize teams to create real value for users, and we must regularly evaluate whether the metrics are still effectively driving us in the direction we really want to go.

Skill Match Index -- Pan Wu

LinkedIn’s vision is to create economic opportunities for every member of the global workforce. The mission of our Data Science team is to transform the data from the world’s largest professional network into actionable products/insights. In this talk, we will share a story in one of our fast growing business lines -- LinkedIn Learning. When we are rapidly ramping new product features and contents on LinkedIn Learning for our professionals, we observe an interesting phenomenon: In learning, most professionals get the picture of “why” but unfortunately not “what”. They are swamped with colossal amount of courses and can be confused of the learning roadmap. Here’re some cases in point: 1) Professionals, that are making a career transition, are not equipped with the necessary skills for a new industry but don’t know which learning path to take; 2) Universities want to prime students for their first industry job yet syllabus can’t constantly adapt to the ever-changing industry trend; 3) Companies desire to keep a competitive workforce but fail to come up with a quantitative benchmark to gauge talents. To solve these conundrums, we have developed a Skill Match Index (SMI). SMI quantifies the degree to which members’ skills are calibrated to those required by jobs. The higher the SMI is, the more competitive a member (or a group of members) is for selected jobs. SMI also provides the list of skills where members need further improvement and actionable course recommendations to bridge the skill gap. Through SMI, we can set ready our members for better economic opportunities ahead.