Dru Smith, Chief Geodesist of the National Geodetic Survey stands near a measurement device used to survey the height of the Washington Monument in 2017.Susan Walsh/AP This story was originally published by Wired and is reproduced here as part of the Climate Desk collaboration. Cuts made by the Trump administration are threatening the function of a tiny but crucial office within the National Oceanic and Atmospheric Administration that maintains the US framework of spatial information: latitudes, longitudes, vertical measurements like elevation, and even measurements of Earth's gravitational field. Staff losses at the National Geodetic Survey (NGS), the oldest scientific agency in the US, could further cripple its mission and activities, including a long-awaited project to update the accuracy of these measurements, former employees and experts say. As the world turns more and more toward operations that need precise coordinate systems like the ones NGS provides, the science that underpins this office's activities, these experts say, is becoming even more crucial. The work of NGS, says Tim Burch, the executive director of the National Society of Professional Surveyors, "is kind of like oxygen. You don't know you need it until it's not there."

Three of every four companies have reported talent or labor shortages and difficulty hiring–a 16-year high. Profound social, economic and demographic changes have created unmet demands for workers in industries ranging from hospitality to logistics to healthcare. Executives across sectors are struggling to attract and retain talent and it's likely that labor shortages will remain a critical issue for many organizations moving forward. However, the rapid advances in artificial intelligence (AI) have the potential to significantly disrupt labor markets. Leading organizations are using AI technologies to reduce the impact of labor shortages and improve their competitive position, while also saving on costs. Here's how they're putting AI and big data to use: Some say a non-supportive and unpleasant work environment is the reason their employees quit, creating labor shortages.

One of the more persistent consequences of the COVID crisis has been the so-called "Great Resignation," a development that has been unfolding over most of the past two years. We've seen a steady flow of employees leave the workforce, many doing so after taking stock of their lives amid a rapidly changing world. The insurance industry has by no means been immune to this. Companies in our industry rely heavily on the institutional knowledge of experienced employees, so as the pandemic has served as a catalyst for early retirements, these organizations have been especially hard hit. Employees are an organization's most valuable assets.

This article first appeared in IndustryWeek. As manufacturers begin to integrate AI solutions into production lines, data scarcity has emerged as a major challenge. Unlike consumer Internet companies, which have data from billions of users to train powerful AI models, collecting massive training sets in manufacturing is often not feasible. For example, in automotive manufacturing, where lean Six Sigma practices have been widely adopted, most OEMs and Tier One suppliers strive to have fewer than three to four defects per million parts. The rarity of these defects makes it challenging to have sufficient defect data to train visual inspection models. In a recent MAPI survey, 58% of research respondents reported that the most significant barrier to deployment of AI solutions pertained to a lack of data resources.

This country has something of a love/hate relationship with government jobs. We hate that most government workers are guaranteed overtime and coffee breaks when not working strictly 9-5. But then who wouldn't love being well paid, with early retirement and congressional-level benefits for such effort. Thus, for those of us in the private sector it might seem a bit of career karma that a recent federal study finds automation can eliminate five percent of all government jobs and 30 percent of the work the remaining employees do. I'd like now to offer the perspective I've gained over three decades helping build an industry-leading company designing the information technology systems now automating those government jobs and workloads.

Even after years of experience, senior underwriters can still spend a large part of their day doing the administrative tasks that they were taught early in their careers. AntWorks, a global artificial intelligence (AI) and intelligent automation company, can transform the way they spend their time. "All the rules and learning are completely discoverable, addressing concerns often held about AI and RPA technologies." "In your first weeks of work you may have been trained to recognise insurance slips and documents that brokers might present to you as an underwriter," said Mike Hobday, AntWorks' senior vice president for Europe. "You would be trained to understand the data you need to extract, to think about the standing of the broker and the nature of the risks. You might even make some calculations and underwrite the offered risk by entering data into the core systems of the business. "As a very senior and experienced underwriter, there might still be a large part of your day spent doing the administration you were taught in those earlier days.

Time is a critical context for understanding how things function. It serves as the digital history for businesses. When you think about institutional knowledge, that's not just bound up in people. Data is part of that knowledge base as well. So, when companies can capture, store and analyze that data in an effective way, it produces better results.