It was such a tight labor market long with more open roles than there were people to fill them. And we've all seen how quickly that has changed with more than 40 million American workers being displaced over the last 13 weeks. We're seeing progressive HR teams using this time to build their candidate pipelines to make sure they are ready to staff up quickly when the time is right but can develop their teams with highly qualified, diverse candidates. Progressive HR teams are building their candidate pipelines to make sure they are ready to staff up ... [ ] quickly when the time is right and develop their teams with highly qualified, diverse candidates There is a strong need for automation and smart technology to help augment and support HR teams that are strapped for time and resources. As recruiters are engaging in discussions with active and passive candidates, tools like CareerBuilder's Talent Acquisition platform automate the entire recruiting funnel.

The World Economic Forum (WEF) is upon us this week, and the Future of Work is one of its key themes. This is a good opportunity to catch up on the trends unfolding in this domain right now, and to ponder on the insights of the people taking note and shaping this discussion. Automation and AI is part of this discussion as well, with the jury still out as to how exactly this will shape labor, workforce dynamics, and workplace transformation among others. Based on the WEF's latest report on the Future of Jobs, we highlight the major forces at play today. We discuss how these effect the technology behind the job market with Panos Alexopoulos, Head of Ontology at Textkernel, a Careerbuilder company.

CareerBuilder hopes to appeal to tech-happy job seekers with a new mobile app that uses both artificial intelligence and augmented reality to simplify job searches. The mobile app has some attention-grabbing features. It can build your resume, apply to jobs on your behalf, and show augmented reality views of job openings at the businesses you walk by. It also helps you develop the skills needed for a better-paying job. And for employees, the mobile app shows the real-time supply and demand trends for talent you need. It instantly builds your job descriptions, automatically matches your job openings to candidates who are more likely to respond, and runs campaigns to engage them.

The use of robotics and advanced analytics are apparent and mature in industrial settings, while in support functions such as HR, it has the potential to be just as revolutionary but the uptake has been a little slower. For example, in HR, onboarding – the process of hiring new members of staff and putting them to work following recruitment– generally takes around one month, according to recent research by CareerBuilder. The various processes – taking up references, verifying identities, carrying out health and safety assessments and ensuring hires have an understanding of company practices, policies and culture – requires a complex set of actions and toolsets which are not easy to automate. However, there's a lot to gain – as well as driving efficiency by cutting down time spent on mundane but vital processes and compliance, automating tasks like this will free up skilled workers to apply themselves more creatively. In fact, the potential up-sides mean that automation of support functions is an inevitability, as market forces drive businesses to strive for ever greater efficiency efficiency.

From artificial intelligence and automation to machine learning and semantic search, we've been inundated with the industry's hottest buzzwords, but what do these terms really mean for us in the talent acquisition space and for the future of our profession? These terms are far from passing fads. Nearly 3 in 4 employers expect that some roles within talent acquisition and human capital management will become completely automated within the next 10 years, according to a 2017 survey by my company, CareerBuilder. Our research also shows that artificial intelligence and automation will have a major impact on HR and employment over the next few years, as more than 1 in 10 HR managers are already seeing evidence of AI becoming a regular part of HR, while more than half say it will be within the next five years. This has been stoking unwarranted fear in our industry and beyond.

The use of robotics and advanced analytics are apparent and mature in industrial settings, while in support functions such as HR, it has the potential to be just as revolutionary but the uptake has been a little slower. For example, in HR, onboarding – the process of hiring new members of staff and putting them to work following recruitment– generally takes around one month, according to recent research by CareerBuilder. The various processes – taking up references, verifying identities, carrying out health and safety assessments and ensuring hires have an understanding of company practices, policies and culture – requires a complex set of actions and toolsets which are not easy to automate. However, there's a lot to gain – as well as driving efficiency by cutting down time spent on mundane but vital processes and compliance, automating tasks like this will free up skilled workers to apply themselves more creatively. In fact, the potential up-sides mean that automation of support functions is an inevitability, as market forces drive businesses to strive for ever greater efficiency efficiency.

Job openings often go unfulfilled despite a surfeit of unemployed or underemployed workers. One of the main reasons for this is a mismatch between the skills required by employers and the skills that workers possess. This mismatch, also known as the skills gap, can pose socioeconomic challenges for an economy. A first step in alleviating the skills gap is to accurately detect skills in human capital data such as resumes and job ads. Comprehensive and accurate detection of skills facilitates analysis of labor market dynamics. It also helps bridge the divide between supply and demand of labor by facilitating reskilling and workforce training programs. In this paper, we describe SKILL, a Named Entity Normalization (NEN) system for occupational skills. SKILL is composed of 1) A skills tagger which uses properties of semantic word vectors to recognize and normalize relevant skills, and 2) A skill entity sense disambiguation component which infers the correct meaning of an identified skill. We discuss the technical design and the synergy between data science and engineering that was required to transform the system from a research prototype to a production service that serves customers from across the organization. We also discuss establishing customer feedback loops, and it led to improvements to the system over time. SKILL is currently used by various internal teams at CareerBuilder for big data workforce analytics, semantic search, job matching, and recommendations.

US small and medium-sized companies running Google's G Suite will now be able to use machine learning technology to support their recruitment efforts. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered. You have exceeded the maximum character limit.

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BAE Systems is looking for a Machine Learning and Signal Processing Research Engineer to join their Cognitive RF research group. The cognitive RF group works on programs and problems that involve machine learning, optimization, detection & estimation, information theory, deep learning, and adaptive decision and control. These technologies are applied to a number of different RF domains, such as cognitive communications, radar, electronic warfare (EW), spectrum sensing, SIGINT, to name a few. The Cognitive RF research group is part of BAE Systems' Technology Solutions division which is heavily involved in advanced research concepts primarily from the various government research labs and organizations, including DARPA and IARPA. Members of the group are involved in the entire cycle of research development, from the initial concept ideation and program shaping with potential customers and new business pursuits through the execution and transition of research concepts to BAE Systems' business areas and products.