Artificial Intelligence (AI) is the new buzzword, and we are constantly hearing or reading about Artificial Intelligence in the news, like the development of self-driving cars or driverless cars. Anyone interacting with a chatbot on any website is an AI tool. But did you ever wonder how exactly artificial intelligence in talent acquisition is used now-a-days? Before deep-diving into how AI plays a major role in the recruitment industry, let's learn about talent acquisition. Gartner defines Talent Acquisition is the process of identifying organizational staffing needs, recruiting qualified candidates, and selecting the candidates best suited for the available positions. The stakeholders include recruiters, HR managers, hiring managers, and top-level executives. The team's goal is to identify, acquire, assess, and hire candidates to fill open positions within the organization. For the majority of organizations, the talent acquisition team will be part of the HR team. In a few larger organizations, talent acquisition is a different team that collaborates with the HR team.

Elon Musk has demonstrated the Neuralink brain chip in a pig, a monkey and we could soon see preform in a human brain. The firm posted a new job listing for a clinical trial director, which says the right candidate will'work closely with some of the most innovative doctors and top engineers, as well as working with Neuralink's first Clinical Trial participants.' The position is based in Fremont, California and provides the candidate with commuter benefits, meals and'an opportunity to change the world.' It also indicates that the job will mean leading and building'the team responsible for enabling Neuralink's clinical research activities,' as well as adhering to regulations. Neuralink posted a new job listing, first spotted by Bloomberg, for a clinical trial director, which says the right candidate will'work closely with some of the most innovative doctors and top engineers, as well as working with Neuralink's first Clinical Trial participants Although the posting does not say when the trials will begin, Musk revealed last month that they are less than a year away - meaning human trials could start this year.

In today's competitive industry, it is extremely difficult for companies to find the right candidates. The hiring process has seen several changes in the last few years, enhancing the quality of recruitment. According to the Gartner 2019 Artificial Intelligence Survey, more than 30% of organizations around the world will use AI-based solutions in their HR function by 2022. Artificial Intelligence (AI) and Machine Learning (ML) have transformed the recruitment processes by increasing the efficiency and rate of productivity in organizations. Automation has resulted in new paradigms in the traditional format which has been accepted excessively by organizations globally.

Identifying the right talent pool for your organization begins with an extensive candidate search. Internal and external recruiters might be involved in screening the resumes for the vacant roles. Having said so, it seems that mapping the competency and scrolling the resumes for job matching is a never-ending task for the recruiters. Most of the time, prior experiences and '' gut feeling'' drive recruiters' decisions rather than logic. Needless to say, candidate sourcing is not an easy task as well.

However, a far more revolutionary concept has set its foot in the Modern World. Artificial Intelligence, despite being a novice concept, has initiated to change the paradigms of life. Small and mid-sized companies as well as startups and entrepreneurs are adopting AI to scale their business. Large scale corporate giants and startups both are investing in AI to gain a competitive edge in the market. If you're wondering how to integrate AI into your business model to make it efficient, just keep reading and we'll steer you to five ways you can use AI to scale your business.

I've been featured on many reputed publications and online magazines! AI has made headlines for the last few years and it's here to make an impact. But what does exactly that mean for HR professionals and recruiters? While adopting artificial intelligence has benefits of its own, the organizations that are the real head-turners are those that have integrated artificial intelligence in the very cores of their business. HR professionals said talent acquisition is one of the most important areas where AI will play a role over the next few years.

Machine learning is the subset of Artificial Intelligence or AI that has become the newest applied technology in most of the industries. With its ability to optimize and automate the hiring process, all sectors are welcoming it with open hands, including the recruitment sector. In fact, for the recruitment sector, machine learning technology has come out as a miraculous solution. The AI-powered tools and methodologies have made it easier to target the right people and find the best candidates for an opening. Additionally, machine learning methodologies can help screen hundreds and thousands of resumes in just a few minutes. But is machine learning only lucrative or does it have some negatives too? In this post, we will dig deeper into the functionalities and mechanics of machine learning in recruitment.

There is no denying that the current trend in business is implementing automation across the different sectors. It is beginning to impact all aspects of the business from eCommerce to the Human Resource (HR) department. A big part of automation is the use of artificial intelligence (AI) with the technology already showing up in many functions of HR. So how is artificial intelligence changing HR? The key thing to understand about the transformative power of artificial intelligence is its ability to analyze large data sets. This can help in decision-making in a wide variety of ways.

Applying Data Science in HR and extracting actionable data intelligence can not only help companies keep their employees happy and retain valuable talent but it can also help in reducing costs and driving revenues. Critical HR processes like recruiting, training & development, work performance analysis, employee dissatisfaction management, and retention management, etc, require everyday analysis to generate insights for proactive action. These activities consume a lot of time, resources and investments of the company. The time and investments made in hiring get wasted if the company doesn't pick the right candidate for the right job at the right time. When a company publishes a vacancy for a role, the applications are received from various sources in large numbers.

Powerful formalisms for abstract argumentation have been proposed, among them abstract dialectical frameworks (ADFs) that allow for a succinct and flexible specification of the relationship between arguments, and the GRAPPA framework which allows argumentation scenarios to be represented as arbitrary edge-labelled graphs. The complexity of ADFs and GRAPPA is located beyond NP and ranges up to the third level of the polynomial hierarchy. The combined complexity of Answer Set Programming (ASP) exactly matches this complexity when programs are restricted to predicates of bounded arity. In this paper, we exploit this coincidence and present novel efficient translations from ADFs and GRAPPA to ASP. More specifically, we provide reductions for the five main ADF semantics of admissible, complete, preferred, grounded, and stable interpretations, and exemplify how these reductions need to be adapted for GRAPPA for the admissible, complete and preferred semantics. Under consideration in Theory and Practice of Logic Programming (TPLP).