Over the course of the recent decade, tremendous progress has been made in the areas of machine learning and natural language processing, which opened up vast areas of potential application use cases, including hiring and human resource management. We review the use cases for text analytics in the realm of human resources/personnel management, including actually realized as well as potential but not yet implemented ones, and we analyze the opportunities and risks of these.

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Anand is the CEO & Product Owner at Amoeboids. The overnight changes the pandemic brought to work life over two years ago would have been a lot more difficult if not for digital tools. Employees appear to agree; according to an Oracle and Workplace Intelligence report, 82% of employees surveyed believed AI can support their careers better than humans, and a whopping 85% wanted technology to help define their future. But what is HR's role in this? Using people analytics in HR functions can bring about positive change--but only if employers cultivate the right approach for their organization.

Recently, Harvard Business Review (HBR) published an article on people analytics titled "Are People Analytics Dehumanizing Your Employees?" In the article, the authors provide a bleak and one-dimensional view of people analytics that, if not seen in context, will damage the field and dilute the current and potential contribution that people analytics can make to HR. In this article, we want to debunk the four things we believe HBR got wrong about people analytics. These misconceptions are dangerous to the field. They could set back much of the progress we have made in Human Resource Management over the past decade.

People analytics, the application of scientific and statistical methods to behavioral data, traces its origins to Frederick Winslow Taylor's classic The Principles of Scientific Management in 1911, which sought to apply engineering methods to the management of people. But it wasn't until a century later -- after advances in computer power, statistical methods, and especially artificial intelligence (AI) -- that the field truly exploded in power, depth, and widespread application, especially, but not only, in Human Resources (HR) management. By automating the collection and analysis of large datasets, AI and other analytics tools offer the promise of improving every phase of the HR pipeline, from recruitment and compensation to promotion, training, and evaluation. Now, algorithms are being used to help managers measure productivity and make important decisions in hiring, compensation, promotion, and training opportunities -- all of which may be life-changing for employees. Firms are using this technology to identify and close pay gaps across gender, race, or other important demographic categories.

I'll be honest with you – artificial intelligence (AI) is complicated, and when people talk about AI in HR, they often gloss over that fact. There are tons of specific terms associated with it, processes that go along with it like machine learning, and technologies designed to use it. It's hard enough for data scientists to keep it all straight, let alone an HR professional with a ton of other competing priorities. I'm sure leading with that did absolutely nothing to calm your anxieties around this topic, but as usual I promise I'll turn this around into something good. In that spirit, let me revise my first statement a little – AI is complicated, but it doesn't have to be complicated for you.

Artificial intelligence (AI) in the HR world refers to technology used to do a task that requires some level of intelligence to accomplish, mainly to help humans do mundane tasks. AI is different from any ordinary software as it requires three core components to operate, namely high-speed computation, a huge amount of quality data, and advanced algorithms. Core AI technologies provide better accuracy and stability to everyday processes using an algorithm that connects quality data with fast computation services. AI technologies offer significant opportunities to improve HR functions, such as self-service transactions, recruiting and talent acquisition, payroll, reporting, access policies and procedures. HR experts have faith that merging AI into HR administration functions will benefit and improve the overall employee experience. This will provide more capacity, time and budget, and accurate information for decisive people management. Smart HR people  For years, organisations have been collecting data to gain insights to predict future behaviour. HR teams have a lot of catching up to do in leveraging these people analytics — what data to track, analyse, manage and protect. AI will play a larger role within HR to support smart people analytics in innovative ways to attract top talent. Technologies that enhance the candidate experience and meet expectations will help distinguish an organisation from all the others. In addition, a stronger digital IQ will bring a business deeper into what is referred to as an “unconscious level” of information.  HR performance and succession data provide information on which employees are engaged and challenged. That gives a new dimension to strategic workforce planning to reduce employee attrition. It is a helpful tool to find the right mix of man and machine in the workplace, which skills and talents are key to maintain balance, and the best-fit candidates for the internal or external hiring process.  See also: Workplace Security: Obstacle of Multi-Factor Authentication Barriers to adopting AI technologies  AI helps efficiently automate many back-office functions for reliable HR transactions and service delivery. This document is focused on conversational AI capabilities for HR transactions and provides insight about intelligent automation via the technology-agnostic chatbot. Beyond the novel benefits of AI, we show how this innovative technology can be the best way to integrate and automate HR transactions in a robust manner. Nonetheless, the cost of using AI might be a barrier for businesses, especially small-to-medium businesses to compete in the fierce marketplace. Financial barriers can be blamed for the lack of wider implementation of AI tools to assist in administrative tasks, said a survey. Thus, when senior leaders do not see the value in using AI for human resources functions, it can be hard to justify the cost. Privacy and security risks posed by AI  Although cybersecurity has traditionally been seen as part of IT tasks, HR data privacy poses a number of challenges for AI development in the workplace. With increasing cyber-related incidents, cybersecurity has moved from the tech silo to wider business frontlines, especially HR as a business front door.  Employee data protection awareness is important, and appropriate governance guidelines need to be set up while dealing with AI. Such guidelines should address not only the overall technical and data inputting processes but also a number of legal and ethical issues. Organisations must get proper consent to avoid additional issues due to the complexities of AI and the training data involved. In some instances, the following tips might be applicable:  Provide a privacy notice to employees explaining why their data needs to be used for the AI solution to facilitate desired results. IT security departments should have policies in place to make it clear to employees what data is permissible and not permissible to collect for the AI solution.The chatbot solution should not store any personal identifiable information (PII) or confidential information during the processing of an employee request. PII and confidential information should be communicated via a secure internet or intranet protocol.Training data should be secure for machine-learning purposes and should not have any HR PII and confidential information.There is potential for a lot of PII information to be collected. Machine-learning solutions should have masking capabilities so that observers can’t learn specifics about other users.HR systems should only release authorized information to employees during conversational AI transactions. Companies need to make sure they have appropriate controls in place around HR data. If they don’t, then the output delivered by the algorithm will be flawed and lead down a path of wrong decisions. Read also: Job Security, Salary and Work-life Balance Top Priority for Workers in Singapore

We see the growth of people analytics at first-hand at Insight222, where we are now working with over 60 global organisations to help them put people analytics at the centre of business. In tandem we have also created a digital learning academy with myHRfuture to upskill HR in digital and analytics. For the last six years I have collated and published a collection of the'best' articles of the preceding 12 months – see 2014, 2015, 2016 2017 and 2018, and following are my choices for the 50 best articles of 2019. Those who have read the previous annual collections may note that the number of articles that make the cut has steadily risen. This is partly down to my inability to prune down to 30 or 20 - although it was hard enough to get it down to 50! Mainly though this recognises the increased number, variety and quality of people analytics and data-driven HR material now being published, which is another indicator of progress in the field. I hope that the articles selected will act as a venerable resource library for those working, researching or interested in the people analytics space. That is certainly the intention. I have arranged the 50 articles into twelve topics: i) Driving business value, ii) the future of work, iii) the future of the HR function, iv) ethics and trust, v) employee experience, vi) strategic workforce planning, vii) ONA, viii) diversity and inclusion, ix) organisational culture, perspectives and case studies from people analytics leaders, x) retention, xi) assessment and xii) getting started, as well as highlighting a few of my own articles from 2019 at the end. I hope you enjoy the articles selected, and if you do, please subscribe to my weekly Digital HR Leaders newsletter. Ultimately, people analytics should be about creating value – for leaders, for managers and for the workforce. So, where better to start than with seven articles that collectively provide insights on how to create value and/or give examples of where organisations have created value from people analytics.

AI is omnipresent becoming the norm in many facets of our everyday lives. Several businesses today have leveraged the capabilities of artificial intelligence. The moment is now -- where do you place yourself in the AI era today? Why does human resource matter more than ever in this age of artificial intelligence? It is but ironic to experience the way AI is transforming human resources -- HR professionals and HR leaders.

As much as many companies seemingly view their Human Resource department as an obligatory expenditure, the fact of the matter is that good HR management is a significant determinant of the long-run success or failure of the organisation. When properly utilised, a modern Human Resource department can add substantial value to its company by recruiting only the most qualified candidates and retaining them once they've been hired. While the basic objectives of HR like talent acquisition, retention, optimising productivity, and securing employee welfare, remain unchanged, the tactics employed have evolved considerably over the last few years especially given the rapid advancements in technology. Technology has advanced to the point where it's not merely shaping how the workforce operates, but what constitutes the workforce itself. HR is being pushed into a much larger role which entails helping their respective organisations go digital.