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Artificial Intelligence Will Humanize Work, Not Replace It

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Artificial Intelligence Will Humanize Work, Not Replace It

This piece was originally published on the Cornerstone Blog. Today we are inundated with articles, interviews and Tweets about artificial intelligence (AI) from people who aren’t aware of the technological reality. They simply shamelessly tap into an imaginary world of competition and submission in order to generate more and more emotion and clicks. As an AI expert, I wish to shed some light on what is involved in the development of these new tools, which may turn out to be more human than one might think. Because the reality is: what we call artificial intelligence is just a succession of specialised tools, each one dedicated to the optimisation of a single repetitive task. A classic example is medical imaging, where an algorithm will analyse hundreds of images for a specific cancer in order to propose a diagnosis to the doctor. AI is nothing more than what we decide to make it. A human technology that has the potential to relieve employees of daunting tasks... Above all, AI makes it possible to automate often repetitive, sometimes thankless, actions that were previously carried out by employees. We must put an end to the preconceived idea that we would put the majority of human activity in a company into the hands of machines. AI must be approached as a technological opportunity that frees up employees’ time and helps them to make decisions. ...and to bring value to employees and the company Employees will therefore be able to concentrate on other, more "human" tasks, where they will have more added value. On the one hand, they will be able to focus on their creativity, innovation and analysis; on the other hand, they will be able to devote themselves to human relationships and communication, whether internal or external. For example, a nurse will be able to spend more time with her patients. In this way, AI gives back meaning to work, an essential demand from younger generations. A phenomenon that will increase with the maturity of the technology Opaque in its operation, AI is a tool that requires interaction in certain aspects similar to that between humans. The solutions known to the general public are still far off from maturity. Indeed, the main goal of GAFA (Google, Apple, Facebook and Amazon) is to keep users captive by not providing them with steering tools or justification. However, it is necessary to ensure that humans and AI understand each other on both the questions and the answers! Collaboration with humans is a crucial issue for enterprise solutions, the progress of which will positively affect the reality of work. Let’s not be naïve, job losses caused by AI will occur. But the reality will be far from the predictions of some think tanks or theorists announcing the elimination of 30% to 90% of current jobs. Humans are far from having lost their place in business. With the development of AI solutions at work, employees will turn to more rewarding activities and goals for more fulfilling careers. To learn more about why an employee-centric approach to advancing AI in the workplace matters, download our whitepaper: Realizing the True Potential of AI in HR.

Close Your Eyes and Dream Big! What AI Can Bring to HR

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Close Your Eyes and Dream Big! What AI Can Bring to HR

Artificial intelligence (AI) in HR remains a mystery to many of us. The application of AI technology in other scenarios is more straight-forward because the goal of AI is clear. For example, AI is used in autonomous vehicles, constantly learning and adjusting to navigate the road better. AI in HR is more complex because its data are very specific and every organization is unique, going through constant change. HR AI is Tricky and Can’t Be Too Scientific As a Data Scientist, I find HR to be one of the most challenging fields in AI for many reasons. One of the main reasons is that HR data is mostly composed of "natural language," which is prone to interpretation—a difficult task for computers because of localization, synonym and homonym issues. On top of that, HR data is subjective: people describe themselves and their team members differently based on their own agenda and framework. The language used will differ from person to person, manager to manager. In contrast, data in the legal domain is also natural language, however meant to be clear and objective. HR concepts themselves are quite blurry. Calling myself a "data scientist" is using a label which is far from giving a clear view of what I’m doing. Using skills to understand a person’s role is a far more precise way of getting accurate data, but even skills must be interpreted with care. For example, two people with "intercultural management" skills could have opposite views of what it means and what the resulting actions are. In addition, applying science to human behaviors is hard. The human mind is infinitely more complex than any transport route optimization or hotel pricing strategy. We will never have enough data to really understand humans. Let’s be clear, HR AI can’t be too scientific. A common saying in the AI community is that AI is usually beaten by a human expert. It's especially true in HR, automating entire HR processes is unrealistic. However, It Can Lead to Ground-Breaking Features in Human Resource Information Systems From my experience, AI in HR is not intended to make the decisions for the HR teams, as it is too complex. Instead, AI can bring an understanding to some HR concepts (skills, jobs, resumes, profiles, careers, departments, learning and development) and their relationships (skills on a CV and the level of mastery, skills by roles, links between learning and career paths, careers in certain departments). This understanding will allow software to have an automatic level of understanding on every data point available across the whole company and: Improve the search/browsing to display appropriate content Add recommendation for the different HR use cases Better represent the data despite its complexity The opportunity differs for each user, so let’s look into the details and find out how it could impact employees, HR and candidates: Employees: AI can help users to find the right objects (jobs, mentor, learning, career advice, development path). It can also allow users to express themselves in their own language (e.g. not to choose skills from closed nested lists). Thanks to this, employees will naturally update their data regularly and this data will open new many use cases, such as transversal teams composed based on skills. HR teams: Beyond having more autonomous employees, AI can optimize certain processes by accelerating access to the right data (finding who can do x in BU y, who are the best candidates for z?). It can also help to reduce the need for administration as there is less custom framework to maintain. AI can improve analytics and open the door to the "real" Strategic Workforce Planning: What is the company current situation, what are our business needs, what trainings are useful or not, what action should I take to reduce my skill gap? It also opens the door to advanced analytics in order to respond with data to the company's strategic issues (transformation, new acquisition, downsizing, etc). Candidates: Thanks to AI, candidates will give more information to the company in less time, for example what they can and want to do. But it is also true in the other direction; candidates will know what is missing from their skillset to get the job they want. Also it can surface other opportunities: For example, with your profile, you would be among the 10% of the best candidates for our job x, would you be interested? We could also imagine giving a candidate more visibility on a future career in a company, based on examples of similar profiles in the past (and why not have a chat with such employees)? These are just some of the examples that I have had the chance to work on. Most of the future possibilities of AI are still to be defined. Overall, the HR challenge in the field of AI masks amazing potential. Contrary to traditional sectors where many scientific approaches are already present and quite usual (for example, nobody expected data science to apply statistics to hotel prices), HR is discovering the potential of their data and the use cases that can be made of it. This is a real leap forward for HR, and we can expect the HRIS to be completely redesigned in the near future. As part of our commitment to innovation we are working very hard from the Paris-based Innovation Lab to make AI more and more relevant to our clients. We have created an eBook you can download here about "Realising the True Potential of AI in HR." Hungry for more AI blogs? Read my opinion about how AI will humanize the workplace and not replace it.

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