Organizations are increasingly looking to harness the power of artificial intelligence to manage talent in ways that are more effective, fair, and efficient. However, the use of AI in Human Resources raises given AI’s potential for problems in areas such as data privacy and bias. The use of AI in HR also poses operational, reputational, and legal risks to organizations, especially with recent moves in several countries to regulate its use. There is therefore high interest in AI in HR but also apprehension, and organizations are looking to navigate this increasingly complex landscape.
To help organizations overcome these challenges, the World Economic Forum collaborated with over 50 experts in HR, data science, employment law, and ethics to create a practical toolkit for the responsible use of AI in this field. The toolkit begins with a guide that provides: an overview of AI in HR including a short primer on how AI works; describes key areas of concern including data privacy, bias, and transparency and explainability; and covers the steps to adopting AI-based HR tools including forming an assessment team, evaluating the risk of a tool, implementation, and monitoring. The toolkit then provides two checklists that are linked to each section of the guide. The first checklist is for the evaluation of a specific tool. The second checklist focuses on broader questions of strategic planning and the development of policies and procedures.
This project was led by World Economic Forum Fellow Professor Matissa Hollister from McGill University, in collaboration with Fellows from Baker McKenzie and New America, and the Centre for the Fourth Industrial Revolution Turkey, an affiliate centre of the World Economic Forum established by the Turkish Employers’ Association of Metal Industries (MESS) and the Republic Of Turkey Ministry of Industry and Technology.
The White Paper provides an overview of the landscape of AI in HR. It begins by outlining what organizations are already doing with AI in HR and the challenges they are facing. It then presents the key lessons that emerged from the project, and then turns to the new issues that are on the horizon for AI in HR.
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