This chapter explores the historical, legal, and regulatory landscape of employment testing bias and fairness in Canada. Canada’s history of colonization and immigration has resulted in a multicultural society. In 1984, the landmark Abella Report, and the subsequent Employment Equity Act, established key protections for historically disadvantaged groups, shaping modern employment practices. The chapter discusses the jurisdictional complexities of employment law, detailing federal and provincial regulations that prohibit discrimination based on race, sex/gender, disability, and other characteristics. Legal frameworks (e.g., the Canadian Charter of Rights and Freedoms, the Canadian Human Rights Act, and the Employment Equity Act) define bias and fairness in employment testing. Key court case decisions illustrate legal principles guiding test validity and adverse impact. We also examine professional guidelines, burden of proof requirements, regulatory oversight, and emerging challenges such as AI-driven assessments and balancing validity with diversity. The legal landscape continues to evolve, with growing emphasis on fairness, transparency, and inclusion.

The chapter examines bias and fairness in employment testing in Italy, comparing the public and private sectors. Public sector hiring is strictly regulated, based on transparency, equality, and meritocracy, as stated in the Constitution. Hiring occurs through public competitions with standardized exams focused on qualifications and technical skills, with growing attention to soft skills. The private sector is more flexible, adapting selection to business needs and emphasizing practical skills, experience, and cultural fit, enabling quicker hiring. Private companies often use innovative methods, including AI tools and social media screening, and value diversity and international profiles. Italian labor laws, aligned with EU directives, prohibit discrimination based on sex/gender, ethnicity, religion, sexual orientation, or disability. Employers must ensure fair, compliant selection processes. Professional guidelines stress the use of valid, unbiased tools. The rise of technology in hiring highlights the need to manage algorithmic bias, with final decisions remaining a human responsibility.

This chapter explores the legal frameworks that govern employment testing in Australia, including federal and state anti-discrimination legislation, and evaluates their impact on employment testing in the country. Overall, despite the existence of legal protections for individuals from diverse demographic groups (e.g., culturally and linguistically diverse backgrounds, sex/gender, age), judicial scrutiny of discrimination in employment testing remains limited. Practical challenges, such as difficulties in gathering evidence of discrimination, and the prospect of limited financial compensation, may discourage legal action. Moreover, statistical evidence is neither widely used nor required to demonstrate discrimination, resulting in a regulatory environment where employment testing practices are often guided more by organizational discretion and international perspectives than by legal mandates. However, as hiring technologies continue to evolve, this chapter highlights the opportunity for stronger regulatory oversight and empirical rigor to ensure employment testing remains both equitable and legally defensible.

Employment testing is routinely performed in South Africa today, but this was not always the case. Turning its back on its apartheid history of racial segregation and discrimination, South Africa has developed a progressive legal system to thwart bias and promote fairness in employment testing. This chapter explores employment-related testing in the public and private sectors, beginning with an overview of South Africa’s apartheid history, followed by a discussion of how the current legal system addresses fairness. A distinctive aspect of South African law is that preferential treatment, including lower cutoffs and within-group norming for protected groups, is not only mandated but also widely practised as the norm rather than the exception. Our review concludes that South Africa has enacted an extensive legal framework to promote equality and prevent unfair discrimination.

Belgium follows global standards in psychological assessments, and great attention is paid to issues concerning bias and fairness by legal authorities, test developers, and researchers. Anti-discrimination laws cover around nineteen protected grounds and align with European Union directives, but hiring discrimination persists. This chapter illustrates the tension between the law, test developers and researchers who promote proper test use, and practitioners who continue to rely on tools that can perpetuate bias, such as unstructured interviews and intuition-based decision-making. Despite comprehensive anti-discrimination regulations and affirmative action measures such as gender quotas, there are no legal requirements for the use of valid selection procedures in Belgium. Balancing validity and diversity is emphasized more in the public sector than the private sector. Although professional bodies offer guidelines for appropriate test use, they mainly target clinical settings rather than employment settings.

This chapter explores bias and fairness in Swedish employment testing from legal, historical, and practical perspectives. Swedish labor laws, influenced by trade unions and the welfare state, emphasize non-discrimination under the Discrimination Act. The law prohibits bias based on sex, gender identity, ethnicity, religion, disability, sexual orientation, and age, and requires preventive action. It is enforced by the Equality Ombudsman and Labour Court. Although validity evidence is not explicitly required, selection decisions should be based on a job analysis. No proof of intent is required in discrimination claims, and the burden of proof is shared. Quotas are banned, but positive action is allowed for gender balance when qualifications are equal. Psychological test certification is voluntary in Sweden; the Psychological Association offers guidelines on validity, reliability, and fairness. However, these are not mandatory, and many employers develop their own policies. International standards offer best-practice guidance for fair assessments, including for emerging artificial intelligence tools.

This chapter examines bias and fairness in employment testing in the Netherlands, addressing twenty key questions related to historical and cultural developments, legal frameworks, professional guidelines, and psychometric issues. Although equal treatment is a fundamental legal principle, perceptions of hiring discrimination remain widespread. The chapter explores demographic shifts that have shaped discussions on employment fairness and outlines the Dutch legal framework, focusing on the Equal Treatment Act and the role of the Netherlands Institute for Human Rights in handling discrimination complaints. It also highlights the relatively limited attention given to fairness in professional guidelines for practitioners. Furthermore, the chapter evaluates how psychological tests are assessed for bias, particularly through analyses of score differences, differential item functioning, and measurement invariance, while noting the scarcity of research on predictive bias. Emerging challenges, such as algorithmic bias, are also examined. Finally, the chapter discusses recent legislative efforts to promote fairness in employment testing, including a proposed law that was rejected in 2024.

Employment testing is a key tool for selection and placement in China’s public and private sectors. Rooted in a tradition of rigorous exams and shaped by modern workforce demands, such testing significantly influences access to job opportunities. Yet concerns about bias and fairness persist, driven by cultural norms, legal structures, and changes in the labor market. This chapter examines key issues related to bias and fairness in Chinese employment testing, exploring historical and cultural contexts, legal regulations, professional standards, and enforcement mechanisms. It also addresses measurement bias, challenges to diversity, and the growing influence of machine learning and advanced psychometrics in assessment design. By analyzing these dimensions, the chapter offers a comprehensive view of current challenges and highlights opportunities to improve equity in hiring practices. The discussion provides insights for employers, policymakers, and researchers navigating the complexities of employment testing in China.

This chapter explores bias and fairness in employment testing in Türkiye across governmental and private sectors. It distinguishes fairness – equal opportunity, transparency, and uniform outcomes – from bias, especially in relation to predictive validity. The chapter situates these issues within Türkiye’s cultural, ethnic, and socioeconomic landscape, examining how historical and regional factors shape perceptions and practices. Key legal and regulatory frameworks, such as Turkish Labor Law and constitutional mandates, are reviewed to highlight protections for equal treatment. It also evaluates bias detection methods, including differential item functioning, sensitivity reviews, and predictive bias analyses, and discusses challenges from emerging technologies such as the use of artificial intelligence in personnel selection. The chapter underscores the need for strong validity evidence and proactive strategies to promote fair and equitable hiring in Türkiye.

Nigeria’s diverse history and ethnic diversity have shaped the country’s current understanding of bias and fairness, including issues relating to employment. This chapter focuses on employment testing bias and fairness in Nigeria. When making employment decisions, it is a common occurrence, albeit not a legally permissible one, to have factors such as age, sex, political beliefs, religion, ethnicity, and disability taken into account. Nigeria’s discrimination laws cover all employers, third parties, and licensure. However, Nigerian discrimination adjudication has a narrow purview. For instance, there are no clear standards for validity evidence, no rules for demonstrating disparate impact, no shifting of the burden of proof, and no recognition of disproportionate impact. The limited use of professionally designed selection processes also means that bias-related concerns receive little attention. Information about the impact of the legal environment on industrial and organizational psychology is similarly lacking. Nonetheless, there are initiatives aimed at professionalizing psychology in the nation, which should increase the reliability and validity of selection procedures.