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 Ghanaian employment space prioritizes procedural fairness, the basis on which the Labour Act, 2003 (Act 651) and the National Labour Commission were established. Other regulations govern certification and employment testing to uphold professional standards and worker rights. For instance, the Ghana Psychology Council regulates the certification and practice of psychologists who are also mindful of other guidelines such as the American Psychological Association (APA) Standards and Society for Industrial and Organizational Psychology (SIOP) Principles. The 1992 Constitution and the Labour Act, 2003 (Act 651) of Ghana further guarantee equality, prohibit employment discrimination based on race, sex, disability, religion, and age, with specific protection for children, the disabled, and women. For instance, women in Ghana are under-represented in the workplace, in response to which the Affirmative Action Law (Act 2024) was passed, aimed at improving equality and participation of women in decision making positions. With the increasing use of artificial intelligence in employment testing worldwide, Ghana has yet to establish formal regulations for the utilization of artificial intelligence in employee selection to ensure ethical standards and data protection.

What happened when people did not pay their debts? Debts Unpaid argues that conflicts over small-scale unpaid debts were a stress test for the economic order. To ensure the wheels of petty commerce continued to turn in Mexico, everyday debtors and creditors had to believe that their interests would be protected relatively fairly when agreements soured. A resounding faith in economic justice provided the bedrock of stability necessary for the expansion of capitalism over the longue durée. Introducing the two-hundred-year period of massive economic transformation explored throughout the book, this chapter presents the text’s key historical and theoretical interventions from the late eighteenth century to the first decade of the twenty-first. As the capitalist credit economy grew, especially through modern financial institutions, ordinary people used new financial tools and navigated increasingly opaque and impersonal credit relations. This Introduction outlines the dynamics of change and the challenges and opportunities they posed for the world of small-scale debtors and creditors.

This book places the troubles of ordinary people at the centre of economic change in Mexico, arguing that conflicts over small-scale unpaid debts were a stress test for the economic and political order. Studying malfunction – what happened when contracts broke or soured – exposes the ways in which debt trouble became a driving force in the history of accumulation and justice in the modern world. This concluding chapter offers final thoughts on the book’s core proposal: that a broad sense of fairness and justice provided a bedrock of stability that allowed for massive economic transformation over a long chronological horizon.

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.

Selection processes in France are governed by a comprehensive legal and regulatory framework that prioritizes fairness, non-discrimination, and equal opportunity. French labor laws explicitly prohibit discrimination based on twenty-five criteria, including sex/gender, ethnicity, disability, and age. Despite these protections, disparities persist, fueling ongoing policy debates and legislative refinements. Regulatory bodies such as the Defender of Rights oversee compliance and promote unbiased hiring practices. However, implicit biases and structural barriers continue to influence employment decisions, challenging efforts to achieve true workplace equality. Employers must balance legal obligations, diversity objectives, and test validity while adapting to evolving EU regulations, such as the AI Act (2024). The introduction of diversity labels and corporate social responsibility initiatives reflects a proactive commitment to fostering inclusive workplaces. Yet enforcement challenges remain, as rising reports of workplace discrimination highlight persistent gaps. Several recommendations have been proposed to mitigate discrimination without compromising the quality and effectiveness of selection methods.

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.

The use of tests and assessments in employment-related decision making has the potential to benefit organizations and individuals. However, their use is frequently criticized because of their adverse potential for bias and unfairness. The saliency of and attention to these issues may also vary from one country to another. Therefore, in addition to an overview of the handbook and its objectives, the present chapter presents a synthesis of the twenty-three chapters organized around four themes pertaining to bias and unfairness in employment testing, specifically, (1) historical and/or cultural issues, (2) legal and professional guidelines and issues, (3) psychometric issues, and (4) future- and forward-looking issues. Furthermore, the theory of cultural tightness-looseness is used in an exploratory manner to gain additional insights into patterns, or the lack thereof, across countries as reported in the chapters. The patterns of associations indicated that, relative to tight countries, loose countries were generally more attune to and have in place practices and regulations addressing employment testing bias and unfairness. Finally, some thoughts and suggestions for future research are discussed.

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.

The Korean term insamansa – “human resources are everything” –‘captures the deep value the nation places on personnel. Despite long-standing recognition of their importance, formal selection systems have emerged only recently. This chapter examines bias and fairness in Korean personnel selection through historical, legal, and societal lenses. Korea’s transformation from the labor-intensive industries of the 1960s–1980s to a technology-driven economy in the 2000s has reshaped perceptions of employment fairness. Current workplace protections primarily address sex and disability discrimination through laws such as the Equal Employment Opportunity and Work-Family Balance Assistance Act. Although the Fair Hiring Procedure Act aims to reduce biased practices, challenges persist in ensuring the validity and fairness of selection methods. Moreover, the increasing use of artificial intelligence in hiring raises concerns over algorithmic bias. The chapter calls for evidence-based policies and robust statistical methods to improve validity and fairness in Korea’s evolving labor market.

Testing and assessment have a long history in Greece. External hiring in the Greek public sector is carried out by the Supreme Council for the Selection of Personnel, an independent human resource management (HRM) body that currently runs employee selection procedures with the use of employment tests. In the private sector, employee assessment methods are used to a much greater extent than in the public sector. Greece’s entry into the European Union in 1981, as well as the competition from foreign companies, have further challenged HRM practices and methods used in staffing. Hiring processes have been enhanced by the inclusion of additional selection stages, such as semi-structured interviews, group interviews, and initial screening via job boards to augment the level of standardization and reduce incidents of bias. Greece’s entry into the EU has also led to the gradual addition of new laws to the Greek constitution aimed at establishing and enhancing equal opportunities in work, employment, and education. However, there are no specific guidelines implemented by psychological or HRM associations that specifically address bias and fairness in employee recruitment and selection processes.

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.

This chapter reviews issues pertaining to employment testing bias and fairness in Poland, which are discussed from the perspective of national legislative circumstances. In contrast to countries that are demographically more diverse in terms of national origin, and despite the existence of clear laws in this regard, Poland struggles with several problems connected with transparency and fairness in employment selection processes. In Poland, there is no single office that is responsible for regulating hiring procedures or controlling the development of standards for such. The general provisions on equal treatment formulated in the Constitution of the Republic of Poland, as well as the more detailed provisions of the Polish Labor Code, which refers to European Union regulations, indicate that various institutions, including the Ombudsman, the Government Plenipotentiary for Equal Treatment, and the labor courts, are responsible for compliance with anti-discrimination procedures. Labor law in Poland is considered one of the most protective of employees’ interests in Europe; it contains regulations aimed at counteracting discrimination arising from belonging to a minority group.