Artificial intelligence in the recruitment process. How can companies gain applicants’ trust?

Table of Contents

• List of abbreviations
• List of illustrations
• List of tables
• 1 Introduction
  • 1.1 Initial situation
  • 1.2 Problem statement
  • 1.3 Objectives and approach
  • 1.4 Methodology
• 2 Theoretical background
  • 2.1 Artificial Intelligence in recruiting
    • 2.1.1 Definition of AI
    • 2.1.2 Types of AI-tools in recruiting
    • 2.1.3 Advantages of AI in recruiting
      • 2.1.3.1 Efficiency
      • 2.1.3.2 Objectivity
    • 2.1.4 Challenges of AI in recruiting
      • 2.1.4.1 Bias and discrimination risk
      • 2.1.4.2 Lack of human interaction and judgement
      • 2.1.4.3 Ethical and legal concerns
      • 2.1.4.4 Lack of transparency
      • 2.1.4.5 Technical limitations
    • 2.1.5 Applicant perceptions of AI in recruiting
      • 2.1.5.1 Emotional impacts
      • 2.1.5.2 Preferences for human vs. AI-driven decisions
  • 2.2 Trust in technology
    • 2.2.1 Prerequisite for trust - procedural fairness
    • 2.2.2 Definition of trust in AI
    • 2.2.3 Initial trust building
      • 2.2.3.1 Performance
      • 2.2.3.2 Process
    • 2.2.4 Ongoing trust development
      • 2.2.4.1 Performance
      • 2.2.4.2 Purpose
    • 2.2.5 Factors influencing trust in AI
    • 2.2.6 Strategies for trust building
  • 2.3 Employer branding and candidate experience
    • 2.3.1 The role of the recruiting process on employer branding
    • 2.3.2 Impact of AI on employer branding
• 3 Research design and methodology
  • 3.1 Research design
    • 3.1.1 Rationale for choosing a qualitative approach
    • 3.1.2 Limitations of the methodology
  • 3.2 Data collection
    • 3.2.1 Development of the interview guide
    • 3.2.2 Pilot testing interview questions
    • 3.2.3 Process of conducting semi-structured interviews
  • 3.3 Participant selection
    • 3.3.1 Inclusion criteria for participants
    • 3.3.2 Recruiting process for applicants
  • 3.4 Data analysis
    • 3.4.1 Steps in qualitative content analysis (Kuckartz)
    • 3.4.2 Coding and categorization of themes
  • 3.5 Ethical considerations
    • 3.5.1 Informed consent and voluntary participation
    • 3.5.2 Anonymity and data protection measures
• 4 Results
  • 4.1 Experiences with AI in recruiting
  • 4.2 Perception of AI in recruiting
    • 4.2.1 Positive
    • 4.2.2 Negative
    • 4.2.3 Fair
    • 4.2.4 Unfair
    • 4.2.5 Different forms of AI
  • 4.3 Emotional response
  • 4.4 Data protection concerns
  • 4.5 Trust in AI based recruitment
    • 4.5.1 Mistrust
    • 4.5.2 Trust
    • 4.5.3 Ambivalence
    • 4.5.4 Compliance without trust
  • 4.6 Transparency about AI usage
  • 4.7 Adjustments in behavior
  • 4.8 Effects on employer brand
  • 4.9 AI recommendatory vs. autonomous
  • 4.10 Trust enhancing factor - hybrid process
• 5 Discussion
  • 5.1 Interpretation of findings
    • 5.1.1 Alignment with existing literature
    • 5.1.2 New insights and contributions
  • 5.2 Practical implication
    • 5.2.1 Human-AI collaboration
    • 5.2.2 Communication
    • 5.2.3 Managing emotional responses
    • 5.2.4 Tailoring AI use to recruitment stages
    • 5.2.5 Employer brand considerations
  • 5.3 Limitations of the study
    • 5.3.1 Methodological constraints
    • 5.3.2 Generalizability of findings
  • 5.4 Suggestions for future research
• 6 Conclusion
• Bibliography
• List of appendices

Purpose & Key Topics

This thesis aims to investigate the factors influencing applicants' trust in AI-powered recruiting processes to derive practical recommendations for organizations. The primary research question explored is: "Which factors foster applicants' trust in AI-powered recruiting processes?"

• Identifying factors that foster and inhibit trust in AI in recruiting.
• Understanding applicants' perceptions of various AI tools and decision-making types.
• Analyzing the impact of AI usage on employer brand perception.
• Exploring how awareness of AI in recruiting alters applicant behavior.
• Developing practical recommendations for organizations to build trust in AI-assisted recruitment.
• Examining the role of transparency and human oversight in AI recruitment processes.

Excerpt from the Book

Summary of Chapters

Chapter 1: Introduction: This chapter sets the stage by outlining the initial situation of AI in recruiting, presenting the core problem statement, defining the research objectives and approach, and detailing the overall methodology of the thesis.

Chapter 2: Theoretical background: This section provides the foundational knowledge, discussing Artificial Intelligence in recruiting, various concepts of trust in technology, and the interplay between employer branding and candidate experience.

Chapter 3: Research design and methodology: This chapter meticulously describes the qualitative research design, including the rationale for choosing a qualitative approach, data collection methods (semi-structured interviews), participant selection criteria, data analysis procedures (Kuckartz approach), and ethical considerations.

Chapter 4: Results: This chapter presents the empirical findings from the qualitative interviews, detailing participants' experiences, perceptions (positive, negative, fair, unfair), emotional responses, data protection concerns, trust levels, transparency demands, behavioral adjustments, and effects on employer brand regarding AI in recruiting.

Chapter 5: Discussion: Here, the empirical findings are interpreted in light of existing literature, highlighting alignments and new insights, followed by practical implications for organizations, and acknowledging the study's limitations and suggestions for future research.

Chapter 6: Conclusion: The final chapter summarizes the primary findings, emphasizing both trust-fostering and trust-inhibiting factors in AI-based recruiting, the strong preference for hybrid processes, the dilemma of transparency, the ambivalent impact on employer brand, and the observed behavioral adjustments of applicants.

Keywords

AI, recruitment, trust, fairness, employer branding, transparency, candidate experience, human-AI collaboration, qualitative research, decision-making, bias, data protection, emotional response, hybrid process, job applicants, automation, perception, ethical concerns, HR management.

Frequently Asked Questions

What is this thesis fundamentally about?

This thesis fundamentally explores how Artificial Intelligence is used in the recruitment process and, specifically, what factors influence job applicants' trust in these AI-powered systems. It aims to understand both the opportunities and challenges AI presents in hiring and to provide recommendations for companies to build trust.What are the central thematic areas?

The central thematic areas include the application of AI in human resources, candidate trust in technology, the impact of AI on employer branding and candidate experience, and the methodology of qualitative research to explore these complex perceptions.

What is the primary objective or research question?

The primary objective is to identify the factors that foster applicants' trust in AI-powered recruiting processes. The main research question is: "Which factors foster applicants' trust in AI-powered recruiting processes?"

What scientific method is used?

The study employs a qualitative research design, utilizing semi-structured interviews for data collection and qualitative content analysis, following Kuckartz's approach, for data interpretation.

What is covered in the main body?

The main body delves into the theoretical background of AI in recruiting and trust in technology, the detailed research methodology, the empirical results derived from interviews on applicant perceptions and experiences, and a comprehensive discussion aligning findings with existing literature and presenting practical implications.

Which keywords characterize this work?

Key terms characterizing this work include AI, recruitment, trust, fairness, employer branding, transparency, candidate experience, human-AI collaboration, qualitative research, decision-making, bias, data protection, emotional response, hybrid process, job applicants.

How do candidates perceive AI decision-making (recommendatory vs. autonomous)?

Participants generally prefer AI to act in a recommendatory capacity, providing suggestions that human recruiters can review, rather than making autonomous decisions, especially in later, more critical recruitment stages. Autonomous AI is more accepted for initial, impersonal tasks like CV screening.

What is the "hybrid process" in AI-assisted recruiting and why is it important for trust?

The "hybrid process" refers to a recruitment approach that combines AI-driven tasks with human touchpoints and oversight. It is crucial for trust because it addresses applicant fears of dehumanization and unjust rejections, ensuring that human judgment and interaction remain integral, especially for complex or sensitive evaluations.

What is the dilemma organizations face regarding transparency of AI usage in recruitment?

Organizations face a dilemma where transparency about AI usage is ethically and morally demanded, but disclosing it can trigger negative reactions from applicants, leading to anxiety and behavioral adjustments. Conversely, concealing AI usage erodes trust and harms the employer brand, creating a difficult balance.

How do applicants' emotional responses and behavioral adjustments influence trust in AI-powered recruiting?

Applicants often experience negative emotional responses like worry and anxiety when AI is used, particularly due to perceived lack of human interaction. This can lead to behavioral adjustments, such as tailoring applications to "fit the AI." These emotional and behavioral reactions significantly impact their trust and willingness to engage with AI-driven processes, highlighting the need for strategies to manage these responses.