Künstliche Intelligenz im Gerichtssaal – Warum Juristen zögern und wie sich das ändern lässt.
Ob im privaten Alltag, in der Industrie oder in der Medizin – Künstliche Intelligenz (KI) ist längst keine Zukunftsmusik mehr. Doch in einem Bereich scheint der technologische Fortschritt nur zögerlich Einzug zu halten: der juristischen Welt. Warum begegnen Jurist:innen und Fachpersonal der KI mit Skepsis? Und was müsste passieren, damit sich das ändert?
Diese Arbeit geht genau diesen Fragen auf den Grund. Sie bietet einen fundierten Einstieg in das Thema „Künstliche Intelligenz im Recht“, erklärt zentrale Begriffe, beleuchtet Einsatzmöglichkeiten und benennt die Herausforderungen, mit denen Legal Tech – also KI im juristischen Einsatz – konfrontiert ist. Der Blick richtet sich dabei vor allem auf die Menschen hinter der Robe: Was hindert sie daran, digitale Werkzeuge zu nutzen, die Prozesse beschleunigen und den Arbeitsalltag spürbar erleichtern könnten?
Zur Erklärung dieses Widerstands wird das Technology Acceptance Model nach Venkatesh und Bala (2008) herangezogen – ein Modell, das das Nutzerverhalten gegenüber neuer Technologie analysiert und zeigt, wie Wahrnehmung, Nutzen und Erwartungshaltungen Akzeptanz beeinflussen. Doch damit nicht genug: Die Autorin verfolgt einen innovativen Ansatz und kombiniert die Erkenntnisse mit der Nudge-Theorie von Thaler und Sunstein (2008). Deren zentrale These: Menschen lassen sich durch subtile Impulse – sogenannte „Nudges“ – zu gewünschten Entscheidungen lenken, ohne ihnen diese aufzuzwingen.
Im Rahmen einer empirischen Untersuchung wurden Jurist:innen aus verschiedenen Bereichen befragt. Zwei Gruppen wurden dabei unterschiedlich informiert – mit erstaunlichem Ergebnis: Bereits kleine, gezielt platzierte Informationen zur Alltagstauglichkeit von KI konnten kurzfristig die Wahrnehmung positiv beeinflussen. Es zeigte sich ein klarer Zusammenhang zwischen dem wahrgenommenen Nutzen und der Bereitschaft, KI-Systeme zu akzeptieren.
Diese Arbeit ist mehr als nur eine theoretische Abhandlung – sie ist ein praxisrelevanter Impulsgeber für alle, die Digitalisierung im Rechtswesen aktiv gestalten wollen. Sie bietet nicht nur Erklärungsmodelle, sondern konkrete Ansätze, wie durch psychologisches Feingefühl die Tür zur digitalen Transformation auch im konservativ geprägten juristischen Umfeld geöffnet werden kann.
Table of Contents
1. Introduction
2. Introduction to Artificial Intelligence
2.1 Historical Development
2.2 Comparing Intelligence Level with Human Intelligence
2.3 Computational Learning
3. Automation in the Legal Field
3.1 Historical Background
3.1.1 Legal Tech - A new idea
3.1.2 Starting signal for a new era
3.2 Why Legal Tech
3.2.1 Acceleration
3.2.2 Faultless
3.2.3 Simplification
3.2.4 Access to legal protection
3.2.5 Objectivity of decision-making and transparency
4. Acceptance theory
4.1 Research
4.2 Expression
4.3 Technology Acceptance Model
4.3.1 The development of the Technology Acceptance Model
4.3.2 Technology Acceptance Model 3
4.4 Psychological Acceptance
4.4.1 Interpersonal Acceptance- Rejection Theory
4.4.2 Anthropomorphism
4.4.3 Dual Process Theory of Cognition
4.5 Why Lawyers Are Not Very Accepting of Artificial Intelligence
4.5.1 Personality of lawyers
5. Nudge Theory
5.1 Economic fundamentals
5.1.1 The economic model of human behavior
5.1.2 Behavioral economics
5.2 Libertarian Theory Paternalism
5.2.1 Decision architecture
5.2.2 Libertarian Paternalism
5.3 Nudging
5.3.1 Digital Nudging
5.3.2 Nudging mechanisms
5.3.3 Opportunities and risks of nudging
6. Empirical Survey
6.1 Methodology
6.1.1 Evaluation of various legal court rulings
6.1.2 Feedback on possible bias
6.1.3 TAM Questionnaire
6.2 Results
6.2.1 Dummy: Coding
6.2.2 Control through TAM control variables
6.3 Discussion
6.3.1 When artificial intelligence support is not obvious
6.3.2 Obviousness
6.4 Descriptive Statistics
6.4.1 Assessing a court decision with AI support by gender
6.4.2 Support for AI by age group
7. Conclusion
Research Objectives & Topics
The research examines the acceptance of artificial intelligence (AI) among legal professionals, specifically investigating whether targeted nudges based on positive characteristics of AI can influence their perception and increase acceptance. The central research question explores how to overcome the inherent skepticism of the conservative legal field towards automation through evidence-based behavioral interventions.
- Technological integration and the "Legal Tech" landscape
- Acceptance theories (TAM, Psychological Acceptance, Dual Process Theory)
- Application of Nudge Theory in legal environments
- Empirical survey analysis of AI-supported court rulings
- The influence of user interface design and information transparency (nudging) on decision-making
Excerpt from the Book
3.2.5 Objectivity of decision-making and transparency
Through the use of AI, expectation is growing that automation can increase the equality of the application of the law (Rademacher, 2017). This hope arises from the public’s criticism of inconsistent jurisprudence, although there is no evidence for this (Ogorek, 2004).
Judges are seen as the epitome of objectivity and neutrality but they are not immune to unconscious prejudices. They can allow themselves to be unconsciously guided by prejudices when making decisions (Jäger, 2018). A study has found that, in addition to factors such as gender and social background, the judge’s mood of the day influences the judge’s decision-making. Even a judge’s hunger can have an influence on decisions. Judges are more likely to decide in favor of defendants after a meal (Danzinger et al., 2011).
Artificial intelligence may appear to be a solution to unconscious prejudices because it is supposedly free of subjective influences. It is possible that AI systems would be able to recognize human biases and alert the users. This could lead to a more uniform and fairer decision-making practice since such systems do not know personal experiences or daily moods and can work constantly (Otto, 2019).
On the other hand, the question arises as to whether the use of AI would actually lead to fairer decisions. After all, programs are developed by people. Their values and prejudices can thus unconsciously flow into the AI during programming. Consequently, the decision is simply transferred from the judge to the program and applied to the general public (Gless & Wohler, 2019). Whether technological progress can bring an advantage in terms of objectivity can only become clear in the future.
Summary of Chapters
1. Introduction: Presents the motivation for the study, highlighting the need to modernize the conservative legal sector through the adoption of AI and the application of acceptance theory.
2. Introduction to Artificial Intelligence: Provides a technical and historical overview, including definitions of weak vs. strong AI and the subfields of computational learning.
3. Automation in the Legal Field: Discusses the historical context, the emergence of Legal Tech, and the benefits of automation, such as acceleration, fault reduction, and increased access to legal protection.
4. Acceptance theory: Examines theoretical models for technology acceptance, including the Technology Acceptance Model (TAM) and psychological factors like anthropomorphism and dual process cognition.
5. Nudge Theory: Introduces libertarian paternalism and specific nudging mechanisms, exploring how these can be applied to steer behavior in legal settings without coercion.
6. Empirical Survey: Details the methodology, survey structure, and statistical results obtained from a study of 62 legal professionals regarding their perception of AI-supported court rulings.
7. Conclusion: Summarizes key findings, noting that targeted feedback (nudging) can positively influence acceptance, but suggests further research on long-term sustainability.
Keywords
Artificial Intelligence, Legal Tech, Nudge Theory, Technology Acceptance Model, Jurisprudence, Automation, Behavioral Economics, Legal Automation, Decision Architecture, Bias, Digital Nudging, Perceived Usefulness, Perceived Ease of Use, Human-Machine Interaction.
Frequently Asked Questions
What is the core focus of this thesis?
The thesis explores the low acceptance rates of artificial intelligence within the legal profession and evaluates whether psychological nudging techniques can improve the perception of AI systems among lawyers.
Which key thematic areas are covered?
The work covers the definition of AI, the evolution of Legal Tech, theoretical acceptance models like TAM, Nudge Theory, and the empirical analysis of how legal professionals evaluate AI-assisted judgments.
What is the primary research goal?
The primary goal is to investigate whether highlighting the positive attributes of AI (such as efficiency and ease of use) via targeted incentives (nudges) can reduce skepticism in the conservative legal environment.
Which scientific methods were employed?
The research uses a quantitative empirical study, specifically an online survey, and analyzes the collected data using ordinary least squared regression with dummy variables to assess differences in participant groups.
What does the main body address?
The main body moves from a fundamental understanding of AI and legal technology to the theoretical framework of technology acceptance and nudging, concluding with an empirical study and its discussion.
Which keywords characterize this work?
The work is characterized by terms such as Artificial Intelligence, Legal Tech, Nudge Theory, Acceptance Theory, Behavioral Economics, and Judicial Decision-Making.
How does "obviousness" affect the judgment evaluation?
The study found that when the use of AI in a court judgment was not obvious, participants perceived the ruling as more appropriate than when the AI assistance was explicitly disclosed.
What role does "Affinity for Technology" play?
Affinity for technology is a significant variable; tech-savvy individuals are generally more accepting of AI, but the study also found that less tech-savvy individuals may accept AI if they recognize it simplifies their routine work.
- Quote paper
- Ronja Boldt (Author), 2024, Fiat Iustitia. An Investigation of the Acceptance of Artificial Intelligence in Jurisprudence, Munich, GRIN Verlag, https://www.grin.com/document/1592537
