Generative AI, Contracts, Law and Design

Table of Contents

1. Frontmatter

2. Generative AI and the Future of Contracts, Law and Design

   Marcelo Corrales Compagnucci, Helena Haapio, Mark Fenwick

   Abstract

   This chapter serves as an introduction to this collection by exploring the transformative intersection of Generative AI (GenAI), contracts, law, and design. It highlights how advanced machine learning models are reshaping legal practice, contracts, and contracting. GenAI—a subset of artificial intelligence—uses large datasets to create original content and provide new opportunities for automating legal tasks, enhancing contract accessibility, and promoting proactive legal strategies. The chapter delves into the technological underpinnings of GenAI, including examples such as OpenAI's ChatGPT and DALL·E, Anthropic’s Claude, GitHub Copilot, Google’s Bard and Gemini, and DeepSeek. It also examines the ethical and regulatory implications of AI adoption, focusing on the principles of “Responsible AI,” and discusses the importance of human-centric design in preparing legal tools and solutions intended to drive policy and strategic objectives. Additionally, it provides a brief overview of the book’s content, outlining key topics such as proactive law, contract design, intellectual property, privacy communication, and health data governance. By providing case studies and practical insights, the chapter offers a comprehensive overview of GenAI’s impact on contracting and the legal domain and sets the stage for further discussions on its applications, challenges, and future directions.

3. No More Legal Writing in Contracts—Time to Break the Magic Spell!

   Helena Haapio

   Abstract

   The business world and the legal profession are undergoing a historic transformation. Traditional approaches to contracting and lawyering are being challenged, accelerated by the rise of generative AI (GenAI), and the spread of design-led thinking. These changes are reshaping the very nature—and legitimacy—of legal writing, particularly in the context of contracts. For decades, contracts have been treated as formal legal documents written by lawyers for other lawyers. Their structure, tone, and language have remained remarkably consistent over time, often reflecting inherited drafting conventions rather than the needs of the people who use them. If the purpose of contracts is to set and reach common goals, why does their language so often feel mysterious, like a kind of magic spell? This chapter begins by taking this question seriously. It explores how traditional legal writing has functioned as a form of inherited linguistic power, a dark legacy. Yet that spell and legacy have begun to break with the rise of visual and redesigned contracts, plain language, and the increasing integration of GenAI. These developments do more than make contracts easier to read; they challenge long-standing assumptions about what and who contracts are for, and how they can work. If we can move beyond legal writing as usual, we can begin to see contracts not as formal legal documents, but as tools for understanding and action. “No more legal writing in contracts” is more than a slogan. It is a call to reimagine how contracts are communicated, how legal professionals work, and how legal knowledge is shared and applied. It is also a call for lawyers to rethink their role—not only as firefighters or interpreters and guardians of rules, but as proactive solution providers and strategic enablers: partners in designing and building a better future.

4. Contracting: Is Generative AI Really Making a Difference?

   Tim Cummins, Sally Guyer

   Abstract

   Artificial Intelligence is not new and has been evident in the contracting process for a decade or more. But this was largely an additional functionality embedded in Contract Lifecycle Management (CLM) systems, initially operating entirely within an organization’s own systems. While Cloud computing introduced a new dimension, it did not take data into the public domain. When Generative AI (GenAI) burst onto the scene in 2022, it represented a revolutionary change. Suddenly, from being a hidden presence within enterprise software, it was freely available on laptops and mobile devices. This was accompanied by the typical reaction to technological innovationa mix of excitement, fear, skepticism and wild over-optimism. While there is no question that GenAI will have significant impact on contracting, this chapter explores the impact to date and anticipates the way that this will evolve.

5. AI as a Financial Coach—Promoting Sustainable Financial Management with Generative AI

   Marika Salo-Lahti, Mikko Ranta, Nina Toivonen, Helena Haapio

   Abstract

   In this chapter we will explore and analyze how generative AI tools designed with a human-centered approach can help companies with financial management and contribute to sustainable finance. The chapter begins with an introduction to the EU regulation related to sustainable finance, aiming to help achieve the objectives of the Green Deal. According to the Triple Bottom Line theory, the three parts of sustainability—environmental, social, and economical—are strongly interlinked. However, economic efficiency and sustainability are often perceived as conflicting goals. We will look at practical ways to reconcile the two perspectives. We will do this with the help of AI crew, a group of AI agents that are specialized in their specific fields. We will test and review how this crew can be used as a financial coach to create solutions for some of the key challenges in sustainable financial management. We will also consider the issue from the perspective of an example company, a European textile firm. The chapter concludes with a summary of our key findings and ideas for future research on AI, sustainable financial management and the law.

6. Generative AI, Can You Help Us Bridge the Implementation Gap in Contracting?

   Robert Waller, Helena Haapio, Patrick Shone

   Abstract

   Traditional contracts are written with disputes and litigation or arbitration in mind. This tends to prioritise a precise form of legal drafting that is coded for legal purposes, rather than for the practical purposes of performing the contract. The resulting disconnection is known as the implementation gap. Bridging the gap requires, among other things, an understanding of the objectives and what information is of most relevance to each type of business user. The ability of generative AI (GenAI) to simplify the language of contracts is well established, but in this chapter we explore what else it can do to bridge the gap and how well it can anticipate the needs of particular audiences—including people responsible for implementation in the field, without a background in law. We begin by using Anthropic’s Claude and OpenAI’s ChatGPT4o as our brainstorming and ideation partners in the problem-framing and solution-finding phases. While they provide significant support, we also evaluate how much help they can be as our contract assistants. We give ChatGPT4o contract simplification tasks and test how good it is at creating a contract guide: a tool that is often used to help contract implementation personnel to do their job. We use de Beaugrande and Dressler’s classic standards of textuality to challenge ChatGPT, asking it to explain its own limitations, and the level of human oversight required. Finally, we discuss how effective prompting can help us get the most usable results from our AI assistants.

7. Generative AI: Can Rule of Law Be Bargained for the Sake of Legal Tech Efficiency?

   Ebru Metin, Tanel Kerikmäe

   Abstract

   The threats of generative AI in modernising justice system and lawyering are discussed among stakeholders (judges, members of Bar, IT architects, public offices responsible for innovation etc.). However, the discourse has mostly been limited to the (a) capacities and resources; (b) theoretical technological possibilities; and (c) breaking down the conservativism of judges or clients. The major problems related to “deep fake,” biased algorithms, human control etc. are apprehended in the context of European Ethical Charter on the use of AI in judicial systems, and AI Act. In reality, there are several existing and planned use cases of legal tech that are related to generative AI, presented as phenomena of progress. Although the general knowledge of the potential problems and errors exists and the audit by humans is highlighted as a solution, the discussion lacks certain relevant aspect—client’s (of innovative services) needs such as transparency and accountability within the scope of Rule of Law. The clear lacuna is the lack of process or lifecycle for adopting the new use-cases prioritising the user-friendly approach and need for more effective access to justice. Innovation in the delicate field of applying legal rules needs analysis of human perception of justice in digital era to avoid the avangard use cases become beneficial rather to the service provider than the client who is left with the illusion of cost and time effectiveness.

8. Proactive Privacy Communication Design for Emotional Robots

   Hilja Autto, Jouko Nuottila, Anna Hurmerinta-Haanpää, Yueh-Hsuan Weng

   Abstract

   This chapter discusses a proactive approach to privacy communication and emotional robots, which are becoming an important part of human–machine interaction. These robots use emotional AI and are able to recognize and respond to human emotions. While there are many benefits associated with the mainstreaming of robotics, there are also significant personal data and privacy concerns involved in the use of emotional AI and robots. As a result, several initiatives to regulate the use of (emotional) AI have been made. This chapter argues that in addition to regulation, a proactive approach to privacy communication is needed in order for users of emotional robots to give consent to the collection of personal data. Tools based on the proactive approach and information design research and methods—multichannel communication, plain language, tone of voice, visualization and tailoring—make it possible to communicate personal data and privacy choices effectively to users: when robots communicate clearly through speech, gestures and screens, even less motivated users can make informed choices about whether to give their consent to the processing of their personal data. In addition, these tools make communication more effective, comprehensible and engaging for the user. The goal is that anyone who interacts with robots can do it safely and by making informed choices.

9. Generative AI for Individuals’ Financial Well-being and Debt Rehabilitation

   Nina Toivonen, Marika Salo-Lahti, Mikko Ranta, Helena Haapio

   Abstract

   Technology plays a significant role in today’s over-indebtedness. However, its potential to help people overcome debt problems and maintain good financial health remains largely untapped. The need for alternative, personalized solutions to over-indebtedness is becoming increasingly pressing worldwide, especially since many people struggling with debt do not have access to judicial debt rehabilitation programs. This chapter explores how generative AI (GenAI) could support individuals in financial distress. Using the behavioral COM-B model as a framework for designing effective interventions, we discuss how AI could help improve individuals’ capabilities, opportunities, and motivation to achieve financial well-being, and what solutions already exist for these purposes. Inspired by fitness applications that offer personalized advice, we used OpenAI’s GPT Builder to create “Finance Friend,” a simple prototype of a financial adviser, and explored its potential as a personalized financial coach. While the tool shows great promise for the future of financial coaching, we also emphasize the need for trustworthy technology and regulatory frameworks that promote responsible design, implementation, and use of AI in the context of debt rehabilitation.

10. AI Between the Legal System and Art—A Systemic Approach

    Petra Hietanen-Kunwald, Perttu Isohanni

    Abstract

    In this chapter, we explore the profound impact of artificial intelligence on the art and legal systems, with a specific focus on copyright issues. We address a significant concern: the potential of artificial intelligence to interfere with the interests and rights of artists when art is created and reproduced using artificial intelligence. Our approach, grounded in systems theory as represented by Niklas Luhmann, examines the characteristics and potential frictions within the legal and art systems affected by AI. Identifying systemic complexities is essential for exploring possible conflicts and developing effective strategies for dispute prevention and resolution. This constitutes the initial steps of a design process outlined in the Double Diamond framework and further developed in the UK Design Council’s Systemic Design Approach. The chapter argues that legislation alone is insufficient; a broader spectrum of (legal) and institutional measures is necessary to protect artists’ rights and interests in both the legal and art systems. This multifaceted approach highlights several factors that could instigate change and help resolve complex questions.

11. Style Matters: Intellectual Property Rights and the New Creative Economy

    Perttu Isohanni, Petra Hietanen-Kunwald

    Abstract

    The rapid emergence of generative artificial intelligence (GenAI) poses an existential threat to the creative profession. It not only serves as a potential substitute for human creativity in general, but also threatens to displace specific artists by reproducing their unique artistic styles. A distinct artistic style serves as an economic asset for an artist, but also as a reflection of their personal identity. Therefore, safeguarding the continued development of such artistic styles is essential not only to protecting economic opportunities for artists but also to preserving their artistic integrity and fostering a culturally rich, human-centric creative landscape. Nevertheless, granting extensive legal protection to individual artistic styles poses significant challenges. Imitation and adaptation of artistic styles have always been integral to human creativity. Copyright law addresses this by being cautious of not affording monopolies over ideas but by granting protection to expressions of ideas. While stylistic features, particularly in visual arts, can sometimes be difficult to distinguish from original creative expressions protectable by copyright, this chapter suggests that such features may not play a central role in assessing infringement, as doing so could risk undue limitations on the creative freedom of others. Instead, it argues that efforts should focus on upholding moral rights to prevent false attribution of works not created by the artist and to protect against derogatory treatments of works that could harm the artist’s reputation. Finally, it is suggested that intellectual property rights and remuneration models adapt to the changing creative landscape by allowing artists to be compensated for the use of their names to generate new works specifically designed to reproduce their artistic styles.

12. AI-Generated Comics: Enhancing Public Engagement and Ethical Awareness in Bioethics

    Marietjie Botes

    Abstract

    This chapter explores the innovative use of AI-generated comics to engage the public in discussions about bioethical issues, particularly in the context of emerging technologies like human germline gene editing. The concept of “Ethics by Design” (EbD), similar to “Privacy by Design” (PbD) under the GDPR, is examined as a proactive approach to embedding ethical considerations into the design and development of technologies. By leveraging AI tools to create visually compelling and narratively rich comics, bioethicists can simplify complex scientific concepts and ethical dilemmas, making them accessible to a wider audience. This democratization of information fosters broader public understanding and facilitates more inclusive and informed discussions about the ethical implications of new technologies. The chapter discusses the methodology of creating AI-generated comics, including the challenges and opportunities this approach presents. Key challenges include maintaining quality consistency, creative control, and addressing legal and ethical concerns. However, the benefits in terms of efficiency, cost-effectiveness, and accessibility are significant, allowing for the rapid production of educational materials that can be disseminated widely across diverse demographics. A case study, “The Artist,” is presented to illustrate the practical application of AI-generated comics in public engagement. This sci-fi comic, used in a public “Dine-and-Draw” event, facilitated discussions on bioethical issues such as consent, autonomy, identity, and the exploitation of AI. The interactive format encouraged participants to explore utopian and dystopian endings, highlighting the ethical complexities of technological advancements. The chapter concludes that AI-generated comics represent a powerful tool for fostering ethical awareness and deliberation. They provide an engaging platform for exploring bioethical issues, enabling communities to proactively engage with and influence the ethical trajectory of technological advancements. By incorporating feedback from public engagement studies and collaborating with experts, AI-generated comics can enhance the relevance and resonance of bioethical discourse, ultimately contributing to a more ethically aware and engaged society.

13. The Use of LLMs in the Legal Design Process—Designing Effective Access to Health Data Under the EHDS and the GDPR

    Jaana Kovalainen, Sarah de Heer

    Abstract

    In this chapter, the authors discuss the possibility of improving access to health data. The individual’s right to access their own health data is well-established in the European Union in both the General Data Protection Regulation (GDPR) and the European Health Data Space (EHDS). Nevertheless, the question arises whether individuals can effectively practice their right to access their health data, as there may be obstacles regarding the understandability and the use of their health data. The authors investigate the possibilities to advance access to an individual’s health data, including the understandability and use, by applying a human-centered design method, particularly legal design combined with Large Language Models (LLMs). The chapter also briefly reviews LLMs in general and their use in health care to provide a more holistic picture of the situation, but mainly the authors illustrate LLMs implementation in the legal design process. As such, the authors consider whether the use of LLMs, combined with legal design can potentially improve an individual’s access to, understandability and use of their own health data under the GDPR and the EHDS. If so, this will also strengthen the compliance with the GDPR and the EHDS. The authors discuss the use of health data from a European perspective, but the legal design process, and some of the ideas can be applied more widely.

14. Backmatter