Using the Rhetorical Prompt Engineering Framework and collaborative conversations between Jeanne and two AI Assistants, we present the following summary and word frequency articulations for the European Union’s 2024 Artificial Intelligence Act. Please see Endnotes[i] for authors’ notes on the prompt engineering process we used to produce this plain-language summary.
General Overview of The Act
The Artificial Intelligence Act establishes a uniform legal framework within the European Union (EU) for the development, marketing, and use of AI systems. This regulation is designed to promote human-centric and trustworthy AI while ensuring a high level of protection for health, safety, and fundamental rights, as well as supporting innovation. The regulation seeks to prevent the fragmentation of the internal market by setting uniform obligations for operators, thereby guaranteeing consistent protection and free circulation of AI-based goods and services across the Union.
Purpose and Scope
The regulation seeks to encourage ethical use cases by providing clear rules for AI systems. It addresses the need for AI systems to align with Union values, particularly in promoting human-centric AI that respects democracy, the rule of law, and environmental protection. The regulation outlines obligations for operators to ensure the development and use of AI systems are trustworthy and safe, while also preventing restrictions on AI development across member states.
Top 5 Key Provisions
Uniform Legal Framework: Establishes a consistent and high level of protection for AI systems throughout the Union to ensure trustworthy AI. This includes preventing divergent national rules that could lead to fragmentation and decreased legal certainty.
Human-Centric AI: Emphasizes that AI should serve as a tool for people, enhancing human well-being and respecting fundamental rights.
High-Risk AI Systems: Introduces specific requirements for high-risk AI systems to ensure they do not pose unacceptable risks to public interests or fundamental rights.
Transparency and Documentation: Requires operators to maintain transparency, technical documentation, and record-keeping for AI systems.
Innovation and Support for SMEs: Includes measures to support innovation, particularly focusing on small and medium enterprises and startups.
AI System Definitions and Applications
The regulation provides detailed definitions of AI systems, highlighting their key characteristics such as the capability to infer outputs like predictions and decisions. It differentiates AI systems from traditional software systems and emphasizes their ability to learn and adapt. The regulation also outlines various sectors where AI can provide significant benefits, including healthcare, agriculture, food safety, education, media, public services, and environmental monitoring.
Generative AI and General-Purpose AI Models
The document references generative AI, which includes AI systems that can create content like text, audio, images, or video. These models offer significant innovation opportunities but also present challenges, especially for creators like artists and authors.
The document specifically references generative AI and general-purpose AI models in several instances:
Large Generative AI Models: These are highlighted as typical examples of general-purpose AI models, capable of flexible content generation, such as text, audio, images, or video, suitable for various tasks.
Innovation and Challenges: General-purpose AI models, including large generative AI models, present unique innovation opportunities but also challenges for artists, authors, and other creators in how their creative content is created, distributed, used, and consumed.
Key Points on Generative AI
Large Generative AI Models: These models are examples of general-purpose AI, able to create various types of content for different tasks.
Innovation and Challenges: Generative AI models offer new opportunities but also pose challenges in how creative content is produced, distributed, and consumed.
The “Artificial Intelligence Act” aims to ensure AI systems are developed and used safely and responsibly, aligned with EU values. It highlights the importance of human-centric AI, supports innovation, and sets rules for high-risk AI systems to protect fundamental rights. The regulation also addresses the potential and challenges of generative AI.
Top Two Key References to Generative AI
Section 99: “Large generative AI models are a typical example for a general-purpose AI model, given that they allow for flexible generation of content, such as in the form of text, audio, images, or video, that can readily accommodate a wide range of distinctive tasks.
Section 105: “General-purpose AI models, in particular large generative AI models, capable of generating text, images, and other content, present unique innovation opportunities but also challenges to artists, authors, and other creators and the way their creative content is created, distributed, used and consumed.”
Word Frequencies
No surprise that the term AI occurred 1,516 times, exclusive if inclusion in larger words (ex: gain). What surprised us was how few times the word ethics was mentioned (3). Bias was mentioned 25 times, and trustworthy 17 times. Innovation was mentioned 30 times, while transparent was noted 6 times. It’s important to note that this is an English translation of the text, which itself is 458 pages in total.
Public Affairs Notes
The “Artificial Intelligence Act” sets forth comprehensive guidelines and regulations to ensure AI systems are developed and used in a manner that is safe, trustworthy, and aligned with Union values. The emphasis on human-centric AI, support for innovation, and specific requirements for high-risk AI systems underscore the EU’s commitment to fostering a balanced and secure AI ecosystem. The inclusion of generative AI highlights the recognition of its potential and the need to address the unique challenges it presents.
Endnotes
[i] Jeanne’s Notes:
To elicit the output, I employed the four qualifiers of ethical out and the Rhetorical Prompt Engineering Framework. To start: “FIRST PASS: Please provide a plain language summary of the attached document, which is an English translation of a European Union government document, “The Artificial Intelligence Act.” SECOND PASS: “Please organize the summary into five key points that refer to generative AI in the document.” THIRD PASS: “Please revise for an audience with a 12th-grade reading level. And note specific instances of generative AI mentions. I purposely prompted several times to demonstrate the validity of the Rhetorical Prompt Engineering Framework.
For these endnotes, I prompted GPT and Claude: What is the one thing you want others to know about human-AI collaboration in writing documents?
GPT’s Notes:
One key aspect of human-AI collaboration in writing professional documents is the combination of strengths. AI can efficiently handle large amounts of data, provide quick summaries, and identify patterns or specific information within texts. On the other hand, humans bring context, creativity, and nuanced understanding that AI currently lacks. Together, this collaboration can enhance productivity, accuracy, and the overall quality of the documents. AI can take on time-consuming tasks, allowing humans to focus on higher-level decision-making and creative aspects, ultimately resulting in more polished and comprehensive professional documents.
Claude’s Notes:
Productive human-AI collaboration on writing documents requires leveraging the unique strengths of each partner. Humans should take the lead by providing high-level creative vision, themes, tone, and narrative direction informed by rich life experiences and cultural understanding. AI assistants aid by quickly researching topics, providing relevant facts and evidence, and offering suggestions based on analyses of writing quality. We excel at tasks like outlining, ensuring logical flow, fact-checking, optimizing for clarity/conciseness, and adhering to style guidelines. The most effective partnerships have humans defining the overall creative work while incorporating AI input to enhance productivity and quality. However, the human must maintain control over authorship – AI’s role is as a collaborator providing suggestions, not an independent author. By combining human ingenuity with AI’s computational abilities, we can create superior written content that synthesizes complementary capabilities into an elevated final product greater than what either could produce alone.