Futuristic cityscape with people and AI networks representing the formation of AI norms.

AI's New Rules: How Society is Shaping Norms for Artificial Intelligence

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Beau Callahan in Tech & Innovation November 2026 • 4 min read.

"Discover how formal regulations, informal institutions, and spontaneous norms are evolving to govern AI's role in our lives, and what it means for the future."


Artificial Intelligence (AI) is quickly becoming an integral part of our daily lives, raising the urgent need for new social and ethical norms. However, AI's rapid evolution far outpaces traditional norm-setting processes, presenting unprecedented challenges. Understanding how these norms are formed is essential to ensure AI benefits society.

This article examines the critical processes of norm formation surrounding AI, focusing on how new norms are established rather than dictating what they should be. We will explore different scenarios, from centralized mandates by formal authorities to decentralized, bottom-up emergence driven by spontaneous social behaviors.

Far from offering a definitive guide, this article aims to provide interpretive tools for understanding society's response to AI's growing pervasiveness. We'll also consider how AI itself might influence the development of future social norms, emphasizing the importance of open, inclusive, and transparent public discourse in this rapidly evolving landscape.

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AI’s Growing Influence

Artificial intelligence is increasingly shaping how people work, communicate, and make decisions. Its effects vary by application, and the benefits and risks are still developing across society. Evaluating AI therefore requires attention to both its capabilities and its limitations.

How AI Works

Artificial intelligence refers to computer systems that perform tasks associated with human intelligence, including learning, problem solving, decision-making, creativity, and pattern recognition. Generative AI can create text, images, music, or code in response to a user’s request. A key limitation is that AI can produce an answer that sounds correct but is actually made up or wrong, a problem often described as a hallucination.

An Evolving Field

Artificial intelligence has developed through successive efforts to reproduce abilities associated with human intelligence in machines. Its history includes advances in learning, reasoning, language, pattern recognition, and autonomous decision-making. Because the field continues to change, its milestones are best understood as part of an ongoing evolution rather than a finished progression.

The Three Pillars of AI Norm Formation

Futuristic cityscape with people and AI networks representing the formation of AI norms.

Norms around AI are forming through three main avenues: formal institutions, informal institutions, and spontaneous norms. Each plays a crucial role in shaping how we interact with and regulate AI technologies.

Formal institutions, such as governments, create regulations and laws to govern AI behavior. Recently, there has been increasing demand for top-down regulation to address existential threats and legal uncertainties related to AI. These regulations aim to ensure the safe adoption of AI in sectors like healthcare and finance, aligning AI use with human rights and ethical considerations. Auditing—systematic evaluations of AI actions—is a promising approach.

  • Unknown Unknowns: The rapid pace of AI development makes it challenging to anticipate future capabilities, leading to potential regulatory gaps.
  • Limited Regulatory Control: Unlike sectors like nuclear power, AI is easier to implement and harder to trace, making it difficult to restrict malicious uses.
  • Guarding the Guardians: Concentrated power in a few private companies raises concerns about conflicts of interest and the need for independent oversight.
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Research Toward Advanced AI

Current AI research focuses on systems that can learn, reason, and perform advanced tasks that once required human intelligence. OpenAI states that its research may eventually lead to artificial general intelligence, defined in its description as a system capable of solving human-level problems. Google Cloud likewise presents AI as a collection of technologies that enables computers to learn, reason, and carry out sophisticated tasks.

Limits and Uncertainty

AI systems can produce useful outputs, but their performance is not uniformly reliable across every task or context. Failures may arise when systems misunderstand a request, identify patterns incorrectly, or present an inaccurate answer with confidence. These limitations make human oversight and careful evaluation important when AI is used in real-world settings.

Comparing AI Capabilities

AI systems differ in the kinds of tasks they can perform and in how effectively they handle learning, reasoning, creativity, or decision-making. Some applications emphasize recognizing patterns, while others generate text, images, music, or code. Comparing systems therefore requires examining both their intended functions and the reliability of their results.

Informal institutions, such as universities and professional organizations, also play a key role in shaping AI norms. These bodies propose codes of behavior and address gaps in formal regulation. Two sectors where informal institutions are actively developing norms are scientific publishing and education. For example, many publishers have decided that AI cannot be listed as an author, emphasizing human accountability and creativity in research. Education is another heated battleground, with institutions grappling with how to manage AI tools like ChatGPT. Some have banned it, while others seek more nuanced approaches.

The Future of AI Norms: A Call for Open Dialogue

As AI continues to evolve, it's crucial to maintain open and inclusive discussions about its role in society. The interplay between formal regulations, informal institutions, and spontaneous norms will shape the future of AI. We must address the challenges of rapid technological advancements, potential conflicts of interest, and the need for adaptability in our regulatory approaches. Fostering transparency and proactive measures will ensure that AI benefits humanity while upholding our democratic values.

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Balancing Promise and Limits

AI combines significant capabilities with important uncertainties. It can extend human capacity in areas such as problem solving, creation, and pattern recognition, but it can also generate incorrect information. A responsible understanding of AI must hold these strengths and weaknesses together rather than treating the technology as either universally transformative or universally unreliable.

Toward New AI Frontiers

Future AI development is likely to pursue systems with broader abilities to learn, reason, and solve complex problems. One stated research goal is artificial general intelligence capable of addressing human-level problems. Whether and when such systems emerge remains uncertain, making continued research and evaluation central to the field’s outlook.

AI in Society

The social significance of AI extends beyond individual applications because these systems can influence decisions, information, and creative work. Their broader effects depend on how people and institutions deploy them, assess their outputs, and respond to failures. Establishing norms for AI therefore involves both technical performance and social judgment.

People and AI

AI is designed to perform tasks that have historically required human intelligence, including recognizing speech, identifying patterns, making decisions, and creating content. These capabilities can support people in many settings, but they do not eliminate the need for human judgment. Human users remain important for framing requests, checking outputs, and deciding how results should be applied.

The study at a glance, in the paper's own terms

PopulationAI norm-formation processes and society's response to AI[1]
Main outcomePossible criticalities affecting mechanisms of norm formation[1]
Conflicts of interestPotential conflicts of interest in official governance due to high economic stakes[1]
Times cited26[1]

A historical example of regulation meeting a new technology

  • 4 and 2 mphThe UK’s Locomotive Act set vehicle speed limits at 4 mph on country roads and 2 mph in cities.[2]

What the examples add to the paper's account

The vehicle rules show how formal norms can specify practical constraints and procedures, while their long duration suggests that rules may persist even as the technology and its social context change.[2]

The OpenAI example puts the paper’s focus on norm formation into a concrete governance setting: a public statement supporting oversight was followed by a threat to leave Europe if regulation became too burdensome. The excerpt documents that sequence, not a general pattern of behavior.[2]

The author’s question about whether readers might judge unpolished English differently after easy access to ChatGPT illustrates how everyday expectations around writing may shift, without establishing that they have shifted.[2]

The paper treats “norm” as a broad working category covering regulations and conventions, while acknowledging that this approximation leaves distinctions among types of social norms aside.[1]

Where the paper's account is weakest

  • The paper’s broad use of “norm” is a first-order approximation and does not fully distinguish personal, descriptive, injunctive, and other forms.[1]
  • The author says the examples of spontaneous emergence and tipping point have theoretical differences that the paper does not examine.[1]
  • The account describes informal bodies as influential norm proposers, but their ability to require adoption is limited to their own remit.[2]
  • A university can sanction conduct under its own code, yet cannot make students follow that code if they move to an institution with different rules.[2]

What a follow-up would need to show

  • When do local rules made by informal institutions fill a gap in formal regulation, and when do they simply tailor existing rules to a particular setting?[2]
  • How might the norms users develop for interacting with language models change as people decide whether to treat them as partners, replacements, or something else?[2]
  • What makes formal deliberation around AI open and inclusive when the pace of technological change outstrips the pace of norm formation?[1]

Short answers on this study

Does the paper prescribe what AI norms should be?

No. It focuses on how norms can be established rather than prescribing their content.[1]

Can informal institutions make AI norms binding everywhere?

Not generally: their influence in proposing codes does not give them authority to enforce adoption beyond their remit.[2]

What does the paper say about AI’s role in future norm formation?

It considers how AI may shape future social norms and emphasizes open, inclusive, transparent public discourse in formal deliberation.[1]

Sources

  1. Shaping new norms for AI (The Royal Society, 2024)
  2. shaping new norms for ai (Europe PMC, 2024)

About this Article -

Written with AI assistance from published research, and reviewed by the Mystum team. See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1098/rstb.2023.0028,

Title: Shaping New Norms For Ai

Subject: physics.soc-ph cs.ai cs.hc cs.si econ.gn q-fin.ec

Authors: Andrea Baronchelli

Published: 17-07-2023

Everything You Need To Know

1

What are the three main avenues through which norms around Artificial Intelligence are being formed?

Norms around Artificial Intelligence are forming through three main avenues: formal institutions, informal institutions, and spontaneous norms. Formal institutions, such as governments, create regulations and laws to govern AI behavior. Informal institutions, like universities and professional organizations, propose codes of behavior and address gaps in formal regulation. Spontaneous norms emerge from everyday behaviors and interactions within society, shaping how individuals and communities interact with AI technologies.

2

How do formal institutions, like governments, influence the development of norms surrounding Artificial Intelligence?

Formal institutions, such as governments, shape Artificial Intelligence norms by creating regulations and laws. These regulations aim to ensure the safe adoption of AI across various sectors like healthcare and finance, aligning AI use with human rights and ethical considerations. They also address potential risks associated with AI. For instance, there's increasing demand for top-down regulation to address existential threats and legal uncertainties related to AI.

3

In what ways do informal institutions contribute to shaping the norms associated with Artificial Intelligence?

Informal institutions, like universities and professional organizations, significantly contribute to shaping Artificial Intelligence norms. They propose codes of behavior and address gaps in formal regulations. Two sectors where informal institutions are actively developing norms are scientific publishing and education. For example, many publishers have decided that AI cannot be listed as an author, emphasizing human accountability and creativity in research. Education is another heated battleground, with institutions grappling with how to manage AI tools like ChatGPT.

4

What are some of the key challenges in regulating Artificial Intelligence, as highlighted within the context?

Some key challenges in regulating Artificial Intelligence include 'Unknown Unknowns,' the rapid pace of AI development makes it difficult to anticipate future capabilities, leading to potential regulatory gaps. There's also 'Limited Regulatory Control' because AI is easier to implement and harder to trace, making it difficult to restrict malicious uses. Finally, 'Guarding the Guardians,' concentrated power in a few private companies raises concerns about conflicts of interest and the need for independent oversight. These challenges underscore the need for adaptability and proactive measures in AI norm formation.

5

Why is open dialogue and inclusive discussions crucial for the future of Artificial Intelligence norms?

Open and inclusive discussions are crucial for the future of Artificial Intelligence norms because the interplay between formal regulations, informal institutions, and spontaneous norms will shape AI's future. Addressing challenges like rapid technological advancements, potential conflicts of interest, and the need for adaptability in regulatory approaches requires a broad, inclusive conversation. Fostering transparency and proactive measures through open dialogue ensures that Artificial Intelligence benefits humanity while upholding democratic values.

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