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Ethics of Artificial Intelligence

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History

In 1956 a small group of scientists gathered at Dartmouth for a Summer Research Project on Artificial Intelligence.

A new field of Science had begun.

Dartmouth AI Workshop, 1956
Dartmouth Summer Research Project on Artificial Intelligence, 1956. Credit: IEEE Spectrum, The Minsky Family

Over the next 70 years, Artificial Intelligence persisted mainly in the minds of science fiction writers and the small group of industry researchers and academics who continued to work toward creating the digital infrastructure needed for Artificial Intelligence to bloom, and to one day achieve the ultimate goal of Artificial General Intelligence (AGI)().

Using AI ethically

As consumers of GPTs and other AI platforms, we must consider in what ways can we use AI both effectively, and ethically.

AI Constitutions and Bills of Rights

How should the values that guide AI systems be set, and by whom? Two distinct approaches have emerged: corporate AI constitutions written by AI companies for their own models (Anthropic's Claude Constitution is the canonical example), and public AI bills of rights developed through democratic processes (the White House Blueprint for an AI Bill of Rights, October 2022, is the leading example).

Sociologist Alondra Nelson — who led the Blueprint's development as acting director of the White House Office of Science and Technology Policy (OSTP) — argues in A civic grammar for AI rights (Science, 2026) that these two forms of foundational document do very different work, and that one of them is structurally insufficient as a source of democratic legitimacy.

Corporate constitutions vs. public bills of rights

  • Corporate AI constitutions are internal training and alignment specifications. They describe a company's vision of how its model should behave. They are not negotiated with the publics affected by the model's deployment, and they can be revised by company fiat. Nelson notes that newer revisions of Anthropic's Claude Constitution have quietly removed references to international human rights agreements — and with them protections for "personal liberty, freedom of religion and intellectual property," and other rights that earlier versions included. Historian Jill Lepore observed that the document arrived "at a trying time for both artificial intelligence and constitutional democracy."
  • Public AI bills of rights declare rights claims that publics can extend to new institutions and new harms. Their force comes from democratic legitimacy and the broader legal-political infrastructure, not from the model developers. The Blueprint took its name from the first ten amendments to the U.S. Constitution but, Nelson argues, structurally resembles a different founding document — the Declaration of Independence. It declares principles and claims rights against concentrated power, but it does not establish courts, enforcement mechanisms, or procedures for redress.

"Civic grammar" and the diffusion of rights claims

Nelson describes what has emerged as a "civic grammar": a shared vocabulary of rights claims (non-discrimination, transparency, data privacy, notice, human alternatives) that publics can extend to new institutions and new harms, and that "has been traveling across jurisdictions, partisan lines, and institutional contexts." The American tradition is long — Patients' Bill of Rights, Consumer Bill of Rights, Tenants' Bill of Rights, Workers' Bill of Rights, Taxpayers' Bill of Rights — and the AI Bill of Rights template has spread the same way: actors with no shared political coalition, sometimes with explicit antipathy toward each other, adopting a common vocabulary because each, separately, has encountered the same kind of algorithmic harm.

This pattern reflects what sociologists David Strang and John Meyer call institutional diffusion among weakly related actors — a conceptual rather than relational mechanism by which abstract typologies become "a strategy for making sense of the world." Connecticut Democrats, Oklahoma Republicans, Florida's Republican governor, and a national student-advocacy network can adopt the same vocabulary without coordinating, because all are responding to the same structural condition: AI reshaping people's lives without their consultation. (For the specific state-level examples and the international convergence, see Blueprint for an AI Bill of Rights in the Legal lesson.)

Marshall's social citizenship and the AI rights tier

Nelson grounds the analysis in British sociologist T. H. Marshall's 1950 essay Citizenship and Social Class. Marshall argued that rights expand historically through successive waves of claim-making: civil rights extending to political rights, political rights extending to social rights — entitlements to economic security and the conditions of participation, against harms of industrial capitalism that individual civil-liberties frameworks could not address. Rights, in Marshall's account, "are never fully delivered at the moment of declaration. They are successively rearticulated by publics who attempt to hold institutions to commitments those institutions have not yet honored."

The Blueprint's five principles, Nelson argues, map onto Marshall's social-rights tier. They are not classical civil liberties; they are entitlements against systems "that increasingly govern access to employment, credit, healthcare, housing, and education." The structural parallel — collective, diffuse, opaque harms that older rights frameworks address only partially — is what explains the cross-partisan convergence: "actors who disagree on nearly everything else agree that algorithmic power requires a social citizenship response."

The limits of rights talk

Nelson is clear-eyed about what civic grammar cannot do on its own:

  • Accommodation can mimic transformation. A vocabulary that moves easily across partisan lines may have been "drained of the political content that gives rights claims their force."
  • Rights individualize structural problems. Frameworks built around individual claims often fail to address the collective and systemic nature of algorithmic harms.
  • Declaration is not delivery. History shows "declarations of entitlement and their substantive delivery can remain decades apart, separated by the organized power of those who benefit from the status quo."

Nelson's clarifying question for democratic institutions: will they take this civic grammar seriously before the AI companies finish writing their own constitutions for us all?

Sources and further reading

Transparency & Accountability

Bias & Discrimination

Assessment

Can you explain the difference between "Ethics of AI" and "Ethical AI?"

Hint: Refer to how Siau and Wang (2020) define each term

Ethics of AI
  • Ethics of AI refers to principles and regulations
Ethical AI
  • Ethical AI focuses on how AI behaves
How does Asimov's Three Laws of Robotics relate to modern ethical concerns of AI?
Do no harm

Asmiov emphasizes preventing harm to humans and how that concept informs current AI safety practices.

True or False: The Turing Trap suggests that efforts to make AI more human-like will empower workers' economic and political power.
False

The Turing Trap warns against replacing humans with AI, and that AI could be used to drive down wages and to a loss of economic and political power.

Name at least one major declaration or agreement on AI Ethics
International Agreements
  • Council of Europe Framework Convention on Artificial Intelligence and human rights

  • Political Declaration on Responsible Military Use of Artificial Intelligence and Autonomy

  • G20 AI Principles

Principles and Ethics
  • Asilomar AI Principles

  • UNESCO Recommendation on the Ethics of Artificial Intelligence

  • OECD AI Principles

  • Toronto Declaration

True or False: It is okay to use a GPT to write a research proposal on a topic you have no experience in?

Hint: Review "Using AI Ethically"

False

If you do not have the ability to verify output truthfully or accurately, it is not safe to use a GPT for research.