Ethics · Cognition · Judgment

Artificial intelligence,cognition and critical thinking.

A starting point for exploring how we think with artificial intelligence: what we mean by reasoning, what we need to test, and which responsibilities we cannot delegate.

Explore research themes
02

Research themes

Questions for a technology that also defines us.

Three connected areas for studying not only what AI systems do, but which claims we can justify about them and which responsibilities we assume when using them.

01

Ethical evaluation

Examining the criteria we use to assess systems, decisions, and consequences.

What does sound evaluation mean for a technology that changes as we observe it?

02

Cognitive evidence

Distinguishing observable behaviour, functional capability, and attributions of thought.

What evidence would justify speaking of reasoning without mistaking it for its appearance?

03

Data governance

Examining who collects information, for which purposes, for how long, and under which limits.

How does power shift when personal data is no longer under the control of individuals?

A discipline of analysis

From the question to its implications.

An open working framework for organising research, making assumptions visible, and separating claims from the evidence that supports them.

  1. Question

    Frame the problem and define exactly what is being claimed.

  2. Test

    Gather evidence and look for alternative explanations.

  3. Evaluate

    Examine values, risks, responsibilities, and limits.

  4. Translate

    Turn the analysis into clear and useful implications.

Data governance

Analytical frameworks, not promises of output.

01

Data minimisation

Collect only the data needed for a clearly defined purpose.

02

Storage limitation

Define from the outset how long data is kept and when it will be deleted.

03

No data trade

Do not treat personal data as a commodity available to buy and sell.

This framework draws on the three measures Carissa Véliz proposes for governing privacy: data minimisation, storage limitation, and banning trade in personal data.

Reading framework

A genealogy for thinking about and questioning AI.

References that help distinguish intelligence, rationality, understanding, and judgment. This map guides the line of study; it does not present these works as original output.

Starting point

  1. 1950

    Alan Turing · Computing Machinery and Intelligence

    Reframes the question of machine thought through the imitation game.

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  2. 1955–56

    John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon · Dartmouth Summer Research Project on Artificial Intelligence

    Introduces the term artificial intelligence and the conjecture that founded the field.

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Critical thinking

  1. 1962

    Robert H. Ennis · A Concept of Critical Thinking

    Places the evaluation of claims and precise formulation of questions at the centre of critical thinking.

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  2. 1991–2003

    Matthew Lipman · Thinking in Education

    Connects critical thinking, criteria, dialogue, and the formation of judgment.

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  3. 2019

    Keith E. Stanovich, Maggie E. Toplak, and Richard F. West · Intelligence and Rationality

    Distinguishes intellectual ability from rational thought and its specific assessment.

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  4. 2019

    Deanna Kuhn · Critical Thinking as Discourse

    Understands critical thinking as a dialogical practice of argument and examination.

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  5. 2021

    Steven Pinker · Rationality

    Brings together logic, probability, causal inference, and decision-making tools for examining how we reason.

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Critiques of AI

  1. 1972–92

    Hubert L. Dreyfus · What Computers Still Can’t Do

    Questions whether human intelligence can be reduced to formal rules without embodiment, context, or experience.

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  2. 1976

    Joseph Weizenbaum · Computer Power and Human Reason

    Distinguishes computational power from the human responsibility to judge.

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  3. 1980

    John R. Searle · Minds, Brains, and Programs

    Questions whether correct symbol manipulation is sufficient for understanding.

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  4. 2016

    Shannon Vallor · Technology and the Virtues

    Argues for technomoral wisdom and practical judgment in relation to emerging technologies.

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  5. 2021

    Emily M. Bender, Timnit Gebru, and co-authors · On the Dangers of Stochastic Parrots

    Warns against attributing understanding to language models based on fluent output.

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Profile

Anabel Alcaide Acevedo

She is developing a personal line of study around the ethics of artificial intelligence. Her interest centres on how we distinguish evidence from appearance when attributing reasoning to systems, and on the responsibilities that arise from their use in decision-making.

This first version presents the research territory. An academic biography and documented work will be added at a later stage.

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