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Generative artificial intelligence: The Times and Sunday Times editorial guidelines
As we explore the potential of generative artificial intelligence our commitment is to uphold our high editorial standards.
Generative AI in a Nutshell - how to survive and thrive in the age of AI
More Than a Tool
What We Learned from a Year of Conversations About AI
Journal investigating paper on cognitive impact of generative AI
A paper about the effects of generative AI use on confidence in work tasks is under investigation after critics raised questions about the study design, data analysis and ethics approval for the re…
Ars Technica's policy on generative AI
How Ars Technica uses, and doesn't use, generative AI.
The abstraction you didn't ask for
When I say 'generative AI isn't going away,' people hear 'and you have to like it.' You don't, and you might be right not to. But the is-ought divide here is real and we should all be preparing for both outcomes.
Where does the rigor go? Research software and the future of trustworthy science.
Generative AI now makes it dramatically easier to produce something that looks like research: analysis code, figures, literature reviews, even whole pap…
Language Machines
How generative AI systems capture a core function of language Looking at the emergence of generative AI, Language Machines presents a new theory of meaning i...
Standards around generative AI
Accuracy, fairness and speed are the guiding values for AP’s news report, and we believe the mindful use of artificial intelligence can serve these values and over time improve how we work.
AI is turning research into a scientific monoculture
Generative AI deserves scientific attention. But the rush to study it is producing a feedback loop of topical and methodological convergence, flattening scientific imagination and crowding out the pluralism needed to keep research adaptive, resilient, and intellectually generative.
In spite of hype, many companies are moving cautiously when it comes to generative AI | TechCrunch
Companies are extremely interested in generative AI as vendors push potential benefits, but turning that desire from a proof of concept into a working product is proving much more challenging.
Glossary of Terms: Generative AI Basics - MIT Sloan Teaching & Learning Technologies
Learn key AI terms. This glossary defines and explains important concepts like generative AI, large language model, natural language processing, and more.
Can generative artificial intelligence be considered a cognitive subject? An analytic analysis
This paper examines whether contemporary generative artificial intelligence (GAI), especially large language models (LLMs), can be regarded as a “cognitive subject” in the epistemic sense relevant to the production and endorsement of knowledge claims. GAI systems increasingly participate in writing, research, and decision-making workflows and can display striking competence in information processing and task-directed problem solving. Yet, the thesis that GAI is a cognitive subject is stronger than the observation that GAI contributes as a cognitive tool. Therefore, we propose an explicit set of necessary and sufficient conditions for cognitive subjecthood and evaluate each condition in light of recent philosophical and empirical scholarship. The analysis supports a two-part conclusion: (i) present-day GAI can reasonably be described as a cognitively significant contributor to knowledge production, but (ii) it does not satisfy the conditions for cognitive subjecthood, largely because robust intentionality, metacognitive self-representation, and consciousness-related indicator properties are not established.
Generative AI for Pro-Democracy Platforms · From Novel Chemicals to Opera
Online discourse faces challenges in facilitating substantive and productive political conversations. Recent technologies have explored the potential of generative AI to promote civil discourse, encourage the development of mutual understanding in a discussion, produce . . .
Measuring Usage in the Age of AI - Research Information
Tasha Mellins-Cohen outlines COUNTER Metrics' new guidance for usage metrics associated with generative and agentic AI
“The task that generative A.I. has been most successful at is lowering our expectations, both of the things we read and of ourselves when we write anything for others to read.” — Ted Chiang
Why A.I. Isn’t Going to Make Art
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