Making Sense of AI: An anthology of language, metaphor and public understanding

Over the last decade, between May 2016 and May 2026, I have written about 50 blog posts about AI and metaphor spanning a large variety of topics, from recording emerging metaphors, describing shifts and changes in metaphors and discussing their impacts on science and society. I have now sorted these posts into categories so that they can be accessed and read more easily. If you want a more readable version, here is a webpage.

***

This is a thematic reading guide to posts on artificial intelligence, metaphor, and public understanding collected from the blog Making Science Public by Brigitte Nerlich.

Themes in this guide

1. Origins & Early Encounters
2. Metaphors: The Core Thread
   • Using metaphors to think about AI
   • Using metaphors to build AI
   • Thinking with AIs about metaphors
3. Language, Words & Meaning
4. AI Meets Biology
5. AI in Society & Culture
6. Ethics, Safety & Governance
7. Overviews & Reflections

How to use this guide. The posts below are grouped by theme rather than chronology. Within each section, entries are ordered to build on one another where possible. Each post stands alone, but readers interested in the core metaphor thread are encouraged to start with Section 2 and read it through. Posts marked ‘guest’ were written by invited contributors. Posts marked ‘series’ form a trilogy or sequence.

SECTION ONE: Origins and Early Encounters

The blog’s engagement with AI did not begin in 2023 with ChatGPT. The posts in this section show a longer view; from early algorithmic unease in 2016 through to the first encounter with generative AI and the curiosity it sparked.

• May 2016 The ghost in the machine: Of automation, algorithms and AI An early post asking what it means when machines do things we cannot fully explain. This was written before generative AI was a household concern, but the ‘ghost in the machine’ metaphor already does important work here.
• Sep 2018 Anticipating public reactions to emerging sciences and technologies: Nano, synbio and AI Drawing on my experience with nanotechnology and synthetic biology engagement, this post asks whether we can anticipate how publics will react to AI and what lessons earlier controversies offer.
• Sep 2020 Mutant algorithms This post deals with early anxieties about automating decision making in the grading of A level assessments, exacerbated by Boris Johnson’s use of the phrase ‘mutant algorithm’.
• Dec 2021 AI and the (public) understanding of science Prompted by a wave of AI-generated artwork, this post begins asking what AI means for how science is communicated and understood.
• Jan 2023 Artificial Intelligence: Education and entertainment This is the blog’s first post in the ChatGPT era after a first encounter with the new wave of generative AI over Christmas 2022. It asks what it might mean for education, communication and daily intellectual life, providing early reflections on the dangers of ‘knowledge pollution’.
• Feb 2025 When the world falls apart, enjoy a metaphor! A reflective post on why metaphor-watching has become a personal as well as intellectual refuge and how AI became central to that project.

SECTION TWO: Metaphors: The Core Thread

This is the core of the Making Science Public blog’s AI coverage. This thread documents a sustained, evolving investigation into how metaphors shape what we think AI is, can do, and should do. From early hunts for metaphors in the wild, through thematic studies of specific metaphor families, to calls for systematic observation. The posts are sorted thematically and within the themes chronologically. The three sub-themes below are not watertight as many posts straddle more than one theme, but they offer a useful orientation.

Metaphors we use to think about AI

These posts study the metaphors that circulate in public and media discourse, in journalism, social media, general commentary, and shape how non-specialists imagine what AI is and what it means.

• Apr 2024 Hunting for AI metaphors A systematic foray into the metaphor landscape based on collecting, sorting and beginning to analyse the metaphors that writers, technologists and commentators use to make AI legible.
• Aug 2024 AI, LLMs and an explosion of metaphors As AI discourse intensified, so did its metaphor density. This post surveys the proliferation and asks: what does it mean when a technology attracts so many different imaginative frameworks at once?
• Jan 2025 Food for thought: AI and culinary metaphors A thematic study of food and digestion as metaphors for AI, framing, for example, training data as food, models as consumers, outputs as produce and more.
• Jan 2026 From sloppers to slopocalypse: The lexical productivity of AI slop A close analysis of ‘slop’, a word that crystallised anxieties about low-quality AI-generated content, and its remarkable semantic fertility. Companion to the enshittification post in Section 3.
• Feb 2026 Metaphors for AI: Networks, holes and loops A reflection on the epistemological role of metaphor itself as nets cast over AI to produce provisional understanding, and what happens when they fray.
• Feb 2026 Making and unmaking AI metaphors and magic This post revisits a classic paper by Noel and Amanda Sharkey on AI and natural magic and shows how AI has always invited magical thinking, and what it costs us when we indulge it.
• Apr 2026 Is ‘cultural technology’ a metaphor for AI? Prompted by John Naughton’s Observer piece on ten AI metaphors, this post examines whether ‘cultural technology’, a more neutral, anthropological framing, offers something useful.
• Apr 2026 ‘Habsburg AI’: Portrait of a metaphor and its family This post traces the genealogy of a single viral metaphor, ‘Habsburg AI’, and what it reveals about how critical AI discourse is conducted.
• Nov 2025 Metaphors for AI: Three blog posts and a summary (series) A short overview and entry point for the trilogy below.
• Nov 2025 Making the case for an AI metaphor observatory (series) A programmatic statement about why metaphor-watching needs to become systematic, collective and institutionalised. Part one of a research trilogy.
• Nov 2025 Metaphors for AI: An overview of recent studies (series) A survey of the academic landscape summarising what topics scholars were working on with regard to AI metaphors (up to 2025), and where the gaps remain. Part two of the trilogy.
• Nov 2025 Observing shifts in metaphors for AI: What changed and why it matters (series) The third part of the trilogy. It tracks how the metaphors used for AI have shifted since 2022 and arguing for the significance of those shifts for public understanding.
• Apr 2026 AI through a bilingual lens: Metaphors in Italian and English (guest) By Barbara Gabriella Renzi and Giulio Napolitano. A comparative study showing that AI metaphors are not universal and that language and culture shape the imaginative frameworks available to us.
• June 2026 Stochastic flock: A new AI metaphor This post grapples with a new metaphor encapsulating the ‘behaviour’ of swarms of interacting AI agents, a metaphor that builds on the older one of stochastic parrot that itself grappled with the appearance of chatbots in our midst and creating new forms of human-computer interactions.

Metaphors we use to build AI

These posts deal with metaphors that originate inside the technical practice of AI and are mainly used by researchers, engineers and developers to describe, design and reason about AI systems. These often cross over into public discourse, carrying their technical assumptions with them.

• Apr 2024 From contamination to collapse: On the trail of a new AI metaphor Tracing the emergence of ‘model collapse’ and related contamination metaphors and showing how a technical concept becomes culturally loaded through the language used to describe it.
• Jun 2024 Metaphor identification: From manual to automatic This is a more technical look into the ways that metaphors have been identified, from manual to automatic analysis, and from Lakoff and Johnson in the 1980s to the use of LLMs now via natural language processing and computational linguistics.
• Mar 2026 Metaphors AIs live by This post explores not just what metaphors humans use for AI, but what metaphors AI models deploy internally. An intriguing look at the metaphorical furniture built into the systems themselves.
• Apr 2026 Sandboxes and moats: Wrestling with AI metaphors Two field-internal metaphors are examined for what they reveal about how AI developers frame safety and strategy: ‘sandbox’ (a safe testing environment) and ‘moat’ (a competitive advantage).
• Apr 2026 Vibe-coding spaghetti: Unpacking an AI metaphor for biology Sparked by a viral tweet, claiming that “DNA is 4 billion year old, completely undocumented, vibe-coded spaghetti”, this post unpacks how AI developer vocabulary is being borrowed to re-describe biology itself. (This links up with section 4 where AI meets biology)

Thinking with AIs about metaphors

A distinctive strand in which AI systems become active participants in metaphor analysis; where they are not just objects of analysis but interlocutors. These posts raise interesting questions about what it means to ask a machine about its own language.

• Mar 2023 Chatting with a chatbot about metaphor An early (and quite amusing) Chat with ChatGPT about the nature, creation and processing of metaphors, including reflections on pattern recognition.
• Oct 2023 ChatGPT and its magical metaphors A discussion with ChatGPT about the metaphors it would use to describe itself which revealed that it indulged in a lot of magical metaphors

• Jul 2024 Talking with Claude about machine metaphors in biology Using Claude to explore how machine metaphors operate in biology and asking what an AI makes of the metaphors used to describe processes that AI itself is now being used to model. (See also section 4)
• Feb 2026 Moltbook: Snapshots of a metaphorical firework A snapshot of the metaphor explosion that greeted Moltbook, a social network for AIs capturing in miniature how quickly and wildly metaphors multiply around AI novelties, with AI as both subject and occasional commentator.

SECTION THREE: Language, Words and Meaning

Beyond metaphor, these posts dig into specific words, linguistic phenomena, and the relationship between how we talk about AI and how we think about it. Polysemy, prompts, neologisms and the politics of naming.

• Jan 2023 Artificial intelligence, dark matter and common sense In this post I dissect the quite unique metaphor of ‘common sense as the dark matter of AI’. This includes a discussion with ChatGPT about that metaphor (and a mistake it makes)
• Oct 2023 Around the first AI safety summit there was a lot of talk of ‘frontier’ models. But what does that word actually mean and imply for AI risks and safety?
• Oct 2023 Super-computers and super-intelligence: When frontiers collide This post, a collaboration with Alan Miguel Valdez, explores the concept of frontier further and links it to the concept of the US frontier myth.
• Jun 2024 How to do things with prompts: Magic words, speech acts and AI Drawing on J. L. Austin’s speech act theory the post asks what prompts actually do and why the language of “magic words” is both apt and revealing about how we imagine our relationship with AI.
• Sep 2024 Intelligence A meditation on the word ‘intelligence’ itself whose endless meanings make precise definition both necessary and elusive.
• Feb 2024 Truth, post-truth, and post-fake What happens to truth and the language of truth when AI can generate plausible-sounding falsehoods at scale? An examination of a vocabulary under pressure.
• Oct 2025 Enshittification: A word for our times A linguistic autopsy of one of the era’s most distinctive coinages. It traces its origin, spread and meaning, and what it tells us about collective anxieties around platform and AI degradation. (See also ‘slop’ in section 2)
• May 2026 ‘Fake’: From murky origins to murky future A companion to the post on truth and post-truth, this post traces the word ‘fake’ from its murky origins in 18th-century criminal slang, through ‘fake news’ and ‘deepfakes’, to the current crisis of reality in the age of generative AI.
• Jan 2026 AI veganism: A new dietary metaphor for a new type of discourse The post uses the emergence of “AI vegan”, a new phrase meaning someone who refuses AI-generated content on ethical grounds, as a window into how moral identities are being constructed around AI choices.
• Aug 2025 Vibes: From new age to new algorithms The curious career of ‘vibes’, from spiritual informality to “vibe-coding”, is used as a case study to trace how vernacular words get drafted into technical AI discourse.
• May 2026 Polysemy, power and ethics in AI discourse (series) This post introduces a key paper on “strategic polysemy”, the deliberate exploitation of multiple meanings in AI discourse for purposes of hype and power. Part one of a two-part sequence.
• May 2026 Polysemy, safety and epistemic risks in AI discourse (series) This post extends the polysemy analysis to AI safety discourse and shows how the same word can mean radically different things to different actors, with real consequences for governance.
• May 2026 AI literacy and the case for polysemy awareness (series) This post makes the case that awareness polysemy literacy, awareness of how multiple meanings of AI concepts emerge and are used, should be a core component of AI literacy education alongside metaphor awareness.
• June 2026 Polysemy, pragmatics and puppetry: What AI can learn from ethnomethodology (series) This is the last post in the polysemy series in which I go back to the 1970s to explore how an expert in the study of social interaction foresaw, the pitfalls of AI systems. 

SECTION FOUR: AI Meets Biology

A thread drawing on my long experience in studying the language of genetics and genomics. What happens when the vocabularies of molecular biology and AI begin to borrow from each other?

• Oct 2023 The language of life meets large language models A first exploration of the convergence between DNA-as-language metaphors and LLM terminology. This convergence turns out to be both intellectually productive and conceptually treacherous.
• Jul 2024 Large language models, meaning and maths Inspired by Benjamin Labatut’s novels on mathematics and science, this post asks deep questions about meaning in LLMs and whether mathematical structure can bear the weight we place on it.
• Aug 2024 From large language models to DNA language models As researchers began applying LLM architectures to genomic sequences, the metaphor of ‘DNA language models’ raised profound questions about meaning, translation and what it means to ‘understand’ a genome.
• Mar 2026 Metaphors in AI and genomics: Going beyond blueprints and parrots A synthesis comparing the history of metaphor in genetics (blueprints, codes, programmes) with the current metaphor ecology of AI (parrots, assistants, minds) to draw lessons about communication and risk.
• Jan 2025 Synthetic biology in the era of AI: From dominating nature to collaborating with it (guest) By Christian Gude. A guest post from a synthetic biologist asking how AI is changing the field’s self-understanding and whether the controlling metaphors of synthetic biology are shifting as a result.
• Dec 2024 Chatting with a cockroach A playful post on chatting with a cockroach through the medium of AI at the Cambridge Museum of Zoology and the implications this may have for science communication.

SECTION FIVE: AI in Society and Culture

How AI is being absorbed into culture, identity and everyday life, from the social dynamics of AI-model naming to what AI chatbots do to our sense of relationship and truth.

• Apr 2023 LLaMas, Alpacas and Dolly 2.0: Exploring an emerging AI menagerie The naming of AI models as animals, such as llamas, alpacas or falcons as a cultural phenomenon. What does this metaphor family tell us about how the field sees itself?
• Aug 2023 Red and blue AI? An experimental and speculative post drawing an analogy between the political polarisation of GM crops (GM for food and GM for medicine) and the emerging cultural divisions around AI (AI for writing and AI for medicine).
• Jan 2024 Humanising artificial intelligence and dehumanising actual intelligence An analysis of the double movement in AI discourse: as we project human qualities onto machines, we risk diminishing what is genuinely human.
• Oct 2024 Playing with AI/Playing with fire Reflecting on the word ‘playing’, how the playfulness of early AI interactions conceals real dangers, and how the experimental framing both enables and disguises what we are doing.
• Oct 2024 Superintelligence: From the divine to the digital and back again Tracing “superintelligence” from its theological roots to Sam Altman’s recent pronouncements and showing how this concept carries far older anxieties about the creation of something beyond our control.
• Dec 2023 Climate change, metaphors and me A personal and methodological reflection linking my earlier work on climate change communication to the new project on AI and showing the continuity of concerns beneath different subject matters.
• Nov 2024 Chatting with chatbots about the climate crisis An experiment in using AI to discuss climate change and in what AI-mediated conversation reveals about how we think about, and feel about, a vast and difficult subject.
• Sep 2025 Understanding computational hermeneutics: Making meaning between the past and the present Engaging with a complex paper on “computational hermeneutics” (and with Gadamer and Dilthey), this rather philosophical post asks whether interpretation/understanding is something AI can genuinely do.
• Nov 2025 Parasocial Relationships: Problematic Practice or Public Promise? (guest) By Andrew Maynard. On ‘parasocial’ becoming Cambridge Dictionary’s 2025 Word of the Year and what it means that our growing attachments to AI chatbots have a name.

SECTION SIX: Ethics, Safety and Governance

How AI risk, responsibility and regulation are being imagined, argued over and framed. These posts engage with the policy and ethics debates directly through the lens of language and public understanding.

• May 2023 Bridge or Barrier: Does generative AI contribute to more culturally inclusive higher education and research? (guest) By Dimitrinka Atanasova. An early examination of whether AI tools help or harm researchers from non-Anglophone backgrounds — a practical equity question often absent from mainstream AI ethics discourse.
• Jun 2023 Artificial intelligence and existential risk: From alarm to alignment A critical examination of the “existential risk” framing, focusing on how the term functions rhetorically, what it closes down as well as opens up, and the journey from alarm to the more procedural language of “alignment.”
• Nov 2023 The human side of AI: Delivery robots in Milton Keynes (guest) By Alan Miguel Valdez. Against the backdrop of the Bletchley Park AI Safety Summit, this post brings AI back to the pavement level, namely literal robots, actual communities, and what governance means on the ground.
• Feb 2024 Responsible AI to the max: Meet Goody-2 This is a post on Goody-2, the satirical AI that refused every request on safety grounds. It is a humorous intervention in the responsible-AI debate and reveals its contradictions from the inside.
• May 2024 AI safety: It’s everywhere but what is it? This post surveys the rapid proliferation of “AI safety” as a term and asks quite urgently what it actually means across its very different uses.
• Jun 2025 Public engagement with AI: Some obstacles and paradoxes Reporting on a social-science webinar on what AI researchers say about public reception of AI, the post examines the tensions between institutional engagement rhetoric and actual practice.
• Aug 2025 AI winter and AI bubble: Historical and metaphorical reflections Looking at the history of AI hype cycles through two salient metaphors, that of ‘winter’ and that of ‘bubble’, and asking what they tell us about whether the current moment is different, or the same old story.
• Sep 2025 Participation at the core: AI, ELSI and community engagement This post engages with Alondra Nelson’s proposal to apply the genomics ELSI framework to AI and reflects on technology governance, engagement and public participation with a difficult topic.

SECTION SEVEN: Annual Overviews and Reflections

Each year I write a round-up of all the posts written during that year and all the topics I have covered, from genomics and climate change to infectious diseases and AI. These summaries are useful entry points for any given year’s preoccupations. Together they form a record of how AI (and the blog’s engagement with it) has evolved.

• Dec 2023 Making Science Public 2023: End-of-year round-up The year AI became something we could all use and were all talking about. A useful map of the blog’s first intensive year of AI coverage.
• Dec 2024 Making Science Public 2024: End-of-year round-up A year in which the metaphor project deepened and the AI-and-biology thread emerged strongly. Also covers non-AI posts for readers interested in the broader scope of the blog.
• Dec 2025 Making Science Public 2025: End-of-year round-up The year of the metaphor observatory trilogy, enshittification, vibes, AI veganism, and a blog migration.

All posts by Brigitte Nerlich unless otherwise noted  ·  Making Science Public

Reading guide compiled June 2026

Image: Pxhere