Beyond the Paper: Rethinking Academic Communication in the Age of AI

By Luis Lozano-Paredes

This is my first Substack article. I’ve been meaning to start this for a while, but this particular thought has been living rent-free in my head, so here we are. If I’m going to start a space called The Reflexive Machine, this feels like the right kind of opening question: Are we seeing the end of the written academic paper?


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A quick note on the title—The Reflexive Machine—before we dive in:

The Reflexive Machine explores how AI, society, and knowledge production are co-evolving. Drawing from cybernetics, STS, AI & society research, and governance, this space examines how these machines—far from being neutral tools—shape and are shaped by human inquiry, decision-making, and design:

• Reflexive → Feedback loops, institutional adaptation, and the co-production of knowledge.

• Machine → AI, automation, and socio-technical systems as active epistemic agents.

This isn’t just about AI in academia. It’s about how computational thinking meets design thinking, how AI reshapes governance and urban systems, and how digital infrastructures mediate power, knowledge, and public life.

From AI-mediated scholarship to platformed governance to interactive urban AI, The Reflexive Machine is a space for thinking out loud about where all of this is heading.

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Now to the article:

Is the Written Paper Dying?

For centuries, academic discourse has revolved around one thing: text. More recently, the journal article, monographs, and conference papers have been the bedrock of scholarly communication.

But we’re at a strange moment now. AI can apparently already produce high-quality academic writing with citations and arguments that (at first glance) hold up to scrutiny. What happens when writing isn’t the core intellectual activity of scholars anymore?

With platforms like OpenAI's Deep Research automating more of the article-writing process, how will this shape the role of publications in promotion, tenure, and the broader academic bean-counting game?

This isn’t about AI "replacing" academics (we’ve heard alarmists take it a thousand times). The more interesting question is:

What if text loses its primacy as the default mode of knowledge production?

AI as Co-Author, Thought Partner, or Something Else?

We’re already seeing shifts in how AI is integrated into research workflows. It’s no longer just a tool for spell-checking or summarising papers; it’s generating insights, synthesising literature, and sometimes even producing the bulk of an argument.

At what point does an AI move from being a tool to being a collaborator?

There’s a tension here:

• If AI can generate novel insights (debatable), does that challenge human authorship itself?

• How do academic institutions respond if professional progression and funding are still structured around human authorship?

Right now, most journals have drawn a line: AI can assist, but it can’t be listed as an author. The justification is that AI lacks "accountability"—but let’s be honest, academia has seen plenty of human authors evade responsibility for errors or misconduct. The real issue is that our academic institutions are built on structures that assume writing is where scholarly labour happens. What if that assumption is no longer valid?

The Return of Oral and Embodied Knowledge

Before we had the academic journal, scholarship was oral. Think Socratic dialogues, disputations, and public lectures. Knowledge was embodied, not just written down.

Weirdly, we’re looping back to that model—except this time, it’s mediated through podcasts, live-streamed discussions, and AI-assisted dialogues.

Woodcut depicting a disputation between Christian and Jewish scholars, carved by Johann von Armssheim in 1483. Public domain image via Wikimedia Commons.

We’re already seeing this shift:

• Academic podcasts are shaping discourse in ways that rival journal articles. Scholars are being heard, not just read.

• Performative scholarship is on the rise. AI-generated debates, VR-enhanced research presentations, and interactive lectures could create ways to engage with ideas beyond static text.

• Real-time peer review is becoming possible. Imagine presenting your work in a live forum, with AI summarising critiques, mapping counterarguments, and generating instant revisions.

This doesn’t mean the written word disappears. But it does mean it’s losing its monopoly on academic legitimacy.

Any alternatives? and here is where speculation about potential futures starts:

Interactive Knowledge Maps & Hyperlinked Research

Academic papers are fundamentally linear. They present an argument from start to finish. But what if research wasn’t something you "read" but something you explored?

We could see experiments with:

Hyperlinked research graphs, where every reference is clickable, turning a static paper into a living knowledge network.

AI-powered knowledge maps could allow researchers to interact dynamically with a field of study rather than parsing dozens of disconnected PDFs.

Living documents that evolve over time, with AI and human continuously updating literature reviews and integrating new findings.

The idea of a "final" research paper may soon seem outdated. We might be heading toward a world where research is a networked, evolving process—not a fixed output.

What Comes Next?

This might not be the (total) end of the academic paper. But it is the beginning of something different.

We might be moving toward a hybrid model of knowledge production where:

• AI is an active participant (actant) in research—not just a tool.

• Oral, visual, and interactive forms of knowledge might gain legitimacy.

• The traditional peer review model is challenged by real-time, AI-assisted critique.

The big question isn’t whether this transformation is happening. It is. The question is:

Are we ready to move beyond the written page?

Let’s Keep the Conversation Going

This is just the first article on The Reflexive Machine. I’ll be exploring AI-mediated scholarship, interactive knowledge systems, platformed, digital and AI governance in cities and nations, and what this means for how we produce and validate knowledge.

If this resonates, subscribe and join the conversation. I’d love to hear your thoughts:

Are you already seeing these shifts in your field?
How do you think academia will adapt (or resist)?
What excites—or terrifies—you about the future of AI in scholarship?