The Tech-bro-ification of Research

🍏your Thursday read 22nd May, 2025

A well-researched original piece to get you thinking.

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Hi Scholar,

If the subject line didn’t already give it away, allow us to say it plainly: this essay is about technological optimism in research, the Tech-bro as the figurehead of its so-called revolution, and the Silicon Valley ethos they embody and quietly import into both research practices and researchers themselves.

It’s one of those essays that’s been simmering for a long time, so we’ve also included a bibliography of the reading that’s informed it and screenshots of the materials that have informed our analysis to go along with it.

The Tech-bro-ification of Research

Written by The Critic and The Tatler

We appear to have an imagination problem. And by we, we don’t mean just you and us - our scholarly community. We mean society at large. And the problem of imagination we are referring to is not that we are imagining radically different and improbable things; it’s that we have been robbed of our abilities to imagine differently altogether. 

Today, we can only imagine a world and solutions to the current state of our world that is technological in nature. 

Whether it’s climate change, food scarcity, obesity, road safety, or political dysfunction - every challenge is framed as a problem that technology will solve. As the opening quotes suggest, technology is no longer just a tool; it has become our salvation narrative. It promises to "make the world a better place" and fuel "growth and abundance." 

To be clear - though, frankly, it probably already is - we’re not talking about just any technology. We are referring to modern technology: the Internet, big data, algorithms, and, more recently, artificial intelligence. These are the so-called “technological fixes” that have come to dominate our responses to the world’s problems and, more importantly, the limits of what we can even imagine as a solution. 

Just as the sky is blue, so too is the belief that technology can solve virtually any problem and deliver all the innovation necessary to ensure ‘progress’. Apple’s now-iconic slogan, “There’s an app for that”, is emblematic of this worldview: that technology holds the foundational power to change and enrich our lives. Progress has become virtually synonymous with technological advancement. 

We now live within a paradigm of intense techno-optimism, in which a world shaped and saved by technology feels not only possible, but inevitable and even desirable. 

And if you’re wondering, Scholar, ‘what’s any of this got to do with me?’, let us just lay it bare right here, right now: techno-optimism seeps into every part - every nook and cranny - of our world and society. And we, as scholars, are not immune. 

With each new technological innovation, we have largely accepted the belief that both research and the way we do research is becoming ‘better’: more efficient, more accessible, more advanced. 

When the printing press arrived, the Enlightenment narrative held that knowledge could now spread further, travel faster, and be reproduced more easily. Thereafter, the advent of the World Wide Web provided ‘a means to process, review, and distribute scientific publications at a much lower cost and faster pace’, consequently ‘revolutionising’ scholarly publishing. And when Google Scholar was launched, it allowed us to metrify and index scholarly literature - and once more, it was framed as a solution to navigating the flood of ever-growing published literature. Time and again, the story has been the same: technology improves how we create and share knowledge. And now, with the rise of generative AI, we hear it once more: AI will change research, and the loudest voices are screaming, ‘it will change it for the better.’ 

Of course, adopting technology is not the same as adopting a techno-optimistic worldview. But when the dominant belief is that technology will revolutionize research and knowledge in ways that make it ‘better’, more productive, that’s where the optimism holds strong and steady. 

We are also not of the view that technologies themselves are inherently problematic. But our concern is that the uptake of technological products is never just about functionality. Technological innovations are not developed by neutral, disinterested, value-free actors: they are shaped by specific ideologies, cultures, and worldviews. As a result, the technologies we use come bundled with the cultural imports of the people and institutions who create them. 

Our concern, then, is not with adopting tools but with the uncritical adoption of the values and ideologies that come with them. 

To understand the cultural and ideological imports that academic research invites through its use of new technologies, we must therefore ask: 

‘Who’ is bringing these tools to our desks? 

And with them, what cultural and ideological imports are we quietly welcoming into how we conduct our research, how we produce knowledge, and how we relate to knowledge itself? 

The Figure of the Tech-bro

As is alluded to by the title of this essay, the knights in technologically advanced shining armor riding to our rescue are the Tech-bros. A Tech-bro can belong to any ethnicity, sex, gender or social class - although they are usually white men from upper-middle class families. Regardless of their individual characteristics, a Tech-bro in the purest form is likely to have dropped out of a prestigious university to found a disruptive technology company at a relatively young age. They are idealists, full to the brim with confidence that technological innovation can guarantee boundless profits and societal benefit - and we should trust them for they are at the cutting edge. And we, the rest of society who will benefit from the tech they are developing, idolize them. We are obsessed with what time Sam Altman wakes up, Elon Musk’s favorite books and where Bill Gates thinks the future of the world is going. Perhaps it’s unsurprising that they are bestowed a god-like status: we cannot do without their amazingly useful products and we venerate the extreme wealth they acquire through the successes of their enterprise. 

Just about any individual can become a Tech-bro regardless of their individual characteristics - making their formation a relatively clear case of culture prevailing over nature. 

The Tech-bro is not born; they are made. 

They do not arrive pre-formed in the mother’s womb: they are nurtured into being. And the cultural-womb that makes their formation possible, as we’re sure you already know, is Silicon Valley: 

the sheltered valley where idealistic Ivy League drop-outs find space and support to undergo their metamorphosis. 

But more than a place, 

Silicon Valley is a cultural force. 

It has an ethos and it is this ethos that breathes life into the Tech-bro, who embodies it as the vita activa of their very existence. 

In turn, it is also this very same ethos that the Tech-bro embodies that gets exported everywhere else - into our lives and societies - through the technologies they produce, and we as individuals consume. Accordingly, the ethos of Silicon Valley has slowly spread beyond its geographical borders and taken root in our collective imagination.

The techno-optimism that defines our time, Scholar, is underpinned by the Silicon Valley ethos.

Let us spend a few moments then to see what this ethos really is, and how it’s come to be.

 The Silicon Valley Ethos 

The Silicon Valley ethos is a strange fusion of ideas: combining values from 1960s counterculture with the Friedman Doctrine that came to dominate economic thinking from the 1970s onward.

To understand the cultural currents that emerged during the 1960s, we need only to recall the global upheavals of that era. The Cold War and nuclear arms race was in full swing. Across the world from Africa to Latin America to Asia, nations were fighting wars of liberation against the imperial powers that had long ruled over them. In the United States, the Civil Rights Movement was confronting segregation. Second wave feminism had emerged and was gaining momentum. People at large were experiencing and witnessing disruption and change. 

Accordingly, it was a time defined by experimentation, the rejection of traditional authority, and a commitment to ideals of social justice and equality. Within the counterculture, these forces coalesced into a strong anti-establishment sentiment: one that was especially critical of ‘the state’, rooted in opposition to the wars going on at the time. 

Alongside this ‘anti-state’ sentiment, counterculture also developed a distinctive attitude toward technology. During the Cold War, military power was becoming increasingly technological; weapons were increasingly made more sophisticated through their fusion with computers. The counterculture rejected this “establishment technology” - technology developed for war - and instead advocated for human-centred “small-scale technology”. 

The Whole Earth Catalogue (WEC), a magazine popular within the counterculture, played a central role in promoting and fostering this alternative attitude to technology. The WEC contained reviews and information about various products, as well as essays and editorials. It promoted self-sufficiency, a do-it-yourself attitude and the idea that the use of ‘tools’ could foster togetherness and community. The term ‘tools’ was defined broadly by the WEC and ranged from books and calculators to wildflower seeds and psychedelic drugs. But more important than the tools that were promoted was the endorsement of the belief that people should be able to access them and that tools should benefit their users. Its slogan, “access to tools”, captured this mission perfectly. 

It is from these roots that the philosophy underpinning the modern Tech-bro has emerged.

We see it in a fondness for disrupting the status quo. 
We see it in the dislike and distrust of institutional authority and governmental oversight, frequently portrayed as a hindrance to progress. 
And we see it in the belief that technological innovation can make society more equitable and more just. 

These values are still very much present and active in shaping the way Silicon Valley conceives of and positions its technological products. 

Through the development and adoption of technology, there is a prevailing belief that we will become more independent, more self-sufficient, and more connected. 

In addition to its counter-cultural roots, the Silicon Valley ethos has obviously been shaped by neoliberalism. At the heart of neoliberal thought is the idea - famously articulated by Milton Friedman in a New York Times editorial - that the sole responsibility of business is to increase its profits. In a free-market driven by competition, the ones who succeed - in other words, make the largest profits - are the ones who move the fastest, produce the most while using the least resources, and waste no time. Accordingly, the neoliberal regime is defined by its obsession with speed, efficiency, competition, and productivity. 

This is the more familiar side of Silicon Valley - perhaps even the less surprising - given that these logics have come to govern not only corporations but also governments, universities, and society at large. For the Tech-bro, the neoliberal logic is not only the operating manual for how to run their company, but also the blueprint for how society at large should function and by extension, how their technological innovations will help bring that vision to life. 

While counterculture ideals and neoliberal market logic may seem an unlikely pair, these seemingly divergent philosophies have found a home - a harmony - in Silicon Valley and in the Tech-bros who thrive there. This juxtaposition is perhaps why the Tech-bro believes he can save the world and still become a billionaire at the same time. 

Such is the Silicon Valley ethos: 

an ideology which is centred around the advocacy for collective progress through technological innovation all the while embracing the neoliberal imperatives of efficiency, profit-seeking and speed. 

This is the ethos that the Tech-bro lives and breathes. It is with these ideals - this vision - that the Philosopher-Kings of Silicon Valley build their technological products and unleash them into society for public consumption. And so, these ideals shape the messaging around how we should use their products, and by extension, how they promise to change our lives. Every aspect of life, from who we go on dates with to the music we listen to, has been touched by the Tech-bro and his products. 

And now, the Tech-bro's influence is seeping into academic research. 

It is this import of Tech-bro ideals into academic research that we are calling the ‘Tech-bro-fication’ of research. 

The Tech-bro-ification of Research

The ‘ed-tech’ industry has for a long time been the playing ground of the Tech-bro. Education, like everything else, is seen as a system ripe for disruption. It is no surprise, therefore, that time and again Silicon Ventures promise to transform how teaching and learning are delivered: bringing with them the same ethos of optimization, efficiency, and technological solutionism. 

One such project we encountered claims to solve attention issues in classrooms using eye-tracking technology: it monitors, in minute detail, where a child is looking during class, ensuring they remain focused on what is being taught. This is in keeping with typical Tech-bro ideals: coding every activity into a calculable data point that can be leveraged and optimized for greater efficiency and productivity. 

More recently, developments in generative AI technology has given the Tech-bro even more reason to be optimistic about ed-tech. But this time, it’s not just the activities of teaching and learning that are the focus of their technological inventions. It’s research - our very processes and practices of knowledge making - that they intend to completely ‘transform’ and ‘revolutionise’. Eric Schmidt - former Google CEO wrote in the MIT Technology Review:

“AI can rewrite the scientific process.”

To be fair to Schmidt, in the same breath that he argues that AI is going to transform scientific research, he also concedes that the core of the research process is going to remain the same. Quoting directly from his article: 

“At its core, the scientific process we all learned in elementary school will remain the same: conduct background research, identify a hypothesis, test it through experimentation, analyze the collected data, and reach a conclusion.”

It is only that, as he adds, 

“AI has the potential to revolutionize how each of these components looks in the future.”

The important thing to stress here, however, is that the so-called ‘revolution’ does not lie in the mere existence of these technologies as products. A piece of technology, on its own, is arguably neutral. You know the famous argument: you can use a hammer to kill someone or you can use a hammer to put a nail into a wall to hang a picture. The tool itself is not the issue. 

What matters more, in our view, is the way the Tech-bro presents his technological offering. It is the ‘messaging’ - the discourse - surrounding how we should use these tools that deserves our attention.

The Tech-bro defines the problem that the technology is supposedly solving. They set the terms for what counts as a “solution” and how it should be achieved. In doing so, they shape the very way we come to think about our work. This is where the real revolution is taking place: not in the tool itself, but in the framing of its application. 

In other words: it's not just the tools, it's their branding and marketing. 

The power of the Tech-bro lies in the way they package and promote these tools. 

The transformation they claim to offer is pre-scripted through marketing: what the tool is for, how it should be used, and what kind of researcher it will help you become. 

Through this messaging, the Tech-bro imports their culture and ideology into our research practices: shaping how we research, how we think about our research, and how we relate to the very idea of research itself.

Perhaps all this talk of discourse and branding and messaging is getting a bit ‘meta’, a little too conceptually dense. So allow us to show you what we mean in practice. In what follows, we take a closer look at how the branding of the myriad of recently released AI-powered tools is promising to “revolutionise” the various components of the research process Schmidt outlines. While we focus on a few examples in detail, the broader set - a sort of visual bibliography - that informs our analysis can be accessed here. 

A Glorious Revolution 

For our first example, we turn to what is contained in a recent promotional email we received from Consensus, signed by its CEO and co-founder. The subject line reads: 

“🧵Introducing Threads: A New Way to Interact with Scientific Literature”

Upon opening the email, the first thing at the top is the logo and text that reads ‘Find the best science, faster’:

Within the first 2 seconds that the email is seen and opened, the co-founder of Consensus has made three promises to us, a researcher on their mailing list. First, they have a new way for us to interact with scientific literature. Sounds exciting. We find the second and third promises in the Consensus slogan. We are told that not only is there such a thing as “the best” science (which also pre-supposes a not-so-good science), but that their product will help us find it faster. The second and third promises are the most telling: they lie at the heart of the so-called revolution this CEO is marketing. As the company’s ‘tag-line’, it expresses the core ambition of what this product is attempting to do to the research process itself.

Reading through the email, the tirade of promises continues. A description of the new feature reads: 

“It’s fast. It’s natural. It’s how research should be.” 

Finally at the bottom, near his signature, we encounter yet another promise: the new way to interact with scientific literature being announced will make

“your research workflow even more seamless and productive” [emphasis added].

What strikes us is not just the repetition of Tech-bro ideals (efficiency, speed, optimisation) but the tone of prescription: what research “should” be. This becomes even more significant when we turn to the Consensus “About” page. Nestled among the classic Tech-bro mission of building “a product that would democratize access to science” is a line that reads: 

“We deeply love and appreciate the value of consuming evidence-based content. However, it felt inaccessible to us, we didn’t have the skills (or the attention span) to find and process the information with traditional academic tools.” [emphasis added]

Whether this is an attempt to be relevant to the Gen Z-ers and Millennials who grew up on social media, we are not sure. Regardless, we think it is worth questioning what authority this person has to declare that research “should” be fast. Why is a Tech-bro telling us how research should be, or what counts as the ‘best’ science, and at what ‘pace’ we should do our research? Tell us, dear Scholar, do you agree with the CEO of Consensus that your research need not require a deep attention from you? That it ‘should’ be done as quickly as possible? 

Let us move on to the next example. If the Tech-bro tells us we ought to do research faster, he also insists that we must save time while doing it. Consider this, taken from the homepage of scite.ai:

Personally, we struggle to see how evaluating research could possibly be a waste of time. What the Tech-bros at scite.ai would label as “wasting time”, we would counter is simply “spending time”. Is their messaging suggesting that evaluating and analysing - the very activity that helps us develop our research questions - is so secondary to the research process that we ought to reduce the amount of time spent on it? It certainly appears to be the case, given the framing of it as a “waste” of time. 

Going down rabbit holes and engaging with seemingly unrelated papers is exactly how scholars are able to produce unexpected insights and ask novel questions. “Wasting time” is how accidental discoveries are made. By framing broad, open-ended reading as a negative, the Tech-bro hands us a vision of research where we must carve out ever more specific niches: a vision which prioritises efficiency over exploration. One where we must isolate ourselves from any part of the knowledge landscape that does not directly concern what we are working on. Why do you think, Scholar? To be more efficient, more productive and save time, of course. 

The productivity revolution in research our Tech-bros are leading extends to the activity of reading literature as well, thanks to tools that promise to generate summaries of research papers in seconds. Paperguide, for example, promises to “cut hours of reading into minutes” and to extract “relevant and significant points to provide meaningful insight.” 

The messaging here suggests that engagement with literature through deep reading is not only a skill unworthy of development, but also an activity undeserving of time.

We feel it necessary to point out that summarizing is never objective - and more importantly, no single summary can ever stand in for engaged reading. When we, as human researchers, summarize papers, we do more than condense. We interpret. We weigh ideas against our questions, refine our direction, and recalibrate what matters as we go. This process - this flux - is vital. What counts as ‘relevant’ or ‘significant’ varies not just between researchers, but between stages of the same project.

The claim that AI summarizers can pick out ‘the relevant’ and ‘the significant’ points of a paper for you, then, collapses under closer scrutiny. The summaries produced are bog-standard, trimmed down versions of information that identify ‘key insights’ based on what the authors themselves have explicitly flagged in the text. This may be useful in certain contexts. But the promise of the Tech-bro is more ambitious: that you can be the same excellent scholar you are today, but with far less time spent on reading - just minutes. 

Promises to reduce hours of reading to minutes encourage a kind of research-as-speed-dating whereby the researcher merely flirts with papers. This framing of how we are to use AI summarizers - advanced by the Tech-bro - puts forward a vision of the researcher whose intellectual grit has been replaced with a superficial engagement with research. 

As a final example of the sort of ‘revolutionising’ taking place in research through our adoption of technology, we turn to AI writing tools now flooding the academic-AI space. 

Given the stylized and formulaic conventions of academic writing, it’s no surprise that large language models (LLMs) - which work by predicting patterns based on probability - can replicate academic writing so successfully. That, Scholar, is not what concerns us. The concern, once again, lies in the messaging: the way the marketing of these tools devalue the role of writing in the research process. Through their promises of speed and automation, they reframe writing not as a form of thinking - a practice that gives our research its form - but as a mechanical task to be outsourced, preferably completed in minutes. 

Recent promotional material from Jenni.ai tells us how long we should be spending on writing papers. One ad reads: “Not all papers need 100+ hours to write.” The visuals for another ad go even further, offering illustrative calendars that suggest you block out just seven hours - rather than thirty - for writing your paper. It’s only an illustration, of course, but the message is clear: you’re doing it wrong if you’re spending too much time writing.

Another piece of messaging encourages users to

“auto-complete your thoughts.”

Here, we see the Tech-bro ethos at its most vivid: even thinking - arguably the most vital part of the research process - can and should be automated. Why bother wrestling with ideas when your tool can finish your sentences for you?

It’s telling that these tools don’t just promise efficiency: they prescribe it.

They tell you how long scholarly work should take. They define what counts as too much time, too much thought, too much care.

According to the Tech-bro, a research paper contributing to our collective understanding of the world should not take 100+ hours. It should be quick, simple, and streamlined. 

This very essay, which is not even a research paper, has taken us more than 100 hours to research and write. By the standards of the Tech-bro, Scholar, we are clearly underperforming.

Resisting the Seductions of The Tech-bro

Scholar, we have travelled a long road through slogans and AI products, through promises of speed and visions of simplicity. If we move beyond the surface-level hype and sensationalism of the Tech-bro’s claims to “revolutionise research,” what we find is not a radical reimagination of scholarly work but something far more familiar. Silicon Valley is not fundamentally revolutionising research; it is merely remaking it in its own image. What is presented as transformation is, in truth, the importation of older logics: speed, productivity, efficiency, now dressed in the sleek robes of AI-tech. 

Let us say it again: the tools themselves are not the problem. What demands scrutiny is the way these tools are presented to us: packaged, promoted, sold. The tools themselves may be powerful. We do not deny their potential. What concerns us is the frame, the discourses that surround them: the marketing, the messaging, the promises. The Tech-bro does not simply offer technology; he offers a worldview. This is the true site of revolution: not in what we use, but in how we’re being trained to conduct our research in specific ways.

The danger is not that AI can summarise an article or generate a paragraph. The danger is when we are told that this is research.

That thinking can be auto-completed. That reading is a waste of time. That knowledge is only valuable if it’s fast.

These messages are not incidental. They are not harmless. They are the marketing of a worldview. Alongside tools, the Tech-bro is also building a narrative. He tells you what kind of researcher you should be, how much time you should spend on your work, and what counts as success. And perhaps most dangerously of all, he does it gently: with pastel interfaces, friendly onboarding flows and taglines to soothe your scholarly exhaustion. It is easy to swallow. It is meant to be.

And it is difficult to deny that these tools arrive at a moment when the research profession is already strained. Academics face impossible demands for speed and output, career pressures, metric-driven evaluations, and chronic time starvation. The Tech-bro did not invent these conditions, but he is exploiting them. His promise is seductive because it speaks to real pain points. And yet, the solution he offers is to cut corners, to automate depth, to trivialize the very difficulty that makes scholarship meaningful. 

It is this infantilization of research - the notion that reading, writing, and thinking can or should be compressed into seconds, and that ‘knowledge is simple’ - that we are wary of. Why, dear Scholar, are we letting the Tech-bro tell us what research should be? Why are we surrendering our intellectual rhythms, our scholarly labour, our relationship to knowledge to people whose concern is not the pursuit of understanding, but the growth of users and the exponentially steep curves of monthly-recurring-revenues? 

The point of this essay has been to show how the ‘Tech-bro-ification of research’ is unfolding right in front of our eyes at this very moment: not the proliferation of technologies to do research with but the quiet import of an entire worldview into how research should be. We have aimed to illuminate not only the logics the Tech-bro embodies, but how these logics take over our own scholarly work through the ways tools are branded and marketed to us. If this has been a warning, it is not a call to reject technology.

It is a call to approach it with critical reflexivity: to ask not only what a tool does, but what it tells us research ‘should’ be, what kind of researchers we ‘should’ be, and who gets to decide.

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