Who Are the Critical Optimists?

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By Jacob Pleasants & Dan Krutka

In last week’s blog post, David Stroupe, Niral Shah, and Aman Yadav shared a recent article they published in Educational Researcher along with several other colleagues, titled “Refusing educational technology: Artificial intelligence, inequity, and the problem of critical optimism” (Shah et al., 2026). In this blog post, we offer some commentary on their publication that we hope will spur further conversation.

In their article, Shah et al. present a critique of what they call the ideology of “critical optimism” regarding educational technologies. They describe this as a position that “has aimed to reconcile wariness and hope” toward technology in schools and “rejects the idea of technology’s neutrality while maintaining the belief that technology can improve education” (p. 4). It is, they say, the “default position of many education researchers.” And while they grant that this position may have some merit, the primary fault they identify is that “it downplays its own analysis” (p. 4) by continuing to advocate for the promises and benefits of educational technologies despite acknowledging a wide range of concerns. According to Shah et al., the critical optimists thus reveal “a desire to have one’s technology and to critique it, too” (p. 4). 

We agree with Shah and colleagues that there is a faulty pattern of reasoning within a fair bit of educational technology research (and policy), especially when it comes to AI. However, there are parts of their argument that we wish to contest. First, we argue that in their article, Shah et al. mis-locate this discourse and associate critical optimism with scholars who do not espouse such views. We also consider whether it really is such a contradiction to “have one’s technology and to critique it, too.” 

Are We “Critical Optimists?”

Shah et al. give several exemplars of critical optimism, and there are some that do indeed seem to align well with their definition. However, we were rather surprised to see our work listed among those advancing this position. At the beginning of their section titled “Appraisal of Critical Optimism,” the following paragraph appears:

To be clear, we agree that students should be empowered as “critical agents who can shape technological futures” (Pleasants et al., 2023, p. 490). Education in the sociopoliti­cal dimensions of technology—of the kind that critical opti­mism envisions—is a valuable harm-mitigation effort. Ultimately, though, we find critical optimism an insufficient response to the full weight of questions around educational technology like generative AI. (p. 4)

They ultimately find this approach wanting, arguing that it is merely a “guardrail” or “harm mitigation” strategy for risky technologies in schools, the use of which is a foregone conclusion. However, their argument confuses education about technology for educational technologies. Our work cited above, as well as others cited in their paper (e.g., Vakil, 2018) are concerned with the former whereas Shah et al. are concerned with the latter. 

Generative AI provides a useful example. As an educational technology, generative AI may very well be one that we should reject. But even if that is true, a strong case can be made that generative AI should be an object of inquiry in schools. This is because even if teachers and students choose not to use generative AI, they cannot opt out of living in a world in which generative AI is influential - much like the case for social media and other digital technologies (Jandrić & Knox, 2022; Patella-Rey, 2012; Van Dijck, 2013). Generative AI is therefore a worthy object of critical study within technology education (Irgens & Burriss, 2026; Pleasants et al., 2023), regardless of its status as educational technology. 

If we want to find the “critical optimists” for the case of generative AI, a much better place to look would be mainstream scholarship regarding (non-critical) “AI literacy,” especially for teachers (e.g., Deshen et al., 2026; Maurer et al., 2026). For instance, Kohnke et al. (2025) assert that “educators must become AI literate: that is, able to understand AI tools and incorporate them into their pedagogy” (p. 1, emphasis added). Literacy, in this mainstream view, does include an awareness of various problems with AI such as “misleading information, platform limitations and ethical concerns” (Kohnke et al., 2025, p. 1). But it is here that we can observe an unwillingness to entertain the possibility of refusal. Instead, literacy is positioned by scholars such as Kohnke et al. as being in service of adoption rather than in the kinds of careful appraisals and possible rejection that critical approaches suggest. When the limitations and ethical issues of the technology are discussed, it is to emphasize that they should therefore be used “responsibly” (a burden mostly borne by teachers).

So, the discourse of “critical optimism” may indeed exist, but it is located in a different place than Shah et al. suggest. Properly located, we hesitate to call it a novel ideology that truly attempts to chart a middle course between “wariness and hope” (p. 4). The mainstream literature does indeed refer to various concerns with AI in schools, but we argue that this is more a rhetorical move than a genuine ideological position. The promoters of AI have seemingly co-opted concerns raised by critical scholars (e.g., White & Scott, 2024), perhaps because those issues can no longer be reasonably ignored. Yet in practice, this amounts to little more than ethics washing. Their overt goal is to get more technologies (including AI) into schools (e.g., Deshen et al., 2026; Kohnke et al., 2025; Maurer et al., 2026). They mention ethical concerns, but invariably suggest that these can somehow be mitigated or avoided by “responsible use.” In our estimation, this is no middle path, but fairly standard techno-solutionism.

On Critiquing Technology (And Having it, Too?)

Mainstream discourse about educational technology (AI or otherwise) is frustrating in its endless talk of the “potential” for technologies to “enhance” learning or teaching. The promise seems to spring eternal, never mind the past. Shah et al. reference those broken promises of the tech optimists, noting that history shows a common pattern of “irrational hype followed by limited impact.” The question before us, then, is how to respond to and ideally deflate that hype. Shah et al. suggest “refusal” as a reasonable response, and we don’t disagree. Refusal is a solid and often quite pragmatic option for teachers and others. When we work with pre-service teachers, we make that pretty clear (see, for instance, Pleasants & Morris, 2026). 

In fact, our position is that the very purpose of engaging in critiques of technology is to exit the discourse and cycles of hype. Criticism, when done well, reveals that what is presented to us as a tool is, in reality, a much more complex assemblage. Go beneath the surface and we see the systems and values and people and politics that have come together to make this technology (and the discourse around it) what it is – as well as the alternatives that could have been, and perhaps might yet be. It reveals the (hidden) costs incurred for the benefits of the technology, and how they are unevenly distributed. The goal is not to simply evaluate a given technology and judge it good or bad, beneficial or harmful, worthy of acceptance or refusal. Ideally, a critical practice enables us to think more clearly about our relationships with technologies, the ones we bring into our lives and work and the ones we do not. Indeed, the technologies that we use the most are also the ones most in need of our ongoing critical attention. 

The techno-solutionists have no interest in this kind of critical practice. They mention risks and ethical concerns, but they are not engaging in any sort of true criticism. It’s more akin to acknowledging that a chainsaw is dangerous, so we’d better use it carefully!

The Bigger Picture

We were compelled to write this commentary in part because we see a need to clarify what it means to take a critical approach to technology and what it means to resist hype, in schools and beyond. In their article, Shah et al. reference the work of Larry Cuban (1986), who famously showed how classroom technologies have largely failed to live up to their promises. Yet while Cuban argued against hype, he did not claim that those technologies have been categorically useless or harmful or that they should have been rejected. History shows the story to be far more complicated. Even if digital technologies failed to be as “transformative” or “revolutionary” as their promoters claimed, they nevertheless have played productive roles in classrooms. We can think of many examples from our own teaching where digital technologies supported meaningful learning, along with plenty of examples where they did not, and examples where we deliberately opted for a “low tech” approach.

In our efforts to push back against tech hype, we must take care to not adopt a position that is simply the negative mirror image of that of the boosters. Refusal of a new technology can be a reasonable choice, but failure to reject a technology is not equivalent to “giving in to the hype,” nor is it indicative of “critical optimism.”

We understand this inclination considering how technology corporations have been able to have undue influence on school curriculum (as chronicled by Singer, 2026). But treating technological change as merely hype ignores reality. All of us—including the critics—are enmeshed in complex, highly technologized societies where we must make decisions about our relationships with various technologies. Generative AI is a particularly salient and timely target of our critical gaze, considering the environmental, labor, and human rights harms of the companies who are pushing it. And, yes, rejection is often a good option in many contexts. But what of the other technologies in our lives that have produced well-documented harms? Should we drive cars, which have had a profound impact in harms to the environment, human health, and community (gas-guzzling or not)? Should we communicate using digital technologies in light of the myriad ways they have eroded our relationships and distorted the cognitive processes involve in reading/writing using physical media?

We do not raise those examples to downplay the problems involved with AI, but rather to remind us that all technological systems raise gnarly questions that defy easy answers. In other words, we all must reckon with our relationships with technologies, and if refusal is the only option, then we're all critical optimists. Better, then, to identify what constitutes our values.

References

Cuban L. (1986). Teachers and machines: The classroom of technology since 1920. Teachers College Press.

Deshen, M., Harari, R., & Aharony, N. (2026). Teachers’ artificial intelligence (AI) literacy: An exploratory study. Smart Learning Environments, 13(1), 7. https://doi.org/10.1186/s40561-026-00433-5

Irgens, G. A., & Burriss, S. K. (2026). A Framework for Facilitating Young People’s Sociocritical AI Literacies. Educational Researcher. [Online First Publication] https://doi.org/10.3102/0013189X261468334 

Jandrić, P., & Knox, J. (2022). The postdigital turn: Philosophy, education, research. Policy Futures in Education, 20(7), 780–795. https://doi.org/10.1177/14782103211062713

Kohnke, L., Zou, D., Ou, A. W., & Gu, M. M. (2025). Preparing future educators for AI-enhanced classrooms: Insights into AI literacy and integration. Computers and Education: Artificial Intelligence, 8, 100398. https://doi.org/10.1016/j.caeai.2025.100398

Maurer, N., Brückner, M., Thyssen, C., Becker-Genschow, S., & Huwer, J. (2026). Science educators’ AI literacy and AI usage in teaching: Implications for post-qualification programs. Computers and Education Open, 10, 100376. https://doi.org/10.1016/j.caeo.2026.100376

Patella-Rey, P. J. (2012). Social media: You can log off but you can’t opt out. Cyborgology. https://thesocietypages.org/cyborgology/2012/05/10/social-media-you-can-log-off-but-you-cant-opt-out/ 

Pleasants, J., Krutka, D. G., & Nichols, T. P. (2023). What relationships do we want with technology? Toward technoskepticism in schools. Harvard Educational Review, 93(4), 486-515. https://doi.org/10.17763/1943-5045-93.4.486 

Pleasants, J., & Morris, M. (2026). Questioning the “Magic” of generative artificial intelligence in a science methods course. Journal of Science Education and Technology, 1-13. https://doi.org/10.1007/s10956-026-10300-0

Shah, N., Stroupe, D., Yadav, A., Bernhard, T., Logan, C., Dyer, E. B., ... & Li, T. (2026). Refusing Educational Technology: Artificial Intelligence, Inequity, and the Problem of Critical Optimism. Educational Researcher. [Online First Publication]. https://doi.org/10.3102/0013189X261466234

Singer, N. (2026). Coding kids: Big tech’s battle to remake public schools. W. W. Norton.

Van Dijck, J. (2013). The culture of connectivity: A critical history of social media. Oxford University Press.

Vakil, S. (2018). Ethics, identity, and political Vision: Toward a  justice-centered approach to equity in computer science education. Harvard Educational Review, 88(1), 26–52. https://doi.org/10.17763/1943-5045-88.1.26 

White, S. V., & Scott, A. (2024). Responsible AI and tech justice: A guide for K-12 education. Kapor Foundation. https://kaporfoundation.org/wp-content/uploads/2024/01/Responsible-AIGuide-Kapor-Foundation.pdf