'The AI Con': Unmasking Big Tech's AI Hype - Insights from Emily M. Bender and Alex Hanna

In recent years, artificial intelligence has been increasingly heralded as the next frontier in technology, bringing with it a wave of intense speculation and, sometimes, misunderstanding. The term "AI" has become synonymous with a blend of futuristic expectations and fear of unknown capacities, promoting a narrative that often exaggerates what current technologies can achieve. This hype is critically assessed in the book *The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want*, where authors Emily M. Bender and Alex Hanna argue that the label "artificial intelligence" is a marketing strategy rather than a reflection of the actual capabilities of technologies such as large language models. They contend that these models, like ChatGPT, operate more as sophisticated autocomplete systems rather than possessing any form of genuine intelligence ().

The pervasive AI hype is not just about overstating technical capabilities; it also involves significant economic and ethical considerations. The parallels drawn between the current AI enthusiasm and previous tech bubbles, such as the dot-com and cryptocurrency booms, illustrate how valuation often outpaces substantive profitability. This trend raises critical questions about whether these investments in AI are sustainable or based on inflated expectations that might not materialize into practical returns ().

Moreover, AI's potential impact on society is profound, as it is deeply intertwined with issues like data privacy, labor exploitation, and environmental sustainability. Technologies marketed under the AI banner, while promising transformative efficiencies, are at risk of perpetuating existing social inequalities rather than solving them. Bender and Hanna stress the importance of understanding AI's dependency on immense datasets, often acquired without consent, and the massive energy footprint that accompanies it. These are not just technological issues but ethical dilemmas that require careful consideration if the technology is to truly benefit society at large ().

In light of these challenges, Bender and Hanna propose a radical shift in how technological advancements, particularly AI developments, are governed and utilized. They advocate for community-owned and controlled technological systems that align with local values and needs, suggesting that this could pave the way for a more equitable and sustainable integration of AI into daily life. Such models prioritize the public good over private profit, ensuring that technology serves to enhance rather than exploit human potential. This approach aligns with the growing call for regulation and community engagement in technology development, which aims to harness AI's capabilities for broad societal benefits rather than narrowing them to the interests of big tech corporations ().

The term 'Artificial Intelligence' often evokes images of futuristic machines that can think and reason like humans. However, as discussed in the book *The AI Con* by Emily M. Bender and Alex Hanna, this perception is largely a result of marketing hype [In These Times](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley). The authors argue that what we call AI, particularly technologies like ChatGPT, are merely sophisticated tools that predict and generate text based on large datasets, rather than exhibiting any true form of intelligence. This marketing gimmick aims to inflate the capabilities of these technologies to attract investment and maintain the allure of innovation within the tech industry.

Moreover, the hype around AI is reminiscent of past tech bubbles, such as the dot-com boom and cryptocurrency explosions, which promised much but often delivered little [In These Times](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley). Despite significant investments, many AI technologies fail to yield substantive profits, raising questions about their economic viability. Experts suggest that this cycle of investment and disappointment is driven by both the mystique surrounding AI and the pressure for tech companies to continually present cutting-edge advancements.

An alarming concern highlighted by Bender and Hanna is the ethical context surrounding the development of AI, linking it to the controversial history of eugenics in Silicon Valley [In These Times](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley). The pursuit of a singular notion of 'intelligence' overlooks the diverse manifestations of human intellect and perpetuates a narrow view that echoes discriminatory practices of the past. Additionally, this misguided pursuit fosters technologies that often reinforce existing social inequalities, particularly through automated systems that replicate biases present in the training data.

The intersection of artificial intelligence (AI) and the legacy of eugenics is a complex and contentious topic that extends beyond mere technological advancement. AI proponents have long pursued the creation of machines that can mimic or even surpass human intelligence. This ambition, however, is deeply intertwined with historical narratives of eugenics—a movement once aimed at improving the human race by controlling reproduction and eliminating undesirable traits. Emily M. Bender and Alex Hanna, authors of *The AI Con*, highlight how the term 'general intelligence' within AI discourse often mirrors the eugenics movement's flawed assumptions of intelligence, perpetuating a narrow view that lacks diversity and inclusiveness. In their interview with *In These Times*, the authors emphasize the continuing impact of these biases, drawing parallels between the tech industry's ambitions and the outdated, but still influential, eugenic ideologies that underscore them. Learn more about these complex intersections.

The conversation around AI and eugenics also encompasses the ethical dilemmas of AI development. The current trend in AI, as critiqued by Bender and Hanna, relies heavily on data that is often obtained unethically, echoing the morally dubious methods of the eugenics movement. This includes using unconsented data to train AI models, reminiscent of how eugenics exploited pseudoscientific metrics to justify discrimination. The authors assert that just as eugenics propagated inequality under the guise of science, AI risks reinforcing systemic biases if unchecked. For instance, in their book *The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want*, the authors call for a reassessment and regulation of AI technologies to prevent them from perpetuating historical injustices. This critical lens compels us to consider not only technological capabilities but also the ethical frameworks within which they operate. Explore more about the ethical implications of AI.

Exploiting labor through fauxtomation is a hidden reality behind the glittering facade of artificial intelligence. As highlighted in the article by In These Times, AI is often marketed as a groundbreaking advancement aimed at enhancing efficiency and cutting costs. However, this masks the underlying truth that much of what is hailed as AI-driven automation is, in fact, a facade—what Emily M. Bender and Alex Hanna call "fauxtomation." This term indicates systems that feign automation but actually depend heavily on human labor, often sourced from underpaid, gig-based jobs [1](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley).

The concept of fauxtomation is a glaring critique of the way AI is leveraged to sideline human workers while presenting an image of progress and innovation. In reality, these systems exploit labor in less visible ways. The example of the National Eating Disorders Association, which replaced its human hotline operators with a chatbot immediately following a unionization vote, underscores the tendency of companies to prioritize cost savings over job security. Such practices are demonstrative of how AI and fauxtomation are utilized to dismantle labor rights, as it appears automation is solving organizational challenges while it is primarily about reducing labor costs [1](https://www.theguardian.com/books/2025/may/19/the-ai-con-by-emily-m-bender-and-alex-hanna-review-debunking-myths-of-the-ai-revolution).

Bender and Hanna emphasize the economic motivation behind the AI industry’s push towards so-called full automation—where in truth, the illusion of automation is maintained to pacify public and investor expectations, masking the reality of precarious labor conditions. These insights shed light on how AI is not just a technological development but also a tool for financial maneuvering that shifts value from human labor to algorithmic systems. The AI industry's interest in automation is often geared more toward increasing profit margins by masking human involvement as technological advancement [1](https://www.theguardian.com/books/2025/may/19/the-ai-con-by-emily-m-bender-and-alex-hanna-review-debunking-myths-of-the-ai-revolution).

Fauxtomation underscores the ethical concerns surrounding AI deployment, specifically its impact on labor dynamics. The parallels drawn between AI's promises and the grim labor realities call for a more critical evaluation of AI's role in contemporary economies. The rhetoric of AI as a looming job replacer distracts from the immediate impacts it has on job quality, worker rights, and economic equality. As these technologies continue to unfold, the discussions initiated by Bender and Hanna in their book could catalyze deeper scrutiny into not just what AI can do, but what it should do within the spectrum of the labor market [1](https://www.businessinsider.com/the-ai-con-emily-bender-alex-hanna-ai-hype-2025-5)[4](https://events.sjsu.edu/event/a-conversation-with-the-authors-of-the-ai-con).

The dual nature of AI's impact on education highlights both the transformative potential and the inherent risks associated with integrating AI technologies into learning environments. On one hand, AI can provide personalized learning experiences, adapting to individual student needs, and offering resources that may not be otherwise available. For instance, AI-driven tools can support teachers by handling administrative tasks, allowing educators to focus more on engaging with students. This transition towards digital education can stimulate interest in STEM fields, preparing students for future technological landscapes.

On the flip side, relying heavily on AI in education can exacerbate inequities and divert from crucial skill sets that traditional education fosters, such as critical thinking and creativity. Students may become overly reliant on AI tools like ChatGPT for information and writing tasks, discouraging original thought and reducing the depth of learning. According to Emily M. Bender and Alex Hanna, as discussed in an article from *In These Times* [1](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley), these tools are sophisticated but essentially glorified autocomplete systems, presenting limitations in fostering genuine intellectual engagement. Moreover, the dependence on AI due to resource constraints in schools serves as a temporary solution rather than addressing the root causes of educational disparities.

Furthermore, the introduction of AI in education raises questions about data privacy and ethics. The data-driven nature of AI applications often requires significant amounts of personal information, raising concerns about data security and student privacy. In addition, the deployment of AI technologies can lead to job displacement within the educational sector, potentially undermining job security for teachers and administrative staff. The article also critiques the irony of universities criticizing AI-assisted plagiarism, while simultaneously forming lucrative partnerships with AI companies, highlighting the complex dynamics between educational institutions and AI development [1](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley).

AI's potential to reinforce existing biases within educational content and evaluations is another critical concern. AI systems trained on biased datasets may perpetuate and even amplify these biases, impacting student assessments and creating unequal learning opportunities. This calls for a careful examination of the datasets used for training AI models in education, ensuring they reflect diversity and inclusivity to achieve equitable outcomes for all students. The insights from *The AI Con* argue for a more community-driven approach to technological advancement, emphasizing transparency and ethical considerations [1](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley).

In the context of rapidly advancing technological landscapes, the discussion surrounding regulation and community-controlled technologies emerges as a critical issue. Emily M. Bender and Alex Hanna, in their book 'The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want,' advocate for a more responsible approach to technological development. They argue that the term 'artificial intelligence' is often used to mislead the public, masking the real nature of these technologies as advanced autocomplete systems. These systems are powered by massive data sets, often acquired and used without consent, and pose significant energy consumption challenges ().

Bender and Hanna propose a shift towards community-owned and controlled tech systems as a sustainable alternative to the current status quo dominated by big tech companies. They highlight examples like Te Hiku Media in New Zealand, which operates under a model that prioritizes local control and aligns technological development with community values. Such models not only aim to ensure equitable technological advancement but also work against centralized data control, paving the path for data sovereignty and community empowerment ().

The authors emphasize the need for regulation to manage and mitigate the adverse effects of big tech's influence. They argue that without government intervention to ensure ethical compliance and prevent monopolistic practices, the technology sector risks exacerbating existing societal inequalities. Regulation could steer innovation towards public interest, promoting transparency and accountability in technological development ().

By advocating for these changes, Bender and Hanna highlight a pathway towards a future where technological development serves the collective good rather than corporate interests. Their stance invites policymakers, technologists, and communities to consider alternative governance models for technology that emphasize sustainability, equity, and shared benefits. This approach challenges the entrenched paradigms of big tech dominance, inviting a reimagining of technology as a tool for empowerment rather than exploitation ().

As we conclude our exploration of charting a sustainable AI future, it becomes imperative to reflect on Emily M. Bender and Alex Hanna's critical perspectives presented in their book, *The AI Con: How to Fight Big Tech's Hype and Create the Future We Want*. The arguments laid out by Bender and Hanna expose the misleading marketing of "artificial intelligence," highlighting that technologies often labeled as AI, such as ChatGPT, are essentially advanced autocomplete systems. These systems rely heavily on vast amounts of data and consume significant amounts of energy, as illustrated in the extensive interviews detailed in [*In These Times*](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley).

As we chart the path forward, a critical consideration is the sustainability and equity of AI development. Bender and Hanna's critique of AI technologies as tools of labor exploitation, where initiatives masquerading as automation contribute to workforce displacement, underscores the need for ethical investment and regulatory oversight. The potential environmental impact, as noted in a 2025 *MIT Technology Review* report, further anchors the argument for sustainable practices within the tech industry. This perspective aligns with the increasing calls for community-owned solutions, where technological advancements benefit broader societal strata, avoiding the pitfalls of previous tech bubbles [*MIT Technology Review*](https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/).

Emphasizing community ownership and regulatory frameworks, these insights call for a shift towards models that are rooted in accountability and transparency. The example of Te Hiku Media in New Zealand serves as a lighthouse for community-driven technological governance, advocating for systems that are controlled and owned by local populations. Bender and Hanna's advocacy points towards a future where tech systems align more closely with human values and social equity, as suggested by their exploration through *In These Times* articles and discussions [*In These Times*](https://inthesetimes.com/article/big-tech-the-ai-con-book-silicon-valley).

Ultimately, ensuring a sustainable AI future involves not only addressing the technological and environmental challenges but also rethinking the societal frameworks that govern these innovations. As AI continues to evolve, the importance of embedding ethical considerations and fostering an environment where technology enhances human potential, rather than laboriously tethering it, becomes paramount. Engaging with AI critically, as Bender and Hanna propose, encourages us to envision alternative futures where technology amplifies community strengths and upholds justice, steering away from hype-driven narratives that shroud its true capabilities and limitations.