Cognitive scientist Hagen Blix discusses in an interview the detrimental impact of AI on wages and job quality, referring to it as “class warfare through enshittification.” His new book, “Why We Fear AI,” explores societal fears surrounding AI and its material impact on workers. Blix argues that AI is primarily a tool for controlling labor and depressing wages rather than merely a productivity enhancer. He emphasizes the need for workers to recognize shared interests and collectively organize against this ongoing threat. The discussion highlights the comparison between AI’s de-skilling effects and historical industrialization, advocating for a reevaluation of technology’s role in labor to promote worker dignity and quality over cheap production.
| name | description | change | 10-year | driving-force | relevancy |
|---|---|---|---|---|---|
| AI as a wage depression tool | AI’s development primarily serves to lower wages rather than increase productivity. | Shift from viewing AI as a productivity enhancer to recognizing it as a wage depressor. | Widespread acceptance of AI’s role in wage suppression, leading to more demands for worker protections. | Capitalistic motivations prioritize profit over employee well-being, driving wage competition. | 5 |
| Normalization of mediocrity | AI’s impact leads to a cultural adaptation to average outcomes in various professions. | Transformation of work culture from high-quality expectations to acceptance of mediocrity. | Potential decline in quality standards across industries, impacting innovation and expertise. | The desire for cost-cutting and efficiency over quality in product and service delivery. | 4 |
| Class war through enshittification | AI is viewed as a mechanism of class warfare by simplifying and degrading work quality. | Recognition that technology is increasingly being used for controlling and devaluing labor. | An intensified struggle for workers’ rights as technology trends toward de-skilling and deregulation. | The concentration of power in the hands of elite tech corporations at the expense of the workforce. | 5 |
| Growing support for labor movements | Solidarity among workers, including those in creative fields, concerning AI threats. | Shift from individualism in job security to recognizing collective vulnerability to AI. | A rise in unionization efforts and collective bargaining across diverse industries affected by AI. | The shared realization of AI’s impact on job quality and economic stability among workers. | 5 |
| AI’s role in widening economic inequality | The economic benefits of AI are predominantly accrued by a small elite. | Increased disparity between tech elites and the working class as AI replaces jobs. | Deepening of wealth inequality that prompts societal unrest and calls for economic reforms. | Market dynamics favoring profit maximization over equitable wealth distribution. | 5 |
| Environmental costs of AI production | AI production contributes to environmental degradation and resource depletion. | Emerging awareness of AI’s hidden ecological costs alongside economic impacts. | A societal shift towards sustainable practices in AI development and broader tech sectors. | Growing environmental consciousness among workers and consumers pushing for accountability. | 4 |
| name | description |
|---|---|
| Wage Depression Due to AI | AI technologies are likely to depress wages by replacing skilled jobs with low-cost alternatives, affecting worker livelihoods. |
| Class Warfare Through Technological Enshittification | Generative AI is viewed as a tool for class warfare, exacerbating inequalities and reducing job satisfaction. |
| Normalization of Mediocrity in Output | The prevalence of lower-quality AI-generated outputs may lead to a societal expectation of mediocrity, affecting standards. |
| De-skilling of Workforce | AI may de-skill workers, transforming skilled jobs into unskilled ones, leading to a loss of expertise and quality in labor. |
| Environmental Consequences of AI Production | The energy-intensive nature of AI development raises environmental concerns, contributing to resource depletion. |
| Alienation from Work | Workers may feel increasingly alienated due to AI’s role in undermining job satisfaction and purpose. |
| Erosion of Labor Solidarity | As job conditions worsen, there is a risk of eroding solidarity among workers, hindering collective bargaining efforts. |
| Inequality in Access to Quality Services | AI may create a divide in service quality, making essential services less accessible to lower-income individuals. |
| Impact on Future Generations | The long-term societal costs of AI, such as environmental degradation, will disproportionately affect future generations. |
| name | description |
|---|---|
| Class Consciousness Among Workers | The growing realization among various workers about their shared interests against the exploitative use of AI. |
| Solidarity in Labor Movements | Increased solidarity among workers across different sectors facing similar threats from AI and automation. |
| Resisting Deskilling | Workers advocating against the deskilling of their professions due to AI, pushing for recognition of their skills. |
| Awareness of Quality vs. Price | A shift towards valuing quality over low prices, linking it with the negative impact of AI on work and products. |
| Demanding Ethical Technology | Growing demand for technology that enhances rather than diminishes the quality of work and human dignity. |
| name | description |
|---|---|
| Generative AI | AI that produces content like text, images or music, significantly impacting creative and professional jobs. |
| Language Models | Advanced AI systems that process and generate human language, impacting the way we communicate and work. |
| Automation Software | Tools designed to automate tasks traditionally performed by humans, leading to efficiency and potential job displacement. |
| Gig Economy Platforms | Technologies facilitating short-term contracts or freelance work, reshaping labor markets and employment structures. |
| AI-Driven Market Making | Artificial intelligence tools used for creating efficiencies and profits in financial markets, potentially affecting economic stability. |
| AI in Military Applications | Integration of AI technologies in defense, raising ethical concerns and discussions about control and power. |
| Environmental Impact Technologies | Developing technologies addressing the hidden environmental costs of industrialization, including AI’s energy consumption. |
| name | description |
|---|---|
| Class Warfare through AI | Generative AI is perceived as a tool for wage depression and control, leading to class divisions and a negative impact on job quality. |
| Destruction of Quality Jobs | AI and automation are driving the de-skilling of the workforce, leading to a loss of quality in jobs and products. |
| Normalization of Mediocrity | As AI produces average results, there is a risk that society may accept mediocrity, undermining the value of expertise and deep work. |
| Environmental Costs of AI | The energy-intensive nature of AI technologies contributes to environmental degradation and exacerbates climate change issues. |
| Labor Solidarity and Unionization | The fear of AI’s impact on jobs may lead to increased worker solidarity and a push for unionization across various industries. |
| Market Manipulation by Corporations | Emerging trends in AI highlight the manipulative nature of markets, driven by corporate interests at the expense of worker welfare. |
| Shift in Skills Value | The devaluation of skilled labor due to AI may lead to a societal shift in the perceived value of education and expertise. |