a.i. power against minorities

Copywriters were one of the first to have their jobs targeted by AI firms. These are their stories, three years into the AI era.

Possible non-sexist reasons that women are not adopting AI as fast as men. 🍆 If we consider the fact that pornography is one of the most popular and prolific use cases for Gen AI, we should not be surprised that women are less likely to use AI. 📡 Women and girls are raised to develop better and more sophisticated communication skills than boys. Apptitude tests prove this. It’s not that women are inherently better at communicating. We just raise girls to be better communicators.Women can usually write better emails than the slop created by Gen AI. 😔 While there is an epidemic of loneliness universally, it hits men more acutely. Women tend to have richer social-emotional relationships with their real world friends and also seek professional therapy. Men have always been more emotionally isolated and vulnerable. And may use AI more for companionship and therapy. 🧐 Despite being 51% of the global population, women and girls know how it feels to be a disadvantaged group with limited access to power. They are more likely to challenge the dogma of power and are more likely to question the ethics of AI. Maybe the problem isn’t that women are adopting AI too slowly but that men are adopting it without critical analysis.

This collection interrogates how Artificial Intelligence (AI) is reshaping war, sovereignty, and human agency by entangling technological experimentation with myth-making and geopolitical power. Drawing on vignettes from the Ukrainian battlefront to Silicon Valley boardrooms, the contributions highlight the paradox that AI-driven innovation is contingent on perpetual risk-taking, distributed agency between humans and machines, and opaque state-corporate alliances. The latter foregrounds discursive and ideological alignments between state and corporate elites that increasingly naturalise apocalyptic and utopian AI futures. Furthermore, the collection examines the emergence of a global war lab, where conflict zones become sites for the rapid prototyping of autonomous systems. Meanwhile, decision-support algorithms in security and defence redistribute responsibility in unforeseen ways, thus challenging the promise of meaningful human control. Such dynamics are increasingly facilitated by the emergence of an AI Empire, in which corporate technological giants and militaries co-produce new forms of sovereignty and power across the global stage. This equally raises essential questions about the risks of automated violence, revealing the enduring role of judgment and emotion in war, and how mythology itself teaches us a great deal about technologically mediated warfare. Together, the collection argues that AI’s apparent inevitability is sustained by powerful mythmaking and storytelling that normalise experimentation, accelerate escalation, and mask unequal structures of extraction and domination. Ultimately, this collection offers a critical step towards uncovering these processes and reclaiming space for critical reflection, democratic oversight, and accountable design in an era when AI “deities” increasingly govern the politics and practices of conflict today.

Abeba Birhane refutes industry claims about the technology's potential to solve complex social problems.

Few industries have been hit by AI as hard as translation. Rates are plummeting. Work is drying up. Translators are considering abandoning the field, or bankruptcy. These are their stories.

AI Ethics with Professor Casey bit.ly/ai-ethics-syllabus For nearly five years, I've (Casey Fiesler aka Professor Casey) been creating social media content (largely on TikTok and Instagram) about artificial intelligence, especially as related to ethics, policy, and social impact. This page...

As automated technologies, particularly artificial intelligence (AI) and automated decision-making (ADM), become integral to social life, there is growing concern about their ethical implications. While issues of accountability, transparency, and fairness dominate discussions on “ethical” AI, little attention has been given to how socially disadvantaged groups most impacted by ADM systems form ethical judgments about them. Drawing on insights from relational ethics, this study uses dialogue groups with disabled people to explore how people distinguish between ‘more just’ or ‘less just’ uses of technology, and the contextual, situational, and relational factors that shape these judgments. For the dialogue group participants in our study, ethical reasoning was most strongly influenced by concerns about how ADM systems affect self-determination, caring relationships and identity recognition, and about the political–economic drivers of automation. The article contributes to AI ethics by empirically demonstrating that justice and ethics depend on the social relationships valued in different contexts and what is at stake, both personally and politically, in decisions aided by automation.

Disability bias is rife in trained AI models, according to recent research from Penn State. Here’s what we can do about it.

As it’s currently imagined, the technology promises to concentrate wealth and disempower workers. Is an alternative possible?

Attraverso l’analisi di tre tipologie di piattaforme differenti - app di ride sharing, social network e app di dating - cerchiamo di mostrare come la condizione di possibilità per l’implementazione di un design inclusivo sia lo scardinamento del binarismo algoritmico alla base dei sistemi di IA.

Deepfake researchers have long feared the day this would arrive.

Nature - Those who could be exploited by AI should be shaping its projects.