Bridging the gap: inequalities that divide those who can and cannot create sustainable outcomes with AI

"AI" is Automated Inequality

Tech bros still dominate the discussions about so-called "AI" with false claims. Even most "AI"-critical researchers spend much of their time meticulously debunking (always only a subset of) claims, leaving vast areas of the economic consequences of "AI" unexplored. (Even the "AI"-evangelist Economi

AI Gender Pay Gap - Emerging Tech - I by IMD

As AI investment grows, unequal access to emerging tech skills is widening the AI gender pay gap. New research shows how organisations can reverse it.

AI FOR EPISTEMICS & COORDINATION

Civilization and technology have radically improved the human condition. Nonetheless, the world sometimes goes in directions which essentially nobody would prefer — e.g., nuclear arms races, unexpected financial crashes, predatory marketing, or ubiquitous political misinformation.

The Beauty of AI and Why AI Needs More Women

While women remain underrepresented in the Artificial Intelligence (AI) and tech workforce, their participation is considered crucial for developing the right AI for tomorrow.

We’re at risk of a two-tier AI economy if we don’t bridge the AI gender gap, expert says | Fortune

Women are more skeptical of AI. Their hesitation will make AI safer, says Harvard researcher Mara Bolis.

Labor market impacts of AI: A new measure and early evidence

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Why We Need More Women In The AI Revolution

Research suggests that women make up less than a third of AI professionals and only 18% of AI researchers globally.

Women in tech and AI in Europe: Can the region close its gender gap?

AI could be the turning point that finally unlocks women’s full participation in tech in Europe.

Gender Productivity Paradox: Artificial Intelligence Is Failing Women - ICTworks

We're seeing decreasing distributive returns at higher AI exposure levels. Precisely when we should expect technology to be most equalizing.

AI’s Gender Gap - Haas News | UC Berkeley Haas

Generative AI could boost productivity and reduce inequality, but women across the world are at risk of missing out.  A sweeping analysis by Nick Otis, PhD 25, Assistant Professor Solène Delecourt, and colleagues from Stanford and Harvard found that women were about 20% less likely than men to use tools such as ChatGPT, Claude, and […]

A Growing Gender Divide in the AI Economy — The Honest Economist

The article argues that AI is reshaping gender inequality even before the pay gap visibly widens. Women are more concentrated in clerical and administrative roles where AI can restructure work, while men are more concentrated in technical, AI-complementary roles. Among college graduates, the exposur

Why women’s leadership matters in the age of AI - I by IMD

AI is reshaping leadership and work. Ensuring women help design and govern it will determine whether the technology advances equity or deepens inequality.

How AI Is Fueling the Gender Pay Gap in Tech

A new Wharton study finds that too few women are working with emerging tech, and that exclusion is driving a growing divide in pay.

If AI is the future, gender equity is essential | NetHope

As the world faces many serious challenges — from climate change and poverty to displacement and social injustice – women and girls are key to tackling those issues and shaping future prosperity for all. Artificial Intelligence (AI), along with other digital tools, has the potential to help us address those challenges and open new opportunities. Seizing that potential requires us to take meaningful action to mitigate the risks AI poses to women and girls, and to use AI to advance gender equity.

Field Theory: AI as Social Science Question, Object & Tool

Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.