How AI bias may fuel gender inequality in tech

AI systems’ inherent biases and their growing influence across society are creating new forms of gender-based discrimination and harassment, with particularly concerning implications for women’s safety, privacy, and professional advancement.

Current state of AI bias: AI technologies are increasingly being deployed in ways that disproportionately harm and disadvantage women through various mechanisms.

• Algorithmic decision-making systems, such as those used in British immigration, are making life-altering determinations based on potentially biased factors including ethnicity and health markers
• Safety features like car crash test systems, designed primarily around male physiques, result in women being 73% more likely to be injured and 17% more likely to die in crashes
• In Iran, AI-powered facial recognition systems are being used to enforce restrictive dress codes targeting women

Digital harassment and exploitation: The technology is enabling new forms of gender-based harassment and abuse at an unprecedented scale.

• 96% of deepfake content consists of non-consensual pornographic videos targeting women
• High-profile women face widespread AI-generated attacks, including manipulated images reaching millions before removal
• Public figures like Representative Alexandria Ocasio-Cortez have reported trauma from discovering AI-generated pornographic content of themselves

Representation gap: Women remain severely underrepresented in AI development and leadership roles, perpetuating existing biases.

• Women make up only 22% of AI professionals worldwide
• The tech industry’s male-dominated culture (“tech bros”) prioritizes rapid development and profits over addressing bias concerns
• Even highly qualified women face increased scrutiny and challenges to their capabilities

Emerging solutions: Various organizations and initiatives are working to address AI bias and promote gender equity in the field.

• Women in Data is organizing major events focused on addressing AI bias
• Organizations like AnitaB.org India and Women in AI Africa are working to enhance women’s leadership in AI
• Proposals include establishing diverse councils of female AI policymakers and implementing “bias bounty hunter” programs to identify harmful algorithms

Political landscape and future implications: The intersection of AI development and political ideology could further impact gender equity efforts.

• Potential policy changes under new administration may eliminate requirements for equitable AI design
• The involvement of influential tech figures like Elon Musk raises concerns about future AI development directions
• Without intervention, AI’s current trajectory risks entrenching and amplifying existing gender inequalities