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# Behind the Code: How Women Are Powering the Future of AI

Female-led AI startups receive just 1% of global venture funding. This severe disparity directly hardcodes predominantly male, Western-centric biases into the language models we rely on today.

- **Speakers:** [Alexandra Wudel](https://www.wearedevelopers.com/@alexandra-wudel), [Laura Moritz](https://www.wearedevelopers.com/@laura-moritz), [Madalina Florean](https://www.wearedevelopers.com/@madalina-florean)
- **Event:** World Congress 2025
- **Published:** August 20, 2025
- **Duration:** 30:28
- **URL:** https://www.wearedevelopers.com/videos/1707-behind-the-code-how-women-are-powering-the-future-of-ai

## Summary

Despite women leading the charge in responsible and human-centered AI, female-led startups receive critically low venture capital funding—plummeting to a mere 1% of global VC volume. This systemic disparity directly impacts the systems we build today, leading to AI tools and Large Language Models (LLMs) inherently biased by Western-centric and predominantly male engineering perspectives. Reversing this trend requires treating AI not just as a technical challenge, but as an opportunity to build a more inclusive future driven by diverse voices.

In practice, building an effective AI strategy means embedding responsible AI principles into product roadmaps from day one, rather than treating them as an afterthought. Companies benefit from an explicit ethical framework to avoid friction during deployment and remain compliant with upcoming regulations like the EU AI Act. However, sustained user trust comes from focusing on repetitive, long-term business value instead of flashy short-term features. Cultivating this trust demands transparency around a model's limitations, rigorous testing for edge cases, and a governance structure that includes external AI ethics boards to help guide critical development choices.

At the leadership level, rapid AI evolution shifts the emphasis away from specialized silos toward interdisciplinary thinking and active listening. Strong software engineering fundamentals combined with worldly wisdom empower teams to connect ideas across domains and ask better questions. As AI transforms board-level decision-making, continuous education and purpose-driven development become essential. Ultimately, integrating underrepresented groups into the fundamental engineering workflows creates robust, fair systems capable of powering lasting organizational and societal change.

**Keywords:** responsible AI frameworks, EU AI act compliance, VC funding disparities, LLM training bias, AI trust and transparency, external AI ethics boards, female AI founders, AI product roadmapping, interdisciplinary leadership, embedded AI ethics, algorithmic fairness metrics, board-level AI governance, software engineering fundamentals, generative AI edge cases, AI system limitations

## Chapters

1. **Setting the context for female leadership in artificial intelligence** (00:05) — Addressing venture capital disparities helps establish foundational strategies for responsible technology development.
1. **Embedding responsible practices early in initial product development** (03:31) — Addressing regulatory requirements like the EU AI act from day one improves overall output accuracy.
1. **Balancing immediate business value with long-term technological capabilities** (05:26) — Deploying agentic technology incrementally allows companies to establish compounding advantages while remaining agile.
1. **Establishing specific fairness metrics to measure systematic trust** (07:38) — Appointing domain experts per ethical principle prevents corporate governance frameworks from becoming overly vague.
1. **Building organizational trust through transparency and realistic expectations** (10:45) — Acknowledging engineering limitations and monitoring training parameters helps combat black box phenomena.
1. **Cultivating interdisciplinary skills for developing modern technological solutions** (14:31) — Combining foundational software engineering capabilities with interdisciplinary logical thinking accelerates innovation cycles.
1. **Transforming corporate governance with external ethical review boards** (16:33) — Integrating external review panels helps organizational leaders navigate compliance requirements and cybersecurity risks.
1. **Adapting engineering leadership strategies to rapid technological change** (19:47) — Leaders must utilize specialized resources to curate knowledge and guide responsible internal adoption strategies.
1. **Overcoming startup funding disparities and preventing algorithmic biases** (22:38) — Funding diverse founding groups is critical to averting western-centric bias inside large language models.
1. **Empowering the next generation to drive inclusive automation** (26:47) — Embracing specialized niches and advocating for transparent systems enables marginalized populations to lead technological shifts.

## Related Moments

- [Introduction to responsible artificial intelligence and societal impact](https://www.wearedevelopers.com/videos/509-a-walkthrough-on-responsible-ai-frameworks-and-case-studies) (from "A walkthrough on Responsible AI Frameworks and Case Studies")
- [Growth forecasts and core principles for AI-driven product design](https://www.wearedevelopers.com/videos/1016-insight-into-ai-driven-design) (from "Insight into AI-Driven Design")
- [Developing critical leadership skills for AI integration](https://www.wearedevelopers.com/videos/1818-what-happens-to-leadership-when-ai-becomes-a-teammate) (from "What Happens to Leadership When AI Becomes a Teammate?")
- [Assessing AI ethics adoption in the private sector](https://www.wearedevelopers.com/videos/1104-responsible-ai-in-practice-real-world-examples-and-challenges) (from "Responsible AI in Practice: Real-World Examples and Challenges")
- [Building superhuman human resources capabilities with artificial intelligence](https://www.wearedevelopers.com/videos/1484-from-uncertainty-to-empowerment-personalizing-the-human-experience-with-ai) (from "From Uncertainty to Empowerment: Personalizing the Human Experience with AI")
- [Balancing AI regulation with technological innovation in human resources](https://www.wearedevelopers.com/videos/1356-from-learning-to-leading-why-hr-needs-a-chatgpt-license) (from "From Learning to Leading: Why HR Needs a ChatGPT License")

## Related Articles

- [Panel Discussion: Responsible AI in Practice - Real-World Examples and Challenges](https://www.wearedevelopers.com/magazine/488-panel-discussion-responsible-ai-in-practice-real-world-examples-and-challenges)
- [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
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