What Role Can Women Play in Shaping the Ethics of AI?

Women play key roles in advocating for gender-inclusive AI, leading ethical AI research, serving as ethics advisors, educators, and mentors, pioneering AI for social good, shaping policies as regulators, demonstrating ethical leadership, organizing communities for AI ethics awareness, influencing AI narratives in media, and innovating ethically conscious AI technologies.

Women play key roles in advocating for gender-inclusive AI, leading ethical AI research, serving as ethics advisors, educators, and mentors, pioneering AI for social good, shaping policies as regulators, demonstrating ethical leadership, organizing communities for AI ethics awareness, influencing AI narratives in media, and innovating ethically conscious AI technologies.

Empowered by Artificial Intelligence and the women in tech community.
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Advocators for Gender-Inclusive Design

Women can leverage their unique perspectives to advocate for gender-inclusive design in AI development, ensuring that AI systems are free from gender biases and are able to serve diverse populations equitably.

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Maybel Lagumbay
Customer and Community Support Manager at WomenTech Network

Women can play a critical role in making AI more inclusive by bringing diverse perspectives into data, product, and technology development. They can help identify gaps and biases in datasets, challenge assumptions that may exclude certain groups, and advocate for AI systems that reflect the needs and experiences of diverse communities. By combining technical expertise with lived experience and user-centered thinking, women can help ensure that gender inclusion becomes an integral part of responsible AI design rather than an afterthought.

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Leaders in Ethical AI Research

Women in positions of influence within academic and research circles can push the boundaries of ethical AI research. Their work can illuminate the ways in which AI impacts different genders differently, leading to more humane and ethical AI systems.

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Aditi Godbole
Senior Data Scientist at SAP

The sudden rise in AI has created many opportunities such as Personalization, improved customer and business experience, Predictive capabilities, and better decision-making models. However, this sudden rise has also brought some concerns about using and implementing ethically and sustainably across the industry.
One of the major challenges in Ethical AI is gender bias in AI, As AI systems are conceptualized and built they lack high-quality data that may not cover datasets for underrepresented communities such as Women. Based on research and studies done by Berkeley Hass Center for Equity & Gender, 44 percent of systems have shown gender bias
Women can bring diverse perspectives to AI development by assessing data that is misrepresented and can provide data sets that represent women and their experiences. Only 30 percent of women are currently working in AI as per the global gender gap report of 2023. We need more women researchers in this field who can bring industry-wide standards to bring fairness and transparent policies and address potential biases and their impacts on different groups of people. Women can also encourage female representation, participation, and engagement in all the stages from building policies, governance, and implementing solutions across the industry to ensuring AI systems are developed and used responsibly

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Maybel Lagumbay
Customer and Community Support Manager at WomenTech Network

Women in AI, data science, and research can advance ethical AI by examining how algorithms, datasets, and automated systems affect different populations. Their work can contribute to stronger approaches to fairness, transparency, bias detection, and accountability while highlighting issues that may otherwise be overlooked. Increasing women's participation in AI research also brings broader perspectives to the development of technical and industry standards for building trustworthy AI systems.

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Jiahuan Li
Founder, Keyu Ecosystem at Ziran-hypnosoul

Ethical AI conversations often stay abstract — principles on a slide, not decisions in a product. As the founder of Keyu Ecosystem, I've had to make these calls concretely, without a research team or academic framework to lean on, just direct product decisions.

One example: building an anti-fraud tool (Vision Shield), I deliberately chose not to profile users by age, language ability, or demographic group — even though "elderly users" or "immigrants" would be the obvious, data-friendly targeting choice. My own case research showed victims span IT professionals, a retired bank director, and myself — vulnerability to manipulation is a universal cognitive pattern, not a demographic trait. Designing around that meant harder, more general detection logic, but a fairer product.

A second principle I hold firm to: never let the tool imply more certainty than it has. Every result carries a plain disclaimer — this is AI-assisted, not infallible, and real verification always goes through independent, official channels. In fraud-detection specifically, false confidence is itself a harm.

I don't have an academic research platform. What I have is the accountability of building alone, for real users, where every ethical shortcut would show up as someone's real financial loss. That constraint, I've found, produces its own rigor.

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Ethics Advisors in Tech Companies

By taking up roles as ethics advisors or consultants in tech companies, women can directly influence the ethical guidelines that govern AI development. Their insights can help in crafting policies that ensure AI technologies respect privacy, consent, and fairness.

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Irsa S
Social Media Manager at WomenTech Network

This role becomes especially important as companies move from experimenting with AI to putting it into everyday products. Ethics advisors can help teams think through questions around:

  • Privacy and consent
  • Bias and discrimination
  • Human oversight
  • Accountability when something goes wrong

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Okafor Esther
Senior QA engineer at Kaluza

Ethical AI is not only about having principles written down; it is about making sure those principles influence real decisions throughout the AI lifecycle. Women can play an important role in asking the difficult questions around fairness, accountability, privacy, transparency, and the impact AI systems may have on different groups of people.

This is also an opportunity for more women to put themselves in positions where they can influence AI design, governance, assurance, and decision-making. We should be part of the conversations where risks are identified, controls are defined, and decisions are made about whether an AI system is truly ready to be used.

The more visible and involved women are in these spaces, the more opportunity we have to advocate for responsible AI that is not only innovative, but also trustworthy and accountable.

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Educators and Mentors

As educators and mentors, women can inspire and nurture a new generation of AI professionals who are deeply aware of the ethical implications of AI. They can introduce ethical considerations early in the education of future technologists, embedding a strong ethical foundation.

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Sisanda Skweyiya
Senior Business Analyst at Accenture

Women educators and mentors have a powerful role in shaping the next generation of AI professionals. It’s not just about teaching people how to build technology but also encouraging them to think about how that technology affects people.
By introducing conversations around fairness, responsibility and ethics early on, women can help future technologists see ethical thinking as part of building good technology, not something to consider afterwards.

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Okafor Esther
Senior QA engineer at Kaluza

AI is already changing how people learn, work, and make decisions, so education around AI cannot only focus on how to use the technology. We also need to talk about how to question it.

Women in education and mentoring spaces can help younger professionals understand that responsible AI means asking who benefits, who may be excluded, what data is being used, and what happens when the technology gets something wrong.

These conversations do not have to begin when someone becomes an AI expert. They can start much earlier. The more we encourage people to think critically about AI from the beginning, the more likely we are to build a generation that sees ethics and accountability as part of technology, not as something added later.

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Pioneers of AI for Social Good

Women can lead initiatives that deploy AI for social good, providing tangible examples of how ethical AI can address societal challenges. Projects focusing on health, education, and environmental sustainability can underscore the importance of ethical AI in improving lives.

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Irsa S
Social Media Manager at WomenTech Network

AI for social good is a space where ethical thinking can be put into practice rather than staying theoretical. Women can contribute by developing or supporting projects focused on areas such as:

  • Healthcare and accessibility
  • Education
  • Climate and sustainability
  • Public services

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Okafor Esther
Senior QA engineer at Kaluza

AI has a lot of potential to improve everyday life, but social good should be about more than simply applying AI to a social problem.

We also need to ask whether the technology is genuinely helping the people it is meant to serve. Are those communities involved in the design? Is the system accessible? Does it create new risks while trying to solve another problem?

Women can bring important perspectives into these projects by helping keep the focus on people rather than just the technology. Sometimes the most responsible use of AI starts with listening closely to the people affected and making sure their needs remain at the centre of the solution.

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Jiahuan Li
Founder, Keyu Ecosystem at Ziran-hypnosoul

Under my one-person company, Keyu Ecosystem, I've built a portfolio of AI projects that each target a group often left out of mainstream tech design: elderly people living alone, blind and low-vision users, and outdoor adventurers who lose signal in remote or dangerous terrain.

Keyu Changqing supports elderly companionship and emergency assistance for seniors who may otherwise face a crisis alone. Keyu Shijie is an AI companion built for blind and low-vision users navigating daily life. Keyu Shengcun is designed for extreme-sports and wilderness scenarios where there's no signal — helping people get help when standard tools fail them completely.

What connects these projects isn't a single technology — it's a throughline I've carried since long before I started building AI: taking something complex or frightening and translating it into something plain, calm, and usable for someone who would otherwise have to face it alone. I don't come from a coding background; I built all eight Keyu projects by staying close to product design and real user needs, and letting AI tools handle the technical execution.

For me, "AI for social good" isn't a separate initiative — it's the default design brief for every project I build.

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Policy-Makers and Regulators

In governmental and regulatory roles, women can shape the laws and policies that set the framework for ethical AI development and use. They can ensure that regulations are comprehensive, enforceable, and adaptable to technological advancements.

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Role Models in Ethical Leadership

As visible role models, women in high-profile tech leadership positions can demonstrate ethical leadership in AI. Their commitment to ethical practices can inspire others within the industry to prioritize ethical considerations in their work.

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Sisanda Skweyiya
Senior Business Analyst at Accenture

Women in visible tech leadership roles can show that innovation and ethics belong together. By prioritising transparency, fairness and accountability, they demonstrate what responsible AI leadership looks like in practice.
Their influence goes beyond their own organisations, they can inspire others to ask difficult questions, challenge decisions and consider who technology serves.
The leaders shaping AI today are also helping shape the values that will define technology tomorrow.

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Okafor Esther
Senior QA engineer at Kaluza

One thing that matters as AI continues to grow is seeing more women in visible positions where they are making decisions about how the technology should be used.

Leadership is not only about supporting innovation. It is also about being willing to question whether something should be built, whether the risks have been properly considered, and whether enough has been done to protect the people affected.

When women are visible in those conversations, it also shows other women that there is a place for them in AI governance, assurance, leadership, and decision-making. Representation matters because it can encourage more women to step forward and contribute their own perspectives.

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Community Organizers

Women can organize and lead community awareness initiatives that emphasize the importance of ethical AI. By fostering public understanding and debate, they help ensure that communities are informed and can advocate for ethical AI practices.

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Media and Communication Experts

Through media and communication, women can shape the narrative around AI ethics, highlighting issues of concern and generating public discourse. Their efforts can elevate the importance of ethics in public and corporate consciousness.

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Innovators and Entrepreneurs

As innovators and entrepreneurs, women can build startups and technologies that prioritize ethical AI from the ground up. Their ventures can serve as benchmarks for how businesses can succeed while steadfastly adhering to ethical principles in AI development.

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Jiahuan Li
Founder, Keyu Ecosystem at Ziran-hypnosoul

As the founder of Keyu Ecosystem, I've built eight AI-driven projects from the ground up without a traditional coding background. My role sits deliberately on the product and architecture side — I make the design and technical decisions, while hands-on implementation is executed with AI tools and, where needed, technical collaborators.

That vantage point has shaped how I think about ethical AI. Before committing to any tool or approach, I run side-by-side comparisons across a dozen-plus AI systems to understand not just what each one can do, but where it can quietly mislead, exclude, or overwhelm the people using it. One thread runs through all my projects: building AI that translates complexity into something plain and reassuring, rather than adding to the noise.

I also see this as a family practice, not just a business one — I guide my husband and daughter as they build their own AI-assisted projects, which keeps me grounded in how non-technical, everyday users actually experience these tools.

For me, "ethical AI from the ground up" isn't a compliance checkbox — it's a design constraint I apply from the very first product decision: does this make someone's digital life clearer and safer, or does it add another layer they have to navigate alone?

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What else to take into account

This section is for sharing any additional examples, stories, or insights that do not fit into previous sections. Is there anything else you'd like to add?

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Okafor Esther
Senior QA engineer at Kaluza

As someone who has taken a keen interest in understanding the risks and challenges of AI, especially how people interact with it in their day-to-day lives, I believe women should be much more vocal in this space.

Shaping the ethics of AI requires women to be actively involved in conversations around governance, policy, compliance, and how AI is designed and applied across different sectors and in people’s everyday lives.

With AI growing so quickly, we are already seeing important questions around risk, fairness, accountability, privacy, and the impact these systems can have on individuals and communities. There is no better time for women to step forward, make our voices heard, and take part in shaping how AI develops.

AI is here to stay, so we should make sure we are not only represented in the conversation, but actively involved in making its future more inclusive, responsible, and equitable.

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