Join us in celebrating Kate Carter, PhD Candidate in AI & Healthcare, Public Speaker, Advocate for Diversity in Tech. Kate's leadership at the intersection of AI and healthcare is inspiring.
Let's hear from Kate:
Share your AI origin storyI never planned to work in AI. My career started in healthcare, focusing on patient care. But I knew physical therapy wasn't something I could do for the rest of my life, so I went back to school. I earned two master's degrees, one in leadership and management and another in blockchain technology. Both opened my eyes to the Fourth Industrial Revolution. That was the moment everything changed.
I started working at Mia AI, an organization focused on empowering one million women with AI. The mission spoke to me, and I threw myself into the work. I became an AI 2030 Fellow and joined the leadership team for the Black AI Think Tank, committed to increasing access, education, and representation in technology.
Now, I am a first-year PhD student researching how AI can improve chronic pain management. My journey has taken me from patient care to technology, from healthcare to ethics, from learning to leading. I am proud of the work I do because it is shaping a future where AI serves people, not the other way around. Every step I take is a step toward making that vision a reality.
What AI tools have been most game changing for you?
The three AI tools that have had the biggest impact on my work are ChatGPT, Perplexity, and Gamma.
ChatGPT has been essential for brainstorming, drafting, and refining ideas. It helps me structure complex thoughts, making my writing more efficient and clear.
Perplexity has changed the way I research. It pulls information from multiple sources, giving me a broader and more nuanced understanding of topics. It makes finding relevant data faster and more reliable.
Gamma has transformed the way I create presentations. It simplifies slide design and storytelling, allowing me to focus on delivering strong, engaging content without spending hours formatting.
Each of these tools has helped me work smarter, communicate better, and push forward ideas with more impact.
If you were just starting your AI journey today where would you start? If I were starting my AI journey today, I would focus on learning, experimenting, and connecting with others in the field.
I would begin by building a strong foundation. Free and affordable online courses on Coursera, Mia AI, and YouTube provide a great starting point. Reading The Coming Wave by Mustafa Suleyman or Artificial Integrity by Hamilton Mann would help me understand the broader impact of AI and its ethical challenges.
Next, I would get hands-on experience with AI tools. ChatGPT, Perplexity, and Gamma are useful for research, writing, and presentations. Exploring no-code tools like RunwayML or Google's Teachable Machine would allow me to see how AI models function without needing to code.
Connecting with the AI community would be just as important. I would follow industry leaders on LinkedIn, join discussions, and attend webinars. AI is evolving every day, and being part of the conversation would help me stay informed and find new opportunities.
The best way to learn is by doing. AI is shaping every industry, and understanding how to use it now would open new possibilities for the future.
Share the spotlight: Name 3+ women leading in AI we should all follow.
Here are three women leading in AI who you should follow:
Timnit Gebru - Founder of the Distributed AI Research Institute (DAIR) and a leading voice in AI ethics, fairness, and accountability. She has done groundbreaking work on bias in AI and the social implications of machine learning.
Fei-Fei Li - Co-Director of the Stanford Human-Centered AI Institute and a pioneer in computer vision. Her work has influenced the development of ethical and inclusive AI.
Joy Buolamwini - Founder of the Algorithmic Justice League, advocating for fairness in AI systems and fighting against bias in facial recognition technology.
Others to follow include Rediet Abebe, Rumman Chowdhury, and Danielle Belgrave, who are shaping AI's future across ethics, policy, and healthcare.
As a woman in AI, what do you want our allies to know? As a woman in AI, I want our allies to understand that support is more than encouragement. It requires action, accountability, and a commitment to creating real opportunities.
AI is shaping the future, but too often, the perspectives of women, especially women of color, are overlooked. We are already leading, researching, and building. What we need is recognition, access to resources, and a seat in the decision-making process. Hiring, funding, and leadership must reflect the diversity of the world AI is meant to serve.
True allyship means speaking up when voices are excluded, amplifying the work of women in the field, and ensuring that ethical and inclusive AI is the standard, not the exception.
Special Series: Black History Month
How do you see your work contributing to the broader legacy of Black women in technology?
My work builds on the legacy of Black women in technology by expanding access, representation, and ethical leadership in AI. Those who came before me broke barriers, often without recognition, and made it possible for me to be here. I carry that forward by ensuring AI serves communities that have historically been left out of the conversation.
I focus on equity in healthcare AI, making sure that technology does not reinforce the same biases that have harmed marginalized groups for generations. Through research, advocacy, and education, I work to create pathways for others to enter this field and lead. Representation is not enough. Black women must have decision-making power in how AI is designed and used.
Every step I take is part of a larger movement. I want the next generation to enter this space knowing they belong, their ideas matter, and they have the tools to shape the future. That is the legacy I want to leave.
How can the AI community better engage underrepresented communities in shaping ethical AI practices?The AI community can better support communities in shaping ethical AI practices by ensuring transparency, inclusivity, and accountability at every stage of development.
First, AI must be built with input from the communities it affects. This means engaging diverse voices, especially those historically excluded from technology decision-making. Ethical AI cannot be created in isolation. Researchers, policymakers, and technologists must actively listen to communities, understand their concerns, and incorporate their perspectives into design and deployment.
Second, education and accessibility are essential. Many communities lack the resources to understand how AI impacts their lives. The AI community must invest in AI literacy, ensuring that people have the knowledge and tools to advocate for themselves. Public engagement should not be an afterthought; it should be part of the process from the start.
Finally, accountability must be a priority. Ethical AI practices require more than guidelines and statements. They demand oversight, continuous evaluation, and real consequences when AI harms marginalized groups. Organizations should commit to external audits, open-source reporting, and policies that prevent bias rather than addressing it after harm has been done.
Ethical AI is not just about better technology. It is about centering people, protecting rights, and ensuring that innovation benefits everyone, not just those with power and influence.
What are your hopes for the next generation of Black women entering AI?I hope the next generation of Black women entering AI walks into spaces where they are valued, heard, and leading. I want them to see themselves at every level, from researchers to executives, shaping the future of technology in ways that reflect their communities and experiences.
I hope they do not feel the need to prove they belong but instead step in knowing their ideas, perspectives, and contributions are essential. The barriers that existed for those before them should not be their reality. They should have access to resources, funding, and mentorship that allow them to thrive without fighting for a seat at the table.
I want them to redefine what leadership in AI looks like. They should be the decision-makers, the policy shapers, and the ones ensuring that AI is ethical, fair, and inclusive. Their voices should not be an exception but the norm.
Most of all, I hope they enter this space with confidence, knowing that they are part of a legacy of Black women who have always been innovators, problem-solvers, and leaders in technology.
How can we ensure that AI technologies benefit marginalized communities rather than perpetuate inequities? Ensuring that AI benefits marginalized communities starts with building technology that centers people, not just profits. Developers, researchers, and policymakers must work alongside the communities AI is meant to serve, listening to their needs and concerns before a single line of code is written.
Bias in AI does not come from the technology itself. It comes from the data, the developers, and the systems that shape it. Addressing this requires diverse teams that understand the lived experiences of marginalized groups. Representation at every level of AI development and governance is essential.
Regulation and accountability must be more than afterthoughts. Companies should not be left to police themselves when it comes to bias and harm. Independent audits, transparency in AI decision-making, and policies that protect people from discrimination must be standard practice.
Education and access to AI tools are just as important. Marginalized communities should not only be passive users of AI but active creators. Training programs, funding, and pathways into AI careers need to be prioritized to ensure these communities have the power to shape the future of technology.
AI should not deepen the inequalities that already exist. It should be a tool for equity, opportunity, and progress. That will only happen if those most impacted have a voice in how it is built and used.
A great read and this is something I always point out when I'm training:
There's a lot of talk about the developers and the systems holding this bias, but I would go further to say the users of these AI tools have a responsibility to check the output they're getting for biases. Not an easy thing to do, given we aren't always aware of our own.