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This Week in AI: How Kamala Harris might regulate AI

Hiya, folks, welcome to TechCrunch’s regular AI newsletter. Last Sunday, President Joe Biden announced that he no longer plans to seek reelection, instead...
HomeTechnologyWomen in AI: Charlette N'Guessan is tackling data scarcity on the African...

Women in AI: Charlette N’Guessan is tackling data scarcity on the African continent


To give AI-focused women academics and others their well-deserved — and overdue — time in the spotlight, TechCrunch is launching a series of interviews focusing on remarkable women who’ve contributed to the AI revolution.

Charlette N’Guessan is the Data Solutions and Ecosystem Lead at Amini, a deep tech startup leveraging space technology and artificial intelligence to tackle environmental data scarcity in Africa and the global South.

She co-founded and led the product development of Bace API, a secure identity verification system utilizing AI-powered facial recognition technology to combat online identity fraud and address facial recognition biases within the African context. She’s also an AI expert consultant at the African Union High Level Panel on Emerging Technologies and works on the AU-AI continental Strategy titled “Harnessing Artificial Intelligence for Africa’s Socio-Economic Development” with a focus on shaping the AI governance landscape in Africa.

N’Guessan has also co-authored several publications and is the first woman recipient of the Africa Prize for Engineering Innovation awarded by the Royal Academy of Engineering.

Briefly, how did you get your start in AI? What attracted you to the field?

I have an engineering background from a formal and informal education. I have always been passionate about the use of technology to build solutions that would positively impact my communities. This ambition led me to relocate to Ghana in 2017, where I aimed to learn from the anglophone market and kickstart my tech entrepreneurial journey.

In the development process of my startup, my former co-founders and I conducted market research to identify challenges in the financial sector, resulting in online identity fraud. We then decided to build a secure, reliable, and effective solution for financial institutions to bridge the gap in serving the unbanked populations in remote areas and establish online trust. This led to a software solution leveraging facial recognition and AI technologies, tailored to facilitate organizations in processing online client ID verification while ensuring our model was trained with representative data from the African market. This marked my initial involvement in the AI industry. Note that in 2023, despite our efforts, we encountered various challenges that led us to stop commercializing our product on the market. However, this experience fueled my determination to continue working in the AI field.

What attracted me to AI was the realization of its immense power as a tool for solving societal problems. Once you grasp the technology, you can see its potential to address a wide range of issues. This understanding fueled my passion for AI and continues to drive my work in the field today.

What work are you most proud of in the AI field?

I am incredibly proud of my journey as a deep tech entrepreneur. Building an AI-driven startup in Africa isn’t easy, so for those who have embarked on this journey, it’s a significant achievement. This experience has been a major milestone in my professional career, and I am grateful for the challenges and opportunities it has brought.

Currently, I am proud of the work we do at Amini, where we are tackling the challenge of data scarcity on the African continent. Having faced this issue as a former founder myself, I am very grateful to work with inspiring and talented problem solvers. Today, my team and I have developed a solution by building a data infrastructure using space technology and AI to make data accessible and comprehensible. Our work is a game-changer and a crucial starting point for more data-driven products to emerge in the African market.

How do you navigate the challenges of the male-dominated tech industry and, by extension, the male-dominated AI industry?  

Truth is, what we are facing today in the industry has been shaped by societal biases and gender stereotypes. This is a societal mindset that has been nurtured for years. Most of the women working in the AI industry have been told at least once that they were in the wrong industry because they were expected to be  A, B, C and D.

Why should we have to choose? Why should society dictate our paths for us? It’s important to remind ourselves that women have made remarkable contributions to science, leading to some of the most impactful technological advancements that society is benefiting today. They exemplify what women can achieve when provided with education and resources.

I am aware that it takes time to change a mindset, but we can’t wait; we need to continue encouraging girls to study science and embrace careers in AI. Honestly, I’ve seen progress compared to previous years, which gives me hope. I believe that ensuring equal opportunities in the industry will attract more women to AI roles, and providing more access to leadership positions for women will accelerate change toward gender balance in male-dominated industries.

What advice would you give to women seeking to enter the AI field?

Focus on your learning and ensure you acquire the skills needed in the AI field. Understand that the industry may expect you to demonstrate your capabilities more intensely compared to your male fellows. Honestly, investing in your skills is crucial and serves as a solid foundation. I believe this will not only boost your confidence in seizing opportunities but also enhance your resilience and professional growth.

What are some of the most pressing issues facing AI as it evolves?

Some of the most pressing issues facing AI as it evolves include challenges in articulating its short-term and long-term impacts on humans. This is currently a global conversation due to uncertainty surrounding emerging technologies. While we have witnessed impressive applications of AI in industries globally, including in Africa, particularly with the recent advancements in generative AI solutions and the capability of AI models to process vast volumes of data with minimal latency, we have also observed AI models riddled with various biases and hallucinations. The world is undeniably moving toward a more AI-driven future. However, several questions remain unanswered and need to be addressed:

  • What is the future of humans in the AI loop?
  • What is the appropriate approach for regulators to define policies and laws to mitigate risks in AI models?
  • What does AI responsibility and ethical framework mean?
  • Who should be held accountable for the outcomes of  AI models?

What are some issues AI users should be aware of?

I like to remind people that we are all first AI users before any other title. Each of us interacts with AI solutions in various ways, whether it’s directly or through our people (such as family members, friends, etc.) using various devices. That’s why it is important to have an understanding of the technology itself. One of the things you should know is that most AI solutions on the market require your data, and as a user, be curious to understand the extent of control you give the machine over your data. When considering consuming an AI solution, consider data privacy and the security offered by the platform. This is crucial for your protection.

Additionally, there has been a lot of excitement about generative AI content. However, it’s essential to be cautious about what you generate with these tools and to discern between content that is real and that which is false. For instance, social media users have faced the spread of deepfake-generated content, which serves as an example of how people with malicious intentions can misuse these tools. Always verify the source of generated content before sharing it, to avoid contributing to the problem.

Lastly, AI users should be mindful of becoming overly dependent on these tools. Some individuals may become addicted, and we’ve seen instances where users have taken negative actions based on recommendations from AI chats. It’s important to remember that AI models can produce inaccurate outcomes due to societal biases or other factors. In the long-term, users should strive to maintain independence to prevent potential mental health issues arising from unethical AI tools.

What is the best way to responsibility build AI?

This is an interesting topic. I have been working with the High Panel on Emerging Technologies of the African Union as an AI expert consultant, focusing on drafting the AU-AI continental strategy with stakeholders from various backgrounds and countries involved. The goal of this strategy is to guide AU member states to recognize the value of AI for economic growth and develop a framework that supports the development of AI solutions while protecting Africans. Some key principles I always advise considering when building responsible AI for the African market are as follows:

  • Context matters: Ensure your models are diverse and inclusive to address societal discrimination based on gender, regions, race, age, etc. 
  • Accessibility: Is your solution accessible by your users? For instance, how to ensure that a person living in a remote area benefits from your solution.
  • Accountability: Articulate who is responsible when model results are biased or potentially harmful.
  • Explainability: Ensure that your AI model results are comprehensible to stakeholders.
  • Data privacy and safety: Ensure you have a data privacy and safety policy in place to protect your users and you comply with existing laws where you operate.

How can investors better push for responsible AI? 

Ideally, any AI company should have an ethical framework as a mandatory requirement to be considered for investment. However, one of the challenges is that many investors may lack knowledge and understanding about AI technology. What I have learned is that AI-driven products don’t undergo the same investment risk assessment as other technological products on the market.

To address this challenge, investors should look beyond trends and deeply evaluate the solution at both the technical and impact levels. This could involve working with industry experts to gain a better understanding of the technical aspects of the AI solution and its potential impact at the short- and long-term.



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