Dark side of Artificial Intelligence: Challenges, concerns in Africa

12 Apr, 2024 - 00:04 0 Views
Dark side of Artificial Intelligence: Challenges, concerns in Africa A big problem with using Artificial Intelligence in Africa is that there is not enough data for African researchers

The ManicaPost

 

Chipo Chifamba and Sarah Mkorongo

AS Artificial Intelligence (AI) technologies continue to advance and become more widely adopted across Africa, there are valid concerns about how these systems may inadvertently threaten human rights on the continent if not developed and applied responsibly.

While AI holds great promise to help solve many challenges, from improving healthcare to boosting economic opportunities, its use also brings risks that must be addressed.

One area that requires careful consideration is how AI could negatively impact civil and political rights.

 

As governments and companies collect more personal data to train algorithms, citizens’ privacy and freedom of expression are at higher risk.

 

The Worldcoin project in Kenya, where individuals were asked to scan their eyeballs for tokens, raised privacy and ethical questions.

Economic and social rights are also vulnerable if AI exacerbates existing inequalities or lack of opportunity.

 

As AI streamlines decision-making in areas like credit, hiring and public services, marginalised groups face a greater threat of unfair “automation bias” if training data and programme design do not account for structural disadvantages.

For instance, AI scoring used by some Zimbabwean banks to assess loan eligibility was found to systematically disadvantage women entrepreneurs due to biases in the historical lending data.

Artificial Intelligence has been developed and integrated mostly in the Global North since it was founded.

 

This power concentration is directly related to the colonial past of resource extraction from the Global South, which robbed these countries of their industrialisation potential and democracy.

For instance, African governments’ lack of infrastructure investment to support digital economies has hampered the development of digital literacy, one of the difficulties and risks linked with AI.

For example, Microsoft collaborated with Nigeria to enhance its digital economy by investing in internet infrastructure, training digital skills to five million people, developing anti-corruption tools, and utilising AI to protect cultural assets.

While tech giants like Microsoft, Twitter, IBM, Facebook, and Google have a strong presence in Africa, it is important to watch them closely.

 

Their main goal in Africa may be more about making money and gaining power than truly helping.

Another concern is the lack of local AI talent.

 

Artificial Intelligence is now common, and big tech companies are working to make AI development fair and accessible worldwide.

 

 

 

Companies like Google and Microsoft are setting up research and support centres in less developed areas.

 

While this seems good, it might not help local workers if they don’t have the right skills.

 

This could lead to outsiders with better training taking jobs, which is like old colonial patterns.

A big problem with using Artificial Intelligence in Africa is that there is not enough data for African researchers, especially data that are relevant to local issues like farming, healthcare, and language recognition.

Machine learning needs a lot of data to work well, and if it is not available, the AI might not work and could even hurt people who are already at risk.

 

In Western countries, such as the United States, there has been increasing awareness and discussion about the lack of representation of minorities, like black people and women, in datasets.

This issue was recognised and addressed more frequently in recent years.

 

However, the focus on dataset bias has been on Western-centric issues, which means that it overlooks other types of biases that can occur in non-Western regions, often referred to as the Global South.

In these areas, race may not be the primary social division, and therefore, concentrating only on racial representation misses other important aspects of dataset bias that affect these regions.

Many African nations still lack legal frameworks that can handle the complexities of Artificial Intelligence.

 

There is still more to be done to fully address the concerns of accountability, transparency, and the defence of citizens’ rights in the face of self-governing entities.

Ethical issues are also quite important.

 

AI poses a serious risk of aggravating already-existing inequalities, violating privacy, and maintaining prejudices.

 

AI systems trained on non-representative data may produce biased outcomes that further marginalise vulnerable groups in an area with a diverse and complicated social framework.

Looking ahead, African governments, companies, and civil society must work together to ensure that AI’s development follows principles of human rights, non-discrimination, transparency, and community participation.

International organisations too have a role to play, through guidelines, best practices, and monitoring, to help countries avoid potential harms while capturing AI’s benefits.

 

With proactive policymaking and oversight, Africa’s nations can work to establish themselves as leaders in deploying new technologies responsibly and for the betterment of all people.

 

Chipo Chifamba and Sarah Mkorongo are students at Africa University in the Faculty of International Relations and Diplomacy

 

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