Online Reporter
Dr Evans Sagomba
Everything AI
WE are at a pivotal moment in Zimbabwe.
Technology, particularly Artificial Intelligence (AI), is rapidly transforming the way we live, work, and interact. Mobile money facilitates transactions, online services connect us, and data-driven decisions shape our futures.
But with these advancements come critical questions: Are we simply adopting AI, or are we shaping it to align with our values? Are we ensuring that technology serves the people, rather than the other way around?
The conversation around AI often revolves around “ethics.” But what if we aim higher? What if we strive for “Artificial Integrity”, building honesty, fairness, and a commitment to human values directly into AI systems from the very beginning?
Many view AI ethics as a mere compliance exercise, a set of guidelines to avoid penalties.
Instead, Artificial Integrity views responsible AI as an opportunity to improve society meaningfully.
Think of it this way: Ethical AI provides the framework, the rules we are supposed to follow.
Artificial Integrity is the outcome, the AI system’s inherent ability to act fairly, safely, and in alignment with human values. Ethical AI tells us what not to do; Artificial Integrity inspires us to build systems that do good.
The concept of Artificial Integrity is not new.
AI researcher, Hamilton Mann, has championed this idea, arguing that systems designed with a sense of moral obligation (“because we should”) are fundamentally different from those designed purely for their technical capabilities (“because we could”).
Mann’s work challenges us to move beyond a purely utilitarian approach to AI and to consider the ethical implications of every design choice.
So, why does Artificial Integrity matter now, especially for Zimbabwe?
Zimbabwe is undergoing a rapid transformation, embracing digital technologies at an unprecedented pace.
As AI seeps into various sectors, from finance to healthcare to agriculture, it is crucial to ensure that these systems are designed with integrity at their core.
We need to ask not only what AI can do, but what it should do.
Consider the potential for bias in AI algorithms. If the data used to train these algorithms reflects existing societal inequalities, the AI system may perpetuate and even amplify these biases, leading to unfair or discriminatory outcomes.
For example, an AI-powered loan application system trained on biased data could unfairly deny loans to individuals from marginalised communities.
Artificial Integrity demands that we proactively address these risks by carefully curating training data, implementing robust testing procedures, and establishing mechanisms for human oversight.
It requires a commitment to transparency, ensuring that the decision-making processes of AI systems are understandable and accountable.
This is not just about avoiding harm; it is about harnessing AI for positive social impact.
Imagine AI systems that can detect and prevent fraud, improve access to healthcare in remote areas, or optimise agricultural practices to enhance food security. By embedding integrity into these systems, we can ensure that they contribute to a more just and equitable society.
One key difference between ethical AI and Artificial Integrity lies in their approach to rules.
Many organisations treat ethics as a checklist, focusing on compliance with regulations and policies.
While these regulations are important, they are not enough.
Artificial Integrity demands a shift from simply following rules to embodying them. It means building systems that behave fairly and transparently by design, reflecting our values in every decision they make.
This requires a holistic approach that goes beyond simply writing policies. It means fostering a culture of integrity within organisations, empowering employees to identify and address ethical concerns, and investing in ongoing training and education. It means testing AI systems rigorously, monitoring their performance continuously, and fixing them promptly when they go wrong.
Fortunately, we’re not starting from scratch. International frameworks like the European Union’s AI Act and the NIST AI Risk Management Framework provide valuable guidance for building integrity into AI systems.
The EU AI Act, for example, classifies AI systems based on their risk level and imposes strict regulations on high-risk applications, while the NIST framework offers practical steps for managing AI risks and building trustworthy systems.
However, these frameworks are not blueprints to be copied blindly.
Zimbabwe must adapt them to its own unique context, considering its specific needs, challenges, and values. We need to engage in a national dialogue to determine how best to implement these principles in a way that reflects our aspirations for a fair and inclusive society.
Zimbabwe has already taken important steps in the right direction. The introduction of data protection regulations in 2024, requiring registration for processing personal information and establishing roles like Data Protection Officers, demonstrates a commitment to responsible data governance. But laws alone will not create integrity. We need practice, oversight, and public understanding to truly embed integrity into our technological landscape.
So, what does this practice look like in concrete terms?
It starts with small, steady steps.
Organisations should begin by mapping where AI is currently being used within their operations, identifying potential risks and opportunities. They should test systems for unfair outcomes, ensuring that they are not perpetuating existing biases. They should keep humans in the loop for important decisions, providing a layer of oversight and accountability.
Training staff to spot bias and errors is crucial.
Employees need to be equipped with the knowledge and skills to critically evaluate AI outputs and to identify potential ethical concerns.
Organisations should also choose vendors who are transparent about how their systems work, providing clear explanations of their algorithms and decision-making processes.
Ultimately, integrity needs to become part of daily work, not just a yearly audit. Simple, consistent habits are what build trust and ensure that AI systems are aligned with our values. Business leaders have a particular responsibility to champion Artificial Integrity within their organisations.
They should develop a clear plan for implementing these principles, starting by identifying high-impact uses of AI. They should conduct regular audits to assess the ethical performance of their systems and publish plain-language explanations of automated decisions to enhance transparency.
Appointing individuals who can answer questions from the public is essential. These “AI ambassadors” can serve as a bridge between the organisation and the community, addressing concerns and fostering trust.
Leaders should also budget for training and independent reviews, demonstrating a commitment to continuous improvement and accountability.
These steps may require an investment of time and money, but they are essential for mitigating risks and building confidence in AI systems.
By prioritising Artificial Integrity, business leaders can position their organisations for long-term success in an increasingly digital world. But the responsibility for shaping Zimbabwe’s technological future does not rest solely on the shoulders of business leaders and policymakers. Ordinary citizens also have a crucial role to play.
Every individual can contribute to the conversation by asking for clear explanations when an automated decision affects them. Whether it’s a loan application, a job interview, or a government service, citizens have the right to understand how AI is being used and to demand transparency from service providers.
Dr Evans Sagomba is a Doctor of Philosophy and Chartered Marketer (CMktr, FCIM) with an MPhil and PhD in Philosophy. He specialises in AI, Ethics, and Policy Research, and is an AI Governance and Policy Consultant. His expertise extends to the Ethics of War and Peace, Philosophy of Development, and Political Philosophy. [email protected]. ORCID: 0009-0007-0681-0329.
LinkedIn; @ Dr. Evans Sagomba (MSc Marketing)(FCIM )(MPhil) (PhD)
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