Ben-Koko: Tech Should Aid, Not Replace Human Judgment

February 19, 2026 Blessing Dada

Ben-Koko: Tech Should Aid, Not Replace Human Judgment

Mayen Ben-Koko, a biomedical engineer and digital systems practitioner, has urged organizations to treat technology as a support tool rather than a substitute for human judgment.

Ben-Koko, who holds a master’s degree in biomedical engineering from Queen Mary University of London, works at Giboel and Co. Ltd in the United Kingdom. Her work focuses on how machine learning and data systems function in real-world healthcare and operational environments.

Speaking in an interview, she warned against the growing tendency to adopt advanced tools simply because they are trending. She said long-term value often comes from well-structured systems, not flashy innovation.

“I focus on systems that work reliably over time,” she said. “Success is not about how sophisticated a solution looks at launch. It is about whether it continues to serve people effectively after the excitement fades.”

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Ben-Koko explained that academic research encourages experimentation. Applied environments, however, demand restraint. In healthcare and other high-stakes sectors, systems must account for failure points, workflow clarity and human oversight.

She noted that many digital projects collapse not because algorithms fail, but because foundational systems are weak. Unclear data definitions, fragmented workflows and duplicated records often undermine advanced analytics.

In one operational setting she reviewed, teams relied on conflicting versions of the same data. Predictive models functioned as designed, yet outputs proved difficult to act on. The problem was not technical complexity. It was poor alignment.

According to her, machine learning only adds value when problems are clearly defined and data is consistent. In regulated sectors, she said interpretability matters more than marginal performance gains. Decision-makers must understand and question system outputs.

Ben-Koko also stressed that responsible digital practice begins with restraint. Not every decision should be automated. Systems must remain auditable and transparent, especially where outcomes affect lives.

She added that incremental improvements often produce greater impact than new models. Clarifying workflows, removing duplication and stabilizing data structures can transform usability without adding technical layers.

“Technology should aid human judgment, not replace it,” she said. “Trust, reliability and context must come first.”