Ibironke Adegoke urges transparency in AI decision-making systems

Ibironke Adegoke, a data analyst with expertise in artificial intelligence (AI) and data analytics, has called for greater transparency in AI decision-making systems. In her recent remarks, Adegoke highlighted the growing importance of clear, understandable AI processes as these technologies increasingly influence decisions in sectors ranging from healthcare to finance.

Adegoke, who has extensive experience working with data in environments where human judgment and technology intersect, emphasised that transparency is key to ensuring trust and accountability in AI systems.

“As AI continues to be integrated into critical decision-making processes, it is vital that these systems are not black boxes. When decision-makers cannot understand how an AI reached a conclusion, it undermines trust, particularly in industries where decisions can have serious consequences on people’s lives,”she said.

The issue of AI transparency has become more urgent as complex algorithms, particularly deep learning models, are deployed in areas such as risk assessment, healthcare diagnostics, and fraud detection. Adegoke pointed out that the lack of clarity surrounding how these models work raises ethical concerns, particularly when the consequences of an AI-driven decision can be far-reaching, such as in financial loans or medical treatments.

Drawing from her experience working with the Department for Work and Pensions (DWP), Adegoke discussed how AI’s ability to analyse large datasets can enhance decision-making but also highlighted the potential dangers of opaque systems.

“AI can be an incredibly powerful tool, but we must ensure that every decision it makes is interpretable, auditable, and explainable. Without transparency, there is a risk of making unfair or biased decisions that can harm individuals or groups,” she said.

In addition to the ethical implications, Adegoke stressed that transparency also plays a crucial role in mitigating bias in AI. “AI systems are only as good as the data they are trained on. If the data is flawed or biased, the results will be too. We need transparency to ensure that these systems are trained fairly and that the decisions they make reflect the diversity and complexity of the real world,” she explained.

Adegoke’s comments come at a time when AI is becoming an integral part of decision-making in a wide range of industries. As AI continues to evolve, ensuring that these systems are not only efficient but also ethical and understandable will be essential for their long-term success. She called on both tech companies and regulatory bodies to take action to develop AI systems that prioritize explainability and fairness, ensuring that these tools benefit society as a whole.