The Kwame Nkrumah University of Science and Technology (KNUST) College of Engineering has reaffirmed its commitment to using Artificial Intelligence (AI) and locally sourced data to address specific societal challenges.

The College made the pledge as it closed its 11th Summer School, which focused on advancing AI for research, teaching, and innovation in engineering education.

The session featured presentations and hands-on demonstrations that showcased AI’s growing role in improving research workflows and engineering processes.

Prof. Emmanuel Kofi Akowuah, Head of the Department of Computer Engineering, presented on AI in Engineering Research.

He explained how AI is transforming research through faster literature reviews, advanced simulations, and smarter data analysis.

“AI-driven simulations are a game-changer,” Prof. Akowuah said. “They reduce computation time, improve accuracy, and make it possible to model complex scenarios.”

He highlighted tools such as Elicit, Consensus, and Scite, which help researchers analyse data and manage information efficiently.

Prof. Akowuah urged stronger cross-disciplinary collaboration. “Engineers define the problems, and AI assists in exploring innovative solutions,” he said.

During the discussion, participants raised concerns about the ethical use of AI. Prof. Akowuah clarified that AI complements human creativity rather than replacing it.

“AI acts as a powerful scout, sifting through millions of papers to narrow research focus. It augments intelligence, it doesn’t remove it,” he said.

Dr. Andrew Selasi Agbemenu, Deputy Scientific Director of the DIPPER Lab, and other participants emphasised the importance of grounding postgraduate research in local data.

“AI must be used to solve local problems with locally relevant datasets,” he said.

Dr. Henry Nunoo-Mensah, AI in Health Theme Lead at the Responsible AI Lab (RAIL), led a practical session demonstrating how tools such as Elicit, Semantic Scholar, and Research Rabbit streamline literature reviews.

He also showcased Google Colab for data analysis, describing AI as “a productivity multiplier.”

Prof. Kwabena Biritwum Nyarko, Provost of the College of Engineering, closed the session by commending the organisers and highlighting the importance of hands-on learning. “We need more practical, skill-based training to fully harness AI’s potential,” he said.