Preparing for an AI-driven future in workforce and education
By training prompters to ask the right questions, they can become skilled users who know how to effectively use the right tools.
SHAH ALAM - As Artificial Intelligence (AI) technology advances, Malaysia must prepare its workforce to meet future demands.
Outlining the crucial steps to equip both high-skilled and low-skilled workers for an AI-driven economy, the Malaysian Research Accelerator for Technology & Innovation (MRANTI) AI expert Dr Afnizanfaizal Abdullah said Malaysians should see AI in two polarities.
"Extreme polarities, I would I call it, which are downstream and upstream.
"Upstream involves designing new algorithms, developing new software and introducing new AI models. We need experts, high-skilled workers, intelligent and smart people capable of producing new AI or new algorithms.
"Meanwhile, the other end of the spectrum, the downstream of AI, includes those who use AI," he told Sinar Daily.
He said there were already expert prompters using ChatGPT, with some even calling themselves "sifu (experts) of AI."
Afnizanfaizal said although he disagreed with the label as they were simply acting as prompters rather than true AI experts, this kind of talent was needed because asking the right question was difficult.
He added that the downstream AI focused on helping low-skilled workers by teaching them new skills.
For example, he said by training prompters to ask the right questions, they can become skilled users who know how to effectively use the right tools.
Building a career in AI: Advice for young professionals
For young professionals looking to build a career in AI in Malaysia, Afnizanfaizal highlighted the importance of strong fundamentals.
He said the upstream ones needed to be very strong on the fundamentals.
"They need to take computer science or engineering and master this knowledge, especially mathematics and additional mathematics, to use the skills of maths and physics," he said.
To become a specialist in AI, Afnizanfaizal said a Masters or PhD was often necessary.
He said they usually needed to have at least on-the-job training.
The fundamental knowledge learned from a first-degree student, he said would provide a base from which they can specialise in AI.
He said those who wanted to enter the AI field needed to start as generalists and then delve deeply into their specialty.
