AI For The People programme to prepare youths for changing labour market, says Ramanan

TEXT START: KUALA LUMPUR: The AI for the People Programme, which targets 100,000 youths aged between 18 and 30, is an important step towards preparing Malaysia’s workforce for rapid changes in the employment landscape, said Datuk Seri R. Ramanan.

THE DISSECTION

The text converts a structural displacement problem into a skills-access problem. It presents training, subsidised AI applications, digitalisation and financing as evidence that workers can be carried through the transition. It provides no analysis of net job creation, wage pressure, worker bargaining power, ownership of AI capital, or what happens when the three-month subscriptions expire.

The programme may make some youths more productive. That is not the same as making them economically necessary. It is a state-managed adaptation narrative wrapped in the language of inclusion.

THE CORE FALLACY

The central error is assuming that relevant skills generate durable demand for human labour. Under the Discontinuity Thesis, AI does not merely give workers better tools; it makes cognitive work cheaper, faster and more scalable. A trained worker may produce more, while employers require fewer workers.

The programme therefore risks accelerating the very displacement it claims to manage. It gives youths access to rented instruments, not control of productive capital. They become users competing within systems owned by Sovereigns. A small minority may become indispensable Servitors, transition intermediaries or Hyenas. The majority remain replaceable inputs with improved software access.

HIDDEN ASSUMPTIONS

• AI will complement enough workers rather than eliminate the need for them.
• Skills labelled relevant today will retain scarcity as AI capability improves.
• Three months of application access will become durable income or employment.
• Productivity gains will flow to wages instead of primarily increasing margins and asset values.
• Economic growth will create enough new human roles to offset automated labour.
• Credentials and training can overcome concentrated ownership of AI, energy, logistics and infrastructure.
• Institutions can preserve stable human-only economic domains at scale.
• The promise that no one will be left behind is an economic forecast rather than political reassurance.

SOCIAL FUNCTION

Primary classification: transition management.

Secondary classifications: ideological anesthetic and partial truth.

The initiative is a genuine lag defense. Training can help a narrow slice of people capture temporary niches, operate AI systems, serve as verification layers or build small businesses. But the rhetoric recodes declining labour demand as worker inadequacy. If people fail, the implied explanation becomes that they did not acquire enough skills, rather than that ownership and automation made mass participation unnecessary.

The references to fuel subsidies, medical digitalisation, e-Invoicing and micro-business financing expose the broader function: administer the social effects of transition while preserving the appearance of inclusive growth. The state is cushioning the passengers while the engine room is being automated and sold off.

THE VERDICT

Useful programme, false diagnosis. It may produce 100,000 more AI-literate workers, but it cannot preserve the mass employment-to-wage-to-consumption circuit. At best, it manufactures a thin layer of Servitors and transition intermediaries around concentrated AI capital. Without ownership, durable income rights or control over the productive system, this is workforce preparation for a labour market that is progressively preparing to need fewer workers.