Dr Fazal Ali
Superintelligence, the climate transition, screen economies, data-driven innovation, AI for security, security for AI, and AI-Accelerated threats have dismantled outdated arrangements. This tearing apart of the past creates space for new institutional arrangements. Exigencies are always painful, but they offer rare opportunities to build consensus in democracies wishing to avoid the middle-income trap.
Middle-income countries need frequent informed public dialogue to dismantle stubborn institutions and undo long-standing arrangements.
In these countries, even though 4G network coverage, the main technology bringing people online, is about 95 per cent, some regions still lack access to high-speed fibre-optic networks, and services are not as affordable as in other regions.
Middle-income countries may need to review their national fibre-optic backbones and backhaul networks, and how they connect public institutions in areas without service or with poor coverage. Some may benefit from landing new subsea fibre-optic cables to improve network reliability and avoid single-path vulnerabilities.
Rural infrastructure operators may be deployed, and community networks promoted, through the allocation of free and dynamically used spectrum. Defining distinct markets within the sector can help identify those that need additional regulation, especially where countries may only differentiate between fixed and mobile markets.
The whole world is in an AI race. Middle-income countries are home to about six billion people. In the AI race, many countries face extreme capital burn rates, heavy reliance on partner cloud providers, and distribution disadvantages against vertically integrated giants. About 108 countries are classified as middle-income.
Depending on their size, geographic position, and stage of economic development, they will need to adopt ideographic AI strategies that can lead to a rich policy mix. They can begin by focusing on “1i” policies that increase investment in state-of-the-art digital technologies and their widespread domestic infusion.
After that, middle-income countries can shift to a “2i” policy mix of investment and infusion. The third “i” of the “3i” method layers data-driven innovation across the economy’s digital fabric and AI architecture. Countries must note that the AI transition threatens to fold the traditional “development ladder” for emerging economies, making it much harder to escape the middle-income trap, a state in which countries stall after initial growth and fail to reach high-income status.
Traditional growth models of middle-income nations relied on cheap labour to attract manufacturing or outsource routine service jobs. AI and automation replace this low-cost advantage, enabling advanced nations to “reshore” production rather than sending jobs down the income ladder.
Developing economies historically used low-end manufacturing and basic technology adoption to gradually upgrade their industrial base. AI-driven, capital-intensive production cuts off these stepping stones. High entry costs for integrated digital infrastructure and advanced data systems widen the gap between wealthy nations and middle-income countries struggling with basic power and internet access.
Countries must drastically upgrade education and digital skills pipelines to foster a human-machine collaborative model rather than competing on raw labour costs.
Middle-income countries also face unbalanced and inadequate development, driven by the uneven distribution of wealth along the urban/rural continuum, which superintelligence could amplify.
Governments everywhere are paying more attention to the Moral Economy in the Age of AI and to fake impressions about infallible AI models. Unbeknownst to ordinary people, they actively participate in the mobilisation and circulation of norms and values that shape whether we enable superintelligence or resist its uptake.
Morals never reside in individuals. They are affectively charged formations that individuals come to inhabit. What is “moral” is historically constituted and culturally situated, and it changes with time.
During the infosphere revolution, the mobilisation and circulation of norms and values have the most profound effect on “floating” youth, who find it unsettling to grasp the improbability of the unfolding future. They face the contradiction between wanting a better life and living in a world of unbalanced development.
Education no longer reduces their vulnerability if it fails to prepare them for an AI-infused workplace. Many opt for “lying flat” to avoid intense competition for work.
The old tertiary enrolment playbook is no panacea if curriculum tracks yield worn-out qualifications. Ordinary people now critique how digital technologies are narrated and legitimised through stories of optimism and future-making. Some unpack how the mobilisation of charisma celebrates some lives and not others.
Some discourses claim that technical interventions solve urban poverty and frame them through tropes of “hope” and the promise of better resources and skills.
Work on the moral economy now examines how digital technologies, gig platforms, and digital ID systems are enacted as “good” and “virtuous” despite the exploitative labour conditions and social injustices they can produce.
We have also seen how attachments to the ideal of making technology “useful” can frame technological “upgrading” as a virtuous endeavour, masking exhaustion and exploitation. Superintelligence is not neutral. Superintelligence is humans.
Dr Fazal Ali completed his Master's in Philosophy at the University of the West Indies. He was a Commonwealth Scholar who attended the University of Cambridge, Hughes Hall; the Provost of the University of Trinidad and Tobago; the acting President of UTT; and the Chairman of the Teaching Service Commission. He is the President of NIHERST and an external services consultant with the IDB.
