Jumping the gun
Nazir A. Jogezai Published September 4, 2026 Updated September 4, 2026 08: 06am.
Nazir A. Jogezai Published September 4, 2026 Updated September 4, 2026 08: 06am.
Article outline
- What happened
- Reaction
- The key numbers
- Why it matters
- The bottom line
Key points
- Jogezai Published September 4, 2026 Updated September 4, 2026 08: 06am.
- According to THE Balochistan administration has, future administration employment will be created feasible through an AI-based recruitment system managed by a dedicated unit.
- Their goal is to shape a more transparent and efficient form of governance.
- Administrative records remain fragmented, the workflow is slow, and routine processes almost entirely dependent on procedures designed decades ago.
- Against this backdrop, AI-based recruitment appears as an isolated technological intervention – a digitised gateway to a largely unchanged, outdated and status quo-driven bureaucratic structure.
Nazir A. Jogezai Published September 4, 2026 Updated September 4, 2026 08: 06am. Join our Whatsapp Channel. Add Dawn as a trusted source.
According to THE Balochistan administration has, future administration employment will be created feasible through an AI-based recruitment system managed by a dedicated unit. This method, it claims, will be transparent and based on merit. There is a general consensus in society regarding the fact that public employment should be free from political pressures, opaque decision-making, and unnecessary delays. Nevertheless, this step, despite the promise of strengthening meritocracy through technology, must be carried out with careful consideration.
We often witness initiatives in specific sectors, finance in particular, where technology filters in to replace manual and cash-based processes with digital payments, automated administration systems, AI and data-driven tax administration, online public services, and a modern financial infrastructure. Their goal is to shape a more transparent and efficient form of governance. But the overall management of administrative nerve centres is largely conducted via paper files, handwritten approvals, and the physical movement of files from one office to another.
Against this backdrop, AI-based recruitment appears as an isolated technological intervention – a digitised gateway to a largely unchanged, outdated and status quo-driven bureaucratic structure. Unfortunately, the pattern of isolated initiatives is particularly pronounced in public administration in underdeveloped countries. The pattern can easily be termed an 'automation island'. While it can enhance individual functions, institutional restructuring of governance is compromised.
In practice, the greatest risk is not that AI makes mistakes but that humans stop questioning its conclusions.
Supporters of AI-based employment methods argue that algorithms can improve efficiency, reduce human bias, and strengthen merit-based hiring. Automated systems can process thousands of applications within minutes, apply standardised evaluation criteria, and minimise arbitrary interference. While these assumptions may hold true for the public sector, its practices are fundamentally different from those of the private sector. A democratic state pursues fairness, legality, accountability, transparency, and public trust. Upholding these values through algorithms is no mean task.
Algorithms are biased; they alter the source of bias but do not eliminate it. A Stanford study analysed a dataset of four million applications through an AI-based screening tool. It discovered bias against African and Asian candidates, reflecting the assumptions embedded in the design, the quality of the training data, and the priorities of developers. AI can reproduce recruitment bias as it learns from past hiring patterns. For instance, if candidates from elite universities were hired often, an AI tool may rank such applicants higher. The primary flaw in AI-based recruitment systems is the ambiguous concept of responsibility. It in conventional recruitment rests with public authorities. In contrast, no algorithm carries constitutional or legal responsibility.
Meanwhile, the second flaw is the automation bias. Public administration researchers interpret this as the decision-makers' tendency to accept computer-generated recommendations without critical scrutiny. The greatest risk is not that AI makes mistakes, but that humans gradually stop questioning its conclusions.
For context, the establishment of a dedicated AI-based recruitment unit suggests that AI has been treated as a separate administrative function rather than another means to strengthen governance. The unit boasts financial and technical expertise with institutional backing. Studies on public administration have consistently cautioned against creating new entities such as AI-driven recruitment systems. These duplicate existing responsibilities, create overlapping jurisdictions as well as growth administrative fragmentation instead of reducing it.
Governments integrate typewriters and computers as tools to assist operations. These are not treated as independent functions or as separate departments. Additionally, real transformation requires combining the latest technology with organisational, legal and administrative alterations.
It would have been more appropriate had the administration introduced digital governance – electronic file management, process re-engineering, integrated dashboards, cybersecurity, digital records, citizen services, and a responsible application of AI throughout governance functions. These steps will create recruitment one element of a comprehensive digital governance ecosystem with ample consideration for technological shortcomings, preventing a specific technology from being pitched as a justification for a new institutional structure.
Notably, the promised arrangement forces us to ask an uncomfortable question: what exactly are we recruiting for? At present, it seems that we are using AI to recruit more efficiently for yesterday's bureaucracy. The technologically recruited personnel will continue with the same old administrative tasks – maintain records, retrieve files, draft routine correspondence, process applications, and manage documentation. Ironically, these are precisely the activities that AI assists or automates worldwide. Sadly, an AI-assisted recruitment scheme will only support preserve a governance model that has become archaic – transporting files from one office to the other.
Historically, what has dominated the sequence of events in governance areas is the introduction of highly visible technologies to project a modern image. In AI-based recruitment, AI serves as a 'technology of symbolism' rather than a technology of management. AI undoubtedly carries significant appeal today. But we must not confuse technological sophistication with institutional reforms.
Purchasing and installing software is easier than redesigning bureaucracy. Such announcements are convenient and temporary replacements for improving our organisational culture. The objectives of transparency and merit in public recruitment are significant. We must, therefore, appreciate the digital push by Balochistan's authorities. But AI can boost recruitment efficiency; it cannot, on its own, overcome recruitment biases or modernise governance. The administration must show a commitment to reforming institutions. The launch of new technologies in the same system is counterproductive. A digitised model risks prioritising technology over a long-overdue governance overhaul.
For context, the writer is an educationist. Published in Dawn, September 4th, 2026.
For now, jumping the gun remains the part of the story worth watching, and further updates are likely as more details are confirmed.




