By – Dr Anirban Ghosh
Associate Professor, Dept of Electronics and Communication Engineering and AiTI, SRM University-AP( Amaravati)
A race car needs brakes, and not for the reason most people assume. Good brakes do not exist to make a car slow; they exist so a driver can hold the accelerator longer into every turn. A driver who does not trust the brakes is simply left with no choice but to back off before the corner, simply as insurance against the unknown. Strange as it sounds, the better the brakes, the faster the lap tends to be.
This is worth keeping in mind as fresh debate emerges about the development of artificial intelligence. It has settled into a familiar and somewhat lazy shape, in which AI either races ahead with as few constraints as possible, or gets reined in through rules, audits, and oversight. This, however, should never be a binary choice between speed and caution; rather, such an assumption can roll back the years of progress that AI currently enjoys. Guardrails rarely serve as a ceiling to the speed of development but are the very reason it can move quickly without worrying about a disaster that can bring it crashing down.
The history of civil aviation is a case in point over here. When international bodies began standardising safety protocols for commercial flight through the mid-twentieth century, including certified design of aircraft and mandatory training for pilots, the industry did not slow. In contrast, it grew, as ordinary passengers had a concrete reason to believe that flying was safe, and filled the seats. Remove that scaffolding, and air travel would likely have remained a curiosity for enthusiasts and daredevils, regardless of the development.The other side of the coin is just as instructive, and arguably more common. When a technology is built with safety as an afterthought, it is more likely to lose public trust early. Confidence, once broken, takes far longer to rebuild than it would have taken to establish carefully in the first place. In either of the cases, speed was never the concern that stalled progress;it was trust, or the lack of it.
Artificial intelligence now sits at a similar fork, and the timing matters. The capabilities of the new models are advancing at such a breakneck pace that even seasoned researchers often describe it as difficult to fully track.The people at the heart of such development have thus recently started to argue about slamming the brakes.The concern stems from the gap between the increasing capability of the new models and the collective ability of the developers to understand or steer them. Governments, for their part, tend to worry about the issue from a different angle entirely. wary of imposing rules that might hand a strategic advantage to rivals who show no sign of slowing down. Both camps, despite their disagreement, tend to describe the situation the same way: as a trade-off, in which any country or company must pick either safety or speed and quietly give up the other.Amidst this tug-of-war, the end user appears to be at unease,for in the current state, AI can neither be ignored nor be used with confidence.The framing is not quite right, though;the real question is not whether the development of the new models should slow down. It is whether the models come with brakes, and whether those can be trusted to work when needed.
In practice, the introduction of safeguards in the new models might sound unglamorous and can also lead to a temporary initial lag in releasing them. However, rigorous testing of the models for various possibilities, clearly demarcated lines of accountability, and transparent audits by external experts in the domain can not only alleviate the concern of hasty patches if something falls through the cracks but also instil confidence in the models.There is a parallel in how the airline industry works where each aircraft is rigorously tested in-house and examined by experts before it is cleared to fly. None of this amount to an argument for caution over ambition. If anything, it argues the opposite. The countries and companies that build reliable brakes into their models early, rather than as an afterthought, are the ones best placed to go further and faster later.A model built with inherent guardrails will not keep needing to slam on the brakes every time something worrying surfaces but can stay on the accelerator.
The debate keeps circling the question of whether the development of AI models should slow down, and that may simply be the wrong question to keep asking. A sharper one is what kind of guardrails would let the development of the models go faster,uninterrupted by the trust-breaking stops. A car without brakes is not free but is simply dangerous at any speed. Similarly, the goal here should not be to reduce the pace of development but to have appropriate levers that can be trusted even at full throttle.
