The controversy over Yashasvi Jaiswal’s dismissal during the Boxing Day Test between Australia and India has reignited debate about the role of technology in cricket decision-making.
While much of the focus has been on whether the decision was correct, the deeper issue is how technological tools are used and the subjective nature of decisions, even with advanced aids like Snicko and UltraEdge.
A common belief is that technology ensures complete objectivity. However, tools such as Real-Time Snicko and ball-tracking systems provide data that still needs to be interpreted by humans. In Jaiswal’s case, the third umpire overturned the on-field decision based on visual evidence, despite the absence of a conclusive spike on Snicko.
This demonstrates that, no matter how advanced these tools are, the ultimate decision rests on the umpire’s judgment to interpret evidence and decide if it’s sufficient to overturn the original call.
This subjectivity isn’t a flaw but an acknowledgment of the limits of current technology. Tools like Snicko and UltraEdge are highly advanced but not infallible. For instance, Snicko might fail to pick up faint edges due to microphone sensitivity or external noise, while visual replays can be affected by frame rates or camera positioning.
These tools are designed to assist decision-making, not replace human interpretation.
This raises a broader question: if the third umpire’s role is to follow technological outputs, why not fully automate the process? Why not create a system with defined thresholds, such as “if no spike on Snicko, then not out,” and remove human judgment entirely?
The complexity of cricket makes this unrealistic. The game involves situations that can’t always be reduced to strict rules. Conflicting evidence and nuanced circumstances require understanding and discretion that technology alone can’t provide.
The current system reflects this by positioning the third umpire as an interpreter of technology rather than a passive follower of its outputs. Umpires must evaluate all available evidence, using their expertise and understanding of the game to resolve uncertainties.
Yashasvi Jaiswal speaks with the umpire after being dismissed. (Photo by Daniel Pockett – CA/Cricket Australia via Getty Images)
In Jaiswal’s case, the third umpire determined that the visual evidence of deflection was strong enough to overturn the on-field decision, even without confirmation from Snicko. Whether you agree with the decision or not, it highlights the subjective element in interpreting technological data in real time.
Critics often argue that this subjectivity leads to inconsistency, undermining the credibility of the Decision Review System (DRS). However, eliminating subjectivity entirely isn’t practical or desirable.
A fully automated system would risk creating rigid rules that fail to accommodate the complexities of live sport. Allowing umpires to exercise judgment ensures cricket retains the flexibility and context-awareness that no algorithm can provide.
The goal shouldn’t be to eliminate subjectivity but to manage it effectively. This requires clear protocols, consistent application, and transparent communication so that players and fans understand how decisions are made. The Jaiswal incident serves as a reminder that even with the best technology, cricket remains a human game.
Its charm lies in navigating imperfections with a blend of logic, experience, and intuition.
Looking ahead, technology could better support umpires by assisting not just in data collection but in interpretation. Incorporating AI into decision-making tools could provide more dynamic and context-aware support. AI systems could integrate multiple sources of data—visual evidence, sound patterns, and historical examples—to offer a comprehensive interpretation for the umpire.
For instance, AI might analyse the ball’s trajectory, Snicko outputs, and camera angles to calculate the likelihood of an edge, helping umpires understand the context more effectively.
Such systems wouldn’t replace the third umpire but enhance their role. For example, AI could highlight inconsistencies between visual evidence and Snicko, offering explanations like interference or microphone distortion, along with a probability score for contact.
This approach would give umpires a clearer view of the data while leaving room for their judgment within the rules of the game.
As technology evolves, balancing objectivity with human judgment will remain a key part of cricket’s decision-making process. The third umpire’s role is to bridge the gap between technological aids and human interpretation, making decisions that honour the spirit of the game while acknowledging the tools’ limitations.
It may not be a perfect system, but cricket itself is an imperfect sport. And that’s what makes it so compelling.
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