Two steps forward and three steps back / I long to run ahead / In the rat race / I long to run fast / In the rat race.
The winning rat I want to be / The running rat I want to be. / The tireless rat I want to be / The fearless rat I want to be.
Visibility only a hundred meters / Not long can I see / Not far can I see / With a vision so myopic.
Staring at death, I see / Other rats like me / Staring at death, I see / I want to be free.
Far away, I see / The starting line in front of me / Had I smiled more, had I laughed more
Had I talked more, had I sung more.
How unfair, I don’t get a second chance / How unfair, I cannot start again / Had I lived more
Had I lived more.
We strive to win in the metaphorical rat race of life. Often, this goes to the extent of desperation. We must build the best application, win the best client, achieve the best performance rating, and secure the best hike percentage at any cost. Our ambition fails to see our mortality. There is the endless, self-defeating, or pointless pursuit that defines the rat race in modern culture. The intense focus on competition blinds participants to broader life perspectives. The rat racer cannot see far ahead, suggesting literal shortsightedness and a metaphorical inability to comprehend life’s bigger picture. This is connected to the exhausting, repetitive lifestyle without time for relaxation or enjoyment.
Death awaits all participants in this race. Regardless of their position in the race, all competitors share the same ultimate fate. By the end of the race, we realise with startling clarity that we have returned to where we began running. Somebody staring at death, usually has the regret that they could have smiled, laughed, talked and sung more.
We see the unfairness of life’s one-way journey and the inability to begin again. True victory in life might not come from running ahead of others but from fully experiencing life itself. The greatest irony is that people who dedicate their lives to winning the rat race realise too late that the real winners are those who choose to truly live rather than merely compete.
I won’t let you go without talking about LLMs. While the world competes to launch the best LLM with the maximum number of parameters, the shortest inference latency, and the least hallucination, our focus on a safe and meaningful addition to our capabilities should not be compromised. The violations of ethics, justice, and parity must be taken seriously. One may see generative AI as contributing to the VUCA-ness of the world. I see it helping us make the world less VUCA (volatility, uncertainty, complexity and ambiguity).
Volatility: The volatility is caused by diminishing distances among nations, organisations, groups, and individuals. A significant event occurring in one corner of the planet instantly impacts the decisions and activities in the other corner. Uncertainty: We have always been wary of the future. We don’t know what will kill us or what might bring an end to the human species. Complexity: Complexity is the enemy of explainability. The more we understand our actions, decisions, organisations, and the world through the data they generate, the less complex they appear. Ambiguity: Abstraction breeds ambiguity. If you keep abstracting two different entities higher and higher, they will eventually start becoming ambiguous. This is not different from the data aggregation levels data scientists deal with.
AIML is an excellent weapon in our arsenal to fight volatility, uncertainty, complexity, and ambiguity (VUCA). I would even propose having a VUCA score for every AIML solution we develop. The score must tell us about the percentage by which the solution reduces the world’s VUCA-ism. Some say we live in a VUCA world these days. I agree that geopolitical dynamics, climate disruptions, unstable economies, and global pandemics are problems that need to be solved. Haven’t we been solving problems all this while? Now, if you let me go, I will continue working towards being the best data scientist in the world.
Disclaimer
Views expressed above are the author's own.
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