The premature Afghan withdrawal has become an emblem of global humiliation for the United States, where the role of the superpower in the war has started becoming questionable after the Afghan Taliban’s decisive gains.
The US administrations, one after another, relied on falsified narratives and emotions rather than data in settling the mess in Afghanistan.
A calculated approach of computer modeling and statistical methods could have averted the current mess.
However, despite having all the resources, the negligence toward judicious decisions depicts a sorrowful state of affairs.
These blunders of the successive administrations heaped up one after another and empowered the Taliban instead of weakening them in the prior years.
Time and time again, intelligence agencies tried to paint the true picture of the Taliban’s power, but presidents ignored them while undermining the insurgent group.
As the last nail in the coffin is put under Biden’s tenure, had he relied on data, the current mess could have been avoided.
President Biden: Allergic to Data and Predictive Models
Despite being the technological leader with a score of qualified data scientists, the US failed to use technology to predict Afghanistan’s fall. Researches suggest that computers can be used in predicting violence in warring countries.
Biden could have used the predictive models to foresee the Taliban’s advancement and save the United States from global humiliation.
Predictive models of violence have been proven consequential in the past as well, where data scientists incorporated several factors to conclude where the Taliban are most likely to attack.
Had Biden pursued that line and hired the world’s best political data scientists, all the US had to do was conduct social research.
Predictive Models to Paint a True Picture of Violence in Afghanistan
Predictive models of violence incorporate several factors in model construction, including,
- The support of the locals to the Taliban.
- The history of the Taliban’s support in the region.
- The history of the Taliban’s activities in the region.
- The local’s emotional, economic, and military aid to the Taliban.
- The flashpoint of the locals.
- Causes of rebellion within the locals.
- The sentiment analysis of locals in and against the US and its forces.
- The conflict prevention strategies.
History is often regarded as a tool to predict the future, and this could have been the case in the predictive model construction for the Afghan war as well.
By studying the Afghan Taliban’s last government in detail and finding the deeply buried patterns, a lot of valuable data could have been gathered by the United States.
Most of the regions that were pro-Taliban in their 1996 insurgency should have been scrutinized by the US forces by installing additional forces in those regions to curb the Taliban’s advancement.
Small efforts have been made in this regard by some of the data scientists in the past. For instance, in 2011, a data scientist named Jason Lyall tried to construct one such statistical model to predict future violence and showed substantial results.
The good thing for the Biden administration was that several studies were already being conducted on Afghanistan. There is a score of social research and local surveys that the administration could have used to build the statistical model.
This way, the Biden administration has the choice to maintain a sustainable amount of the US army in the areas where the threat to the Taliban’s advancement was mighty.
Final Thoughts
While the United States spent more than $2 trillion in the war, spending some funds on this sensible approach was never a bad option.
And the good thing was that most of this cost was one time expenses and not recurring ones.
Once all the data was collected, the administration would have needed to make a model for predicting violence.
However, now it is useless to cry over spilled milk. But in this failure lies the lessons for the Biden administration. First, the incumbent government must reconsider its approach toward the use of data in political decisions made.
It is a proven fact that decisions taken based on data are more likely to turn out great compared to arbitrary decisions not backed by data analysis.
Ignoring the data is an old habit of President Biden, which always cost him a high amount of peace, time, and money.
Even in the case of the infrastructure bill, he beat around the bush but failed to focus on the data to hit the bull’s eye at once.
This cost him a lot of time. This time, the Afghan withdrawal has been capitalized on by the Republicans and is causing a popularity dip of Biden on a large scale.
This is a lesson to learn for Biden, who should start seeking the services of proficient data scientists, or he will continue biting the dust.
Eli is a Political Data Scientist with over thirty years of experience in Data Engineering, Analytics, and Digital Marketing. Eli uses his expertise to give the latest information and distinctive analysis on US Political News, US Foreign Affairs, Human Rights, and Racial Justice equipping readers with the inequivalent knowledge.