Why Government Managers Require Machine Learning?
2 months ago

Governments typically collect data about the populace, analyze it for relevant information and use the outcome to take well informed decisions. With the use of machine learning and big data, the lag time between these three steps of governance can be reduced greatly and thus the benefits can reach people much faster. The government decision making can become more pin pointed, effective and efficient. It is important to understand the scope of machine learning in e-governance to establish how useful machine learning projects, big data training & analytics would be for the government managers.

 

Machine learning algorithms are quite adaptive in nature. The more data you feed, the more they learn. Their predictive modules become more precise and the results become more accurate. This works really well in case of e-governance as they have huge amount of data being fed from various public domains. Hence, big data and machine learning becomes extremely important for government managers to plan for futuristic policies for the people. With machine learning, government managers can unleash unimaginable potential of advanced data analytics.

 

Taking example of the Police Departments in certain states of the USA, several high-profile incidents related to police violence have battered the nation’s trust in law enforcement. However, imagine if supervisors were able to identify officers disposed to overtly aggressive conduct. And this were to happen even before a fierce incident ever occurs. This is made possible through machine learning algorithms and big data analytics. The data thus collected and analysed is then used for recruitment, training of new recruits and overall management purposes. In combined with information from police reports, the system can ensign potentially aggressive officers and inform their supervisors. Such a program aims at automating the initial step of better oversight by permitting more preemptive intervention by candidates in managerial roles.

 

Policing is not the only area of government which can profit from machine learning.  Advanced machine learning has been tagged as one of the best strategic IT investments which an organization can look forward to. Also, researchers at MIT are presently investigating various machine learning techniques which may reduce recidivism by offering parole officers a healthier statistical profile of recurrent offenders. Furthermore, IBM researchers are utilizing machine learning algorithms which further leads to a system that can predict pollution levels in Beijing 72 hours in advance, thus helping government managers to take appropriate proactive measures.

 

However, machine learning also holds some risks. For example, if the information is extensive with errors or biases, then machine learning dangers amplifies those errors into mistaken future action. But if it’s executed by intelligent data scientists who appreciate the social issues at post, and used by smooth managers who understand the mechanics work, the worth that these programs may expose is fantastic. 

 

 

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