The use of AI in Government could be traced back to the World War 2, when Alan Touring decipher the Enygma machine to intercept nazi’s communications. Barth’s approach reflection, about the impact of AI on the government identified some dilemmas over this field, such as administrative discretion, responsiveness, judgment, and accountability of the use of these technologies in the government public administration.

 

Artificial intelligence (AI) is the latest trend being implemented in the public sector. Recent advances in this field and the AI explosion in the private sector have served to promote a revolution for government, public service management, accountability, and public value. The public sector and government are set to gain tremendous benefits by the integration of AI into different aspects of their work. Artificial intelligence already helps run government, with cognitive applications doing everything from reducing backlogs and cutting costs to handling tasks we can’t easily do on our own, such as predicting fraudulent transactions and identifying criminal suspects via facial recognition. Indeed, while we expect AI-based technology in the years ahead to fundamentally transform how public-sector employees get work done—eliminating some jobs, redesigning countless others, and even creating entirely new professions1—it’s already changing the nature of many jobs and revolutionizing facets of government operations.

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AI helps governments accomplish more within tight budgets, automate tedious tasks, enhance mission-critical capabilities, and enable research breakthroughs. Below are types of government problems appropriate for AI applications as depicted by the Harvard Ash Center:

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Resource Allocation

• Administrative support is needed to speed up task completion

• Inquiry response times are long due to insufficient support

 

Large Datasets 

• Dataset is too large for employees to work with efficiently 

• Internal and external datasets can be combined to enhance outputs and insights 

• Data is highly structured with years of history

 

Experts Shortage 

• Basic questions can be answered, freeing up time for experts 

• Niche issues can be learned to support experts in research

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Predictable Scenario 

• Situation is predictable based on historical data 

• Prediction will help with time-sensitive responses

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Procedural 

• Task is repetitive in nature 

• Inputs/outputs have binary answer

 

Diverse Data 

• Data includes visual/spatial and auditory/linguistic information 

• Qualitative and quantitative data needs to be summarized regularly

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