If one were to go by what is portrayed in works of science fiction and cinema, then artificial intelligence (AI) will appear as a technology to be feared and to be terrified about. After, all advanced artificial intelligence that has gone awry is a potent existential threat to humanity, and a superintelligent agent that eventually refuses to be controlled by its original programmers could become so powerful as to be rendered virtually unstoppable by humans.
While fear of superintelligence has its merits, artificial intelligence in its current state is actually more an agent of good that benefits many of our existing industries—from education, finance, and healthcare to aviation, transportation, and manufacturing.
Today, individual governments and public sector agencies have also begun using artificial intelligence, machine learning, and data analytics to drive value for their citizens and to address many of the existing challenges that they face on a daily basis. It’s safe to assume that governments of the future will increasingly make better use of these technologies to make a difference in their areas of jurisdiction. Here are just some of the spheres of governance in which artificial intelligence and its allied tools and methodologies will see increasing use and deploymentin the near future.
Traffic and Transportation Management
In many areas of the world today, transportation infrastructure are underused and traffic is mismanaged simply because of the lack of access to real-time information among motorists, commuters, and traffic agencies. In the future, more widespread use of artificial intelligence will increase mobility in transportation and efficiency in traffic management.
Some modern cities today, for instance, take advantage of smart traffic signal technologies that let traffic lights change their signals based on real-time traffic information, while some have also equipped public transport assets like buses and trains with GPS technologies that allow the riding public to track the time and availability of these services. Commuters today also make use of third-party mobile applications that use proprietary algorithms to show people the best routes to take, especially during rush hours or when traffic is disrupted by accidents and other causes.
Healthcare and Population Health Management
Today’s healthcare landscape is moving increasingly away from the volume-based paradigm of care to the value-based paradigm of care. This new focus on value and quality of care means health providers, health payers, and relevant government agencies must also become more adept at managing the risks of their patients.However, to be able to change the health trajectories of citizens, both clinicians and regulators must be able to know what the trajectories are in the first place.
This if how artificial intelligence solutions for the healthcare sector can help. A powerful population risk management software can mine through layers and layers of patient data to discover nuanced sub-populations and automatically predict their future risk trajectories. More importantly, such a technology can then advise on the most effective interventions and the best routes of care to take,allowing health providers to generate the most favorable health outcomes for people.
Military and Defense
During the Second World War, mathematician, computer pioneer, and artificial intelligence theorist Alan Turing devised for the British Intelligence a machine that was capable of speeding up the deciphering of intercepted coded German communication. Today, the use of AI in the military has advanced with remarkable progress—a fact that would probably excite pioneers like Turing if they were alive today.
Just this May 2018, U.S. Military leaders have announced that the Pentagon’s keystone artificial intelligence endeavor, Project Maven, has already been deployed in the Middle East and Africa. Project Maven’s particular area of focus is computer vision, an area of machine learning and deep learning which, according to defense officials, can autonomously extract objects of interest from moving or still imagery that have been gathered by reconnaissance and surveillance assets. This process employs biologically inspired neural networks.
Public Safety through Law Enforcement and Disaster Management
The same real-time information used for traffic and transportation management can be used by relevant government agencies to promote public safety. For instance, smart traffic signal technologies can be used to help clear traffic for fire department, emergency service, and law enforcement vehicles that urgently need to attend to callouts.
The growing volume of data generated by cities can also be mined using sensors and smart imaging services to discover people with criminal records as well as to identify possible accidents and possible criminal activities (e.g. by recognizing the sound of gunfire). Moreover, smart cities can also deploy localized disaster warnings on a granular level, allowing individuals and families to proactively prepare for oncoming natural disasters like tsunamis, flashfloods, hurricanes, storm surges, forest fires, and others.
Governments and public sector agencies stand to gain so much by making good use of artificial intelligence. In the near future, increasing use of AI solutions along with machine learning and deep learning technologies will allow people within the governance and public service continuum to deliver vital services to citizens more efficiently.