A new special report from insideHPC, courtesy of Dell EMC and NIVIDA, focuses on how artificial intelligence (AI) is being used within government and unique verticals. What’s next for government AI? This excerpt explores the specific application of artificial intelligence within government entities.
Download the full report.
Before we look at the application of AI within government, it’s important to note that, across the globe, governments are acknowledging the potential of AI technologies to impact our daily lives, from how we make purchasing decisions to improving our healthcare. In Europe, 25 Member States signed an EU Declaration on Cooperation on Artificial Intelligence on April 10, 2018, setting out various commitments: to boost Europe’s technology and industrial capacity in AI along with its uptake; address socio-economic challenges such as the transformation of the labor markets and modernizing Europe’s education and training systems; and ensure an adequate legal and ethical framework.
The National Artificial Intelligence R&D Strategic Plan sets out objectives and priorities for Federally-funded AI research.
In the U.S., a new National Science and Technology Council (NSTC) subcommittee on Machine Learning and Artificial intelligence was formed in 2016, directing the creation of a National Artificial Intelligence R&D Strategic Plan. This plan sets out objectives for Federally-funded AI research, and identifies the following priorities:
- Make long-term investments in AI research
- Develop effective methods for human-AI collaboration
- Understand and address the ethical, legal and societal implications of AI
- Ensure the safety and security of AI systems
- Develop shared public datasets and environments for AI training and testing
- Measure and evaluate AI technologies through standards and benchmarks
- Better understand the national AI R&D workforce needs
Applications and opportunities
From the detection of fraud, through to the processing of citizen enquiries and the maintenance of government assets, the opportunities for the application of machine learning in government are plentiful. An article in the Harvard Business Review highlights that a “machine learning program may be better, cheaper, faster or more accurate than humans at tasks that involve lots of data, complicated calculations or repetitive tasks with clear rules … we expect that much of the ‘low hanging fruit’ of government use of machine learning will be as a first line of analysis or decision-making. Human judgment will then be critical to interpret results, manage harder cases, or hear appeals.’
When members of the Forbes Technology Council were asked for specific ideas on how the U.S. government could leverage AI technology, all answers led to improving efficiencies. Examples include the easing of caseloads—an algorithm could be trained to accept applications that would, with certainty, be accepted by a human. Financial analyses for the purpose of taxation, mitigating the risk of cybersecurity fraud, optimization of recruitment processes via candidate sourcing and filtering, and modernization of government HR systems are all further areas where AI assistance can have measurable benefits.
Advanced technologies require expertise to select, deploy and maintain them. This is challenging given the shortage of data scientists in the general workforce.
Example
New Statesman gives an example of how AI can act as a supplement to human decision-making rather than a replacement for it: “As government agencies around the world start to adopt AI, a number of repeatable use cases have started to emerge. The overwhelming majority of the world’s data—an estimated 80 percent—is held in formats not easily used prior to the emergence of AI. This data may be held as unstructured documents, both electronic and hard copy, as video or audio. AI can analyze these files, recognizing the content of images, videos and text, and then help people to understand them and use them to make informed decisions.”
The National Artificial Intelligence R&D Strategic Plan sets out objectives and priorities for Federally-funded AI research. (Photo: Shutterstock/ Yurchanka Siarhei)
Challenges
There are several reasons why government agencies may be hesitant to adopt AI technologies. The cost of change can often be the most challenging. Adopting new technologies new platforms, methods, and mindsets—and with that comes cost. There’s monetary cost, of course, but also the cost in terms of the time and resources needed to integrate that technology into existing processes.
Moreover, these advanced technologies require expertise to select, deploy and maintain them— again, this is challenging given the shortage of data scientists in the general workforce. Within the private sector, the often heavily regulated industries already leveraging AI must also deal with concerns revolving around the digitalization, sharing and security of personal data. And ensuring compliance requires domain knowledge and expertise. The public sector must contend with these concerns in addition to ensuring both the technology—and indeed the government itself—has the public’s trust.
This insideHPC AI special report series will cover the following topics in the coming weeks:
- Finding an AI solution
- The results of AI & Machine Learning
- What’s Next, and New AI Resources
For more on “Augmented Intelligence in Government,” courtesy of Dell EMC and NVIDIA, see the full special report, downloadable free of charge, to find out what’s next for government Ai.
