Challenges and Opportunities for Cognitive Computing in Public Sector

Challenges to Cognitive Computing in Public Sector

The challenge in today’s world of improving or innovating government programs is that we have a broad array of information and process automation to co-ordinate.   Another major challenge of being in a data driven world is that information can be wrong, false, incorrect, out of date or inaccessible.  Cognitive Computing with its ability to apply algorithmic programming allows advanced patterns to be identified out of a much larger group data sets; which allows us to reduce the “noise” associated with making decisions and program outcomes.

There is also a need for evidence based decision making; which needs to follow a prescribed methodology.  As well as the need to analyze larger bodies of knowledge and information.  Traditional rules and equation based programming cannot manage or interact with a human in natural language.  Cognitive Computing interacts with a government worker with natural language and with the ability to learn and enhance the algorithms needed to find and test hypothesis or questions.

Government must ensure information is secured and managed effective.  One of the challenges of moving to cloud based computing or sharing data sets of information across government raises the issue of how far can the data or the information move from where is was created.  Information provenance and governance practices must be in place but the need for private cloud or platform as a service cognitive computing service catalogs are needed to ensure the data is kept within the boundaries of how it is to be governed and managed.  Data residency is another issue associated with using cloud services or cloud computing; however most major providers of cloud services have data centres within the country thereby offsetting issues associated with Data Residency.

Recommendations:

Most governments around the world today have a shared services model for core ICT and Enterprise applications support.  We are seeing that government are now looking at cloud brokerage services being managed within the government which deals with Data Gravity issues.  And based on the nature of the API Economy we see that PaaS (Platform as a Service) are now being investigated and tested.   Therefore, we see central shared services agencies being the agent of change and will look to them to deploy Cognitive Computing PaaS as a service catalog that other government agencies and projects can leverage which will then ensure information is secure and protected depending on the type of information.

Opportunity to Innovate in Government Programs

Due to ability of cognitive computing to identify patterns or information at high speed and with large sets of information the opportunities in government are broad.  Since all information sources are able to be analyzed and combined (Databases and text etc.) a more complete picture is provided to an individual to make decisions.

Any area within a government program that houses a large set of information relevant to a specific domain: benefits, policy, regulations etc. Would benefit from cognitive computing since this information can be analyzed as well as added to a corpus of knowledge that the machine learning algorithms can access and analyze across dimensions such as time or relevance etc.

Six forces that will impact the future evolution of cognitive computing in Public Sector. 

Each facet has its own issues and challenges for this technology to be adopted.

Society

  • Tremendous demand for more intelligent machines and access through mobile devices can facilitate familiarity and comfort with technology
  • Fears of privacy breaches and machines taking human jobs could be a deterrent

Perception

  • Perceptions and expectations must be well managed
  • Unrealistic perceptions of risk and expectations could lead to a third “Artificial Intelligence AI Winter”

Policy

  • Wider adoption will require the modifying policies (e.g., data sharing) and creating new policies (e.g., decision traceability)
  • Fear, uncertainty and doubt may be addressed by new policies (e.g., data security & privacy)

Technology

  • Advanced, intelligent devices will enable a greater understanding of entity context and contribute to the robustness of available information corpora
  • Greater scalability needs drive new architectures and paradigms

Information

  • Variety and scalability capabilities of future systems will advance rapidly to cope with information exhaust
  • Information explosion could advance evolution and adoption rates

Skills

  • Cognitive computing demands unique skills such as natural language processing, machine learning
  • Greater availability of key skills will be key in the evolution and adoption of the capability

Recommendations: One must co-ordinate a strategy that revolves around the areas discussed above.  The fundamental challenges similar to cloud based computing in pubic sector will be policy and cultural change that needs to be managed in order for the information and technology to develop.

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