Executive Guide to Cognitive Computing Part 4

Five Dimensions that Cognitive Computing will evolve in Public Sector programs

As Cognitive Systems get deployed into Public Sector programs they will continue to evolve over time due to the nature of algorithmic programming and natural language processing of information.  Cognitive systems are dependent upon a feedback loop and as such these dimensions will have an impact on not only the technology but the programs or projects they support.  This evolution is predicated on a few dimensions that affect perception and adoption.

 Cognitive Evolution

Figure 1: Five Dimensions of how Cognitive Computing will evolve over time

 

Cognitive Computing will evolve over 5 dimensions that span both technology and cultural aspects of a public sector program.

Personalized Interactions

Given the ability for cognitive to interact via natural language and learn from those interactions each business problem may require varying levels of interaction and also the level of personalization.  Therefore, a social service benefit self-serve application will need to have a much more intimate understanding of the citizen.  Each person will need to be better understood on more dimensions of interaction: access rights, location, personality, tone, sentiment, log history etc.  All of these dimensions will provide a more satisfying interaction and outcome regardless of the user type.

Learning

As has been explained cognitive systems relying heavily on machine learning.  Machine learning algorithms can be supervised or unsupervised.  It will come down to what level of complexity and knowledge the algorithms has of a specific domain.  Some applications will constantly need the input of a human subject matter expert in order learn whereas other systems will continue to enhance themselves through automated feedback loops.

Recommendation: Develop a culture where analysis and question asking is supporting in that cognitive systems will aid in decision making outcomes.  Also the need to have SME within a domain or program area to participate in helping the cognitive systems learn.  This will impact workforce dynamics and must be positioned correctly so that users do need feel threatened by the new systems being developed.

Sensing

Since Cognitive system analyze larger data sets and require more dimensions of data one path that cognitive systems will evolve around will be the number of data sets used to answer questions or make decisions upon.  One will see the expansion of various sources of information types to ‘sense’ and decide upon.  The Internet of Things, Dirty Data, Big Data, Open Data, Geo-Spatial and Social Media information sources provide greater contextual understanding for cognitive systems to integrate with and additionally enhance their analysis capability.

Recommendations: Policy changes will be challenged to address the evolution of information access in accordance with public sector regulations and compliance.  Planning and strategy will be required in order for this evolution to occur

Ubiquity

Public Sector workers are younger and are technically ‘rich’ in their personal lives.  The expectation of technology use will increase exponentially as the public sector workforce changes.  The need to embed cognitive systems in how people work and where they work regardless of device or location will need to be planned for.

Recommendations: Since cognitive systems focus on information automation vs. process automation and the information can be presented or integrated in any form the ubiquity of the interplay between systems and users can be supported to meet the demand of the new public sector workforce.

Scalability

The ability to interact with government workers or citizens will continue to enhanced with the continuing development of natural language and conversation algorithms which will ensure that the interaction between user and technology becomes easier over time.

Cognitive systems continue to enhance themselves through artificial intelligence and machine learning.  The evolution of feedback loops and deep neural networks will ensure that developed algorithms will be enhanced in a more automatic fashion that the system can truly learn how to interact and better respond with increased levels of confidence and information.

Cognitive systems are really a culmination of existing systems and algorithmic programming as well as the need to incorporate more and larger data sets such as geospatial, weather, social media and internet of things data (IoT).

Recommendations:

Public Sector leaders must plan for the fact that in order to scale systems one must be reliant on technology on premise as well as in the Cloud or with a Platform as a Service (PaaS). 

How do I use Cognitive Computing and for what benefit?

To truly understand what and how cognitive systems will benefit your organization it is best to see how other public sector programs are starting to use cognitive machine learning and natural language processing to enhance programs.

Tax

A large taxation department is using advanced methods of natural language processing to analyze structured information (SWIFT Transactions) and unstructured information such as social media and addresses to investigate and analyze off-shore financial transactions.

Health Agency

A national health agency that is tasked with researching and assessing immunization products for the country they serve are looking at the possibility of what natural language processing and text analytics will allow them to do.  Instead of manually reading thousands of medical journals and research documents by hand; which currently takes 10 months they hope to be able to analyze and extract insight within a shorter period of time thereby getting more effective immunization treatments to the populace in a shorter period of time.

Law Enforcement

Investigations into major crimes and drug gang activity is being enhanced by combining many sources of information together and allowing investigators to ask in natural language who someone is or even where they are.   This information is then fed into visualization tools to better see how individuals and organizations are linked.  Advance analysis tools are being used to image analysis and extraction of meaningful evidence that could only have been done by a human before.  This allows a larger body of evidence to be gathered and because it is automated the change of evidence or forensics can be maintained as it is handed over to prosecution.

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