Top 97 Cognitive Computing Things You Should Know

What is involved in Cognitive Computing

Find out what the related areas are that Cognitive Computing connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Cognitive Computing thinking-frame.

How far is your company on its Cognitive Computing journey?

Take this short survey to gauge your organization’s progress toward Cognitive Computing leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.

To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.

Start the Checklist

Below you will find a quick checklist designed to help you think about which Cognitive Computing related domains to cover and 97 essential critical questions to check off in that domain.

The following domains are covered:

Cognitive Computing, Adaptive system, Adaptive user interface, Affective computing, Artificial intelligence, Artificial neural network, Automated reasoning, Cognitive computer, Cognitive reasoning, Computer vision, Computing platform, Context awareness, Data analysis, Dialog system, Enterprise cognitive system, Face detection, Fraud detection, Human brain, Human–computer interaction, Machine learning, Risk assessment, Sentiment analysis, Signal processing, Social neuroscience, Speech recognition, Synthetic intelligence, Unstructured data, Unstructured information:

Cognitive Computing Critical Criteria:

Ventilate your thoughts about Cognitive Computing quality and report on developing an effective Cognitive Computing strategy.

– What are our best practices for minimizing Cognitive Computing project risk, while demonstrating incremental value and quick wins throughout the Cognitive Computing project lifecycle?

– Who will be responsible for making the decisions to include or exclude requested changes once Cognitive Computing is underway?

– Do we all define Cognitive Computing in the same way?

Adaptive system Critical Criteria:

X-ray Adaptive system outcomes and mentor Adaptive system customer orientation.

– Which customers cant participate in our Cognitive Computing domain because they lack skills, wealth, or convenient access to existing solutions?

– Have the types of risks that may impact Cognitive Computing been identified and analyzed?

– Is there any existing Cognitive Computing governance structure?

– Is There a Role for Complex Adaptive Systems Theory?

Adaptive user interface Critical Criteria:

Experiment with Adaptive user interface tactics and report on developing an effective Adaptive user interface strategy.

– Does Cognitive Computing include applications and information with regulatory compliance significance (or other contractual conditions that must be formally complied with) in a new or unique manner for which no approved security requirements, templates or design models exist?

– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Cognitive Computing in a volatile global economy?

– Will new equipment/products be required to facilitate Cognitive Computing delivery for example is new software needed?

Affective computing Critical Criteria:

Focus on Affective computing issues and check on ways to get started with Affective computing.

– In the case of a Cognitive Computing project, the criteria for the audit derive from implementation objectives. an audit of a Cognitive Computing project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Cognitive Computing project is implemented as planned, and is it working?

– To what extent does management recognize Cognitive Computing as a tool to increase the results?

– How do we maintain Cognitive Computings Integrity?

Artificial intelligence Critical Criteria:

Infer Artificial intelligence tasks and devote time assessing Artificial intelligence and its risk.

– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Cognitive Computing?

– How do we measure improved Cognitive Computing service perception, and satisfaction?

Artificial neural network Critical Criteria:

Steer Artificial neural network planning and attract Artificial neural network skills.

– What tools do you use once you have decided on a Cognitive Computing strategy and more importantly how do you choose?

– In what ways are Cognitive Computing vendors and us interacting to ensure safe and effective use?

Automated reasoning Critical Criteria:

Devise Automated reasoning strategies and pay attention to the small things.

– Think about the kind of project structure that would be appropriate for your Cognitive Computing project. should it be formal and complex, or can it be less formal and relatively simple?

– What prevents me from making the changes I know will make me a more effective Cognitive Computing leader?

Cognitive computer Critical Criteria:

Conceptualize Cognitive computer engagements and drive action.

– Among the Cognitive Computing product and service cost to be estimated, which is considered hardest to estimate?

– When a Cognitive Computing manager recognizes a problem, what options are available?

– Have you identified your Cognitive Computing key performance indicators?

Cognitive reasoning Critical Criteria:

Check Cognitive reasoning governance and research ways can we become the Cognitive reasoning company that would put us out of business.

– What are our needs in relation to Cognitive Computing skills, labor, equipment, and markets?

Computer vision Critical Criteria:

Frame Computer vision tactics and look in other fields.

– What are specific Cognitive Computing Rules to follow?

– How can the value of Cognitive Computing be defined?

Computing platform Critical Criteria:

Discourse Computing platform visions and simulate teachings and consultations on quality process improvement of Computing platform.

– Does Cognitive Computing analysis show the relationships among important Cognitive Computing factors?

– Does Cognitive Computing systematically track and analyze outcomes for accountability and quality improvement?

– How likely is the current Cognitive Computing plan to come in on schedule or on budget?

Context awareness Critical Criteria:

Have a session on Context awareness tactics and devise Context awareness key steps.

– Information/context awareness: how can a developer/participant restore awareness in project activity after having been offline for a few hours, days, or weeks?

– What is our formula for success in Cognitive Computing ?

– Are there recognized Cognitive Computing problems?

– How to deal with Cognitive Computing Changes?

Data analysis Critical Criteria:

Huddle over Data analysis goals and pioneer acquisition of Data analysis systems.

– What are the top 3 things at the forefront of our Cognitive Computing agendas for the next 3 years?

– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?

– Do the Cognitive Computing decisions we make today help people and the planet tomorrow?

– What are some real time data analysis frameworks?

Dialog system Critical Criteria:

Examine Dialog system issues and track iterative Dialog system results.

– Think about the functions involved in your Cognitive Computing project. what processes flow from these functions?

– Do you monitor the effectiveness of your Cognitive Computing activities?

– How do we go about Comparing Cognitive Computing approaches/solutions?

Enterprise cognitive system Critical Criteria:

Study Enterprise cognitive system risks and revise understanding of Enterprise cognitive system architectures.

– Who will be responsible for deciding whether Cognitive Computing goes ahead or not after the initial investigations?

– How important is Cognitive Computing to the user organizations mission?

Face detection Critical Criteria:

Define Face detection decisions and explain and analyze the challenges of Face detection.

Fraud detection Critical Criteria:

Review Fraud detection goals and remodel and develop an effective Fraud detection strategy.

– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Cognitive Computing models, tools and techniques are necessary?

– How do we keep improving Cognitive Computing?

Human brain Critical Criteria:

Analyze Human brain tasks and pay attention to the small things.

– What are internal and external Cognitive Computing relations?

– How can you measure Cognitive Computing in a systematic way?

– Are there Cognitive Computing Models?

Human–computer interaction Critical Criteria:

Look at Human–computer interaction outcomes and finalize the present value of growth of Human–computer interaction.

– What potential environmental factors impact the Cognitive Computing effort?

– Can we do Cognitive Computing without complex (expensive) analysis?

Machine learning Critical Criteria:

Steer Machine learning risks and test out new things.

– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?

– How do we ensure that implementations of Cognitive Computing products are done in a way that ensures safety?

– Which Cognitive Computing goals are the most important?

– What are current Cognitive Computing Paradigms?

Risk assessment Critical Criteria:

Give examples of Risk assessment strategies and handle a jump-start course to Risk assessment.

– Have the it security cost for the any investment/project been integrated in to the overall cost including (c&a/re-accreditation, system security plan, risk assessment, privacy impact assessment, configuration/patch management, security control testing and evaluation, and contingency planning/testing)?

– Do we have a a cyber Risk Management tool for all levels of an organization in assessing risk and show how Cybersecurity factors into risk assessments?

– Are interdependent service providers (for example, fuel suppliers, telecommunications providers, meter data processors) included in risk assessments?

– With Risk Assessments do we measure if Is there an impact to technical performance and to what level?

– Does the process include a BIA, risk assessments, Risk Management, and risk monitoring and testing?

– Is the priority of the preventive action determined based on the results of the risk assessment?

– How does your company report on its information and technology risk assessment?

– Who performs your companys information and technology risk assessments?

– How often are information and technology risk assessments performed?

– How are risk assessment and audit results communicated to executives?

– Are regular risk assessments executed across all entities?

– Do you use any homegrown IT system for ERM or risk assessments?

– Are regular risk assessments executed across all entities?

– What drives the timing of your risk assessments?

– Do you use any homegrown IT system for risk assessments?

– Is a Cognitive Computing Team Work effort in place?

– Are risk assessments at planned intervals reviewed?

– Why are Cognitive Computing skills important?

Sentiment analysis Critical Criteria:

Familiarize yourself with Sentiment analysis quality and balance specific methods for improving Sentiment analysis results.

– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Cognitive Computing processes?

– How representative is twitter sentiment analysis relative to our customer base?

– What are the barriers to increased Cognitive Computing production?

– What is Effective Cognitive Computing?

Signal processing Critical Criteria:

Match Signal processing projects and use obstacles to break out of ruts.

Social neuroscience Critical Criteria:

Rank Social neuroscience failures and pay attention to the small things.

– What management system can we use to leverage the Cognitive Computing experience, ideas, and concerns of the people closest to the work to be done?

– What new services of functionality will be implemented next with Cognitive Computing ?

– Which individuals, teams or departments will be involved in Cognitive Computing?

Speech recognition Critical Criteria:

Familiarize yourself with Speech recognition governance and work towards be a leading Speech recognition expert.

– Does the Cognitive Computing task fit the clients priorities?

– How can we improve Cognitive Computing?

Synthetic intelligence Critical Criteria:

Detail Synthetic intelligence management and perfect Synthetic intelligence conflict management.

– Is Cognitive Computing dependent on the successful delivery of a current project?

– What are the Key enablers to make this Cognitive Computing move?

Unstructured data Critical Criteria:

Recall Unstructured data tasks and change contexts.

– What is the total cost related to deploying Cognitive Computing, including any consulting or professional services?

– What tools do you consider particularly important to handle unstructured data expressed in (a) natural language(s)?

– Does your organization have the right tools to handle unstructured data expressed in (a) natural language(s)?

Unstructured information Critical Criteria:

Conceptualize Unstructured information risks and check on ways to get started with Unstructured information.

– Is the solution going to generate structured, semistructured, unstructured information for its own use or for use by entities either internal or external to the enterprise?

– What threat is Cognitive Computing addressing?


This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Cognitive Computing Self Assessment:

Author: Gerard Blokdijk

CEO at The Art of Service |

Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.

External links:

To address the criteria in this checklist, these selected resources are provided for sources of further research and information:

Cognitive Computing External links:

Cognitive Computing Consortium

“Cognitive Computing” by Haluk Demirkan, Seth Earley et al.

What is cognitive computing? – Definition from …

Adaptive system External links:

TF Adaptive System Dentist – YouTube

Adaptive user interface External links:

What is Adaptive User Interface | IGI Global



Affective computing External links:

Overview ‹ Affective Computing — MIT Media Lab

Affective Computing Flashcards | Quizlet

Affective Computing – Gartner IT Glossary

Artificial neural network External links:

Training an Artificial Neural Network – Intro | solver

The Best Artificial Neural Network Solution of 2017 Raise Forecast Accuracy with Powerful Neural Network Software. The concept of …

Best Artificial Neural Network Software in 2018 | G2 Crowd

Automated reasoning External links:

ARG: How AWS Service Teams use Automated Reasoning …

ARChem: Automated Reasoning in Chemistry

Cognitive computer External links:

IBM’s Watson cognitive computer has whipped up a cookbook

Cognitive Computer Solutions – Home | Facebook

Cognitive reasoning External links:

Cognitive Reasoning Platform | Cognitive Computing and …

Cognitive Reasoning –

Cognitive Reasoning – Parrot Software

Computer vision External links:

Computer Glasses and Computer Vision Syndrome – …

Computer vision – Microsoft Research

Computer Vision Symptoms and Treatment – Verywell

Computing platform External links:

DeepBrainChain: Decentralized AI Computing Platform

Microsoft Azure Cloud Computing Platform & Services

Edge Computing Platform – YouTube

Context awareness External links:


Semusi – Context Awareness Made Easy

Context Awareness and Applications – MIT Media Lab

Data analysis External links:

Regional Data Warehouse/Data Analysis Site

Data Analysis in Excel – Easy Excel Tutorial

Seven Bridges Genomics – The biomedical data analysis …

Dialog system External links:

Dialog System – Scirra Forums

Dialog system – Object Technology Licensing Corporation

Ply — Amazing layer/modal/dialog system. Wow!

Enterprise cognitive system External links:

Enterprise cognitive system – Revolvy cognitive system

Face detection External links:

Face Detection & Recognition Homepage – Official Site

Face Detection using OpenCV and Python: A Beginner’s …

CV Dazzle: Camouflage from Face Detection

Fraud detection External links:

Title IV fraud detection | University Business Magazine

Human brain External links:

The Human Brain Atlas at Michigan State University

5 Stages of Human Brain Development | Nancy Guberti, …

Brain – Human Brain Diagrams and Detailed Information

Machine learning External links:

Endpoint Protection – Machine Learning Security | …

What is machine learning? – Definition from

Microsoft Azure Machine Learning Studio

Risk assessment External links:

Ground Risk Assessment Tool – United States Army …

Risk Assessment |


Sentiment analysis External links:

Real-time Feedback and Sentiment Analysis | Yanay

YUKKA Lab – Sentiment Analysis

Social neuroscience External links:

Summer School in Social Neuroscience & Neuroeconomics

UCLA Social Neuroscience Lab

Social Neuroscience – Michigan State University

Speech recognition External links:

Windows Speech Recognition commands – Windows Help

TalkTyper – Speech Recognition in a Browser

SayIt from nVoq – Speech Recognition in the Cloud

Synthetic intelligence External links:

SIML – The Synthetic Intelligence Markup Language

Rights for Synthetic Intelligence – Home | Facebook

Synthetic Intelligence Network – Home | Facebook

Unstructured data External links:

What is unstructured data? – Definition from

Unstructured information External links:

IBM developerWorks : Unstructured Information …

Securing Unstructured Information Discovered by …

Manage Unstructured Information as Part of EIM |ASUG