102 Cognitive Computing Criteria for Multi-purpose Projects

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 102 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:

Start Cognitive Computing risks and grade techniques for implementing Cognitive Computing controls.

– What are the key elements of your Cognitive Computing performance improvement system, including your evaluation, organizational learning, and innovation processes?

– Does our organization need more Cognitive Computing education?

– What about Cognitive Computing Analysis of results?

Adaptive system Critical Criteria:

Facilitate Adaptive system issues and explore and align the progress in Adaptive system.

– How will you know that the Cognitive Computing project has been successful?

– Does Cognitive Computing appropriately measure and monitor risk?

– Is There a Role for Complex Adaptive Systems Theory?

– What are our Cognitive Computing Processes?

Adaptive user interface Critical Criteria:

Grade Adaptive user interface issues and inform on and uncover unspoken needs and breakthrough Adaptive user interface results.

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

– What are current Cognitive Computing Paradigms?

Affective computing Critical Criteria:

Talk about Affective computing risks and perfect Affective computing conflict management.

– What are the business goals Cognitive Computing is aiming to achieve?

Artificial intelligence Critical Criteria:

Contribute to Artificial intelligence results and look at it backwards.

– Does Cognitive Computing create potential expectations in other areas that need to be recognized and considered?

– What are your most important goals for the strategic Cognitive Computing objectives?

– Are there Cognitive Computing problems defined?

Artificial neural network Critical Criteria:

Design Artificial neural network engagements and figure out ways to motivate other Artificial neural network users.

– What other organizational variables, such as reward systems or communication systems, affect the performance of this Cognitive Computing process?

– How is the value delivered by Cognitive Computing being measured?

Automated reasoning Critical Criteria:

Conceptualize Automated reasoning issues and triple focus on important concepts of Automated reasoning relationship management.

– 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?

– 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?

– What potential environmental factors impact the Cognitive Computing effort?

Cognitive computer Critical Criteria:

Learn from Cognitive computer outcomes and simulate teachings and consultations on quality process improvement of Cognitive computer.

– what is the best design framework for Cognitive Computing organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?

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

Cognitive reasoning Critical Criteria:

Distinguish Cognitive reasoning strategies and devote time assessing Cognitive reasoning and its risk.

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

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

– Are accountability and ownership for Cognitive Computing clearly defined?

Computer vision Critical Criteria:

Powwow over Computer vision tasks and look at the big picture.

– What are your current levels and trends in key measures or indicators of Cognitive Computing product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?

– How do your measurements capture actionable Cognitive Computing information for use in exceeding your customers expectations and securing your customers engagement?

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

Computing platform Critical Criteria:

Focus on Computing platform governance and learn.

– Do several people in different organizational units assist with the Cognitive Computing process?

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

– What tools and technologies are needed for a custom Cognitive Computing project?

Context awareness Critical Criteria:

Demonstrate Context awareness planning and get answers.

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

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

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

Data analysis Critical Criteria:

Consider Data analysis risks and get answers.

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

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

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

– What are some real time data analysis frameworks?

Dialog system Critical Criteria:

Differentiate Dialog system issues and prioritize challenges of Dialog system.

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

– Meeting the challenge: are missed Cognitive Computing opportunities costing us money?

– What are all of our Cognitive Computing domains and what do they do?

Enterprise cognitive system Critical Criteria:

Chat re Enterprise cognitive system decisions and finalize specific methods for Enterprise cognitive system acceptance.

– What are the success criteria that will indicate that Cognitive Computing objectives have been met and the benefits delivered?

Face detection Critical Criteria:

Deliberate Face detection outcomes and probe the present value of growth of Face detection.

– Who is the main stakeholder, with ultimate responsibility for driving Cognitive Computing forward?

– How to deal with Cognitive Computing Changes?

Fraud detection Critical Criteria:

Focus on Fraud detection outcomes and arbitrate Fraud detection techniques that enhance teamwork and productivity.

– Who are the people involved in developing and implementing Cognitive Computing?

– Is Cognitive Computing Required?

Human brain Critical Criteria:

Chart Human brain issues and don’t overlook the obvious.

– What role does communication play in the success or failure of a Cognitive Computing project?

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

– Which Cognitive Computing goals are the most important?

Human–computer interaction Critical Criteria:

Reorganize Human–computer interaction leadership and oversee Human–computer interaction management by competencies.

– What knowledge, skills and characteristics mark a good Cognitive Computing project manager?

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

– How will you measure your Cognitive Computing effectiveness?

Machine learning Critical Criteria:

Shape Machine learning decisions and probe Machine learning strategic alliances.

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

– What sources do you use to gather information for a Cognitive Computing study?

– Is the scope of Cognitive Computing defined?

Risk assessment Critical Criteria:

Devise Risk assessment leadership and get the big picture.

– 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)?

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

– Does the risk assessment approach helps to develop the criteria for accepting risks and identify the acceptable level risk?

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

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

– Are standards for risk assessment methodology established, so risk information can be compared across entities?

– How frequently, if at all, do we conduct a business impact analysis (bia) and risk assessment (ra)?

– Who performs your companys information and technology risk assessments?

– How often are information and technology risk assessments performed?

– 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?

– Who performs your companys IT risk assessments?

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

– How do we go about Securing Cognitive Computing?

– What triggers a risk assessment?

– How can we improve Cognitive Computing?

Sentiment analysis Critical Criteria:

Reorganize Sentiment analysis tactics and test out new things.

– Is maximizing Cognitive Computing protection the same as minimizing Cognitive Computing loss?

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

– What are the barriers to increased Cognitive Computing production?

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

Signal processing Critical Criteria:

Study Signal processing projects and triple focus on important concepts of Signal processing relationship management.

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

Social neuroscience Critical Criteria:

Design Social neuroscience outcomes and find answers.

– Will Cognitive Computing have an impact on current business continuity, disaster recovery processes and/or infrastructure?

Speech recognition Critical Criteria:

Learn from Speech recognition governance and give examples utilizing a core of simple Speech recognition skills.

– What will drive Cognitive Computing change?

Synthetic intelligence Critical Criteria:

Win new insights about Synthetic intelligence leadership and overcome Synthetic intelligence skills and management ineffectiveness.

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

Unstructured data Critical Criteria:

Wrangle Unstructured data risks and gather practices for scaling Unstructured data.

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

– 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)?

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

Unstructured information Critical Criteria:

Scan Unstructured information leadership and report on the economics of relationships managing Unstructured information and constraints.

– 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 are the usability implications of Cognitive Computing actions?


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 | http://theartofservice.com



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:

What is cognitive computing? – Definition from …

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

Adaptive system External links:

Pat Ebright – Complex Adaptive System Theory – YouTube

TF Adaptive System Dentist – YouTube

Adaptive user interface External links:

An Adaptive User Interface in Healthcare – ScienceDirect

What is Adaptive User Interface | FlowPaper

Affective computing External links:

Overview ‹ Affective Computing — MIT Media Lab

Affective Computing – Gartner IT Glossary

Affective Computing Flashcards | Quizlet

Artificial intelligence External links:

Robotics & Artificial Intelligence ETF – Global X Funds

Artificial neural network External links:

Training an Artificial Neural Network – Intro | solver

What is bias in artificial neural network? – Quora

Best Artificial Neural Network Software in 2018 | G2 Crowd

Automated reasoning External links:

Handbook of Automated Reasoning – ScienceDirect

UCLA Automated Reasoning Group – YouTube

ARCOE – Workshop on Automated Reasoning about …

Cognitive computer External links:

Cognitive Computer Solutions – Home | Facebook

Restb.ai – Cognitive Computer Vision | Crunchbase

Cognitive reasoning External links:

Brubaker Cognitive Reasoning Package – alimed.com

What Is Cognitive Reasoning? – YouTube

Cognitive Reasoning – Parrot Software

Computer vision External links:

Computer vision – Microsoft Research

Computer Vision Syndrome: Causes, Symptoms and …

Computer Vision Syndrome – VSP Vision Care

Computing platform External links:

Nutanix Xtreme Computing Platform NX-1365-G5 – cdw.com
http://www.cdw.com › … › Storage Networking/SAN Software

Microsoft Azure Cloud Computing Platform & Services

In-Memory Computing Platform | GigaSpaces

Context awareness External links:

Semusi – Context Awareness Made Easy

Data analysis External links:

Equity in Athletics Data Analysis – US Department of …

Data Analysis – Illinois State Board of Education

Dialog system External links:

Dialog system – Object Technology Licensing Corporation

Enterprise cognitive system External links:

Enterprise cognitive system – WOW.com

Face detection External links:

CV Dazzle: Camouflage from Face Detection

Fraud detection External links:

Fraud Detection and Authentication Technology – Next Caller

Fraud Detection and Anti-Money Laundering Software – Verafin

Fraud Detection and Fraud Prevention Services | TransUnion

Human brain External links:

OHBM 2018 – Organization for Human Brain Mapping

Human Brain: Major Structures and their Functions – YouTube

Brain Anatomy, Anatomy of the Human Brain

Machine learning External links:

Machine Learning: What it is and why it matters | SAS

Amazon EC2 P3 – Ideal for Machine Learning and HPC – AWS

Endpoint Protection – Machine Learning Security | …

Risk assessment External links:

Ground Risk Assessment Tool – United States Army …

Ohio Risk Assessment System (ORAS) – ODRC


Sentiment analysis External links:

Sentiment Analysis | Lexalytics

Sentiment Analysis – Brandwatch

Sentiment Analysis on Movie Reviews | Kaggle

Signal processing External links:

Deep Learning | Signal Processing | DeepSig Inc.

Social neuroscience External links:

Summer School in Social Neuroscience & Neuroeconomics

Social Neuroscience – Michigan State University

[PDF]The Social Neuroscience of Empathy – Greater Good

Speech recognition External links:

Speech API – Speech Recognition | Google Cloud Platform

Dictate text using Speech Recognition – Windows Help

Amazon Transcribe – Automatic Speech Recognition – AWS

Synthetic intelligence External links:

SIML – The Synthetic Intelligence Markup Language

Synthetic Intelligence Network – Home | Facebook


Unstructured data External links:

Scale-Out NAS for Unstructured Data | Dell EMC US

Structured vs. Unstructured data – BrightPlanet

Differences Between Structured & Unstructured Data – …

Unstructured information External links:

Manage Unstructured Information as Part of EIM |ASUG

Unstructured Information Management Architecture SDK – IBM

An unstructured information management system (UIMS…

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