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 109 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:
Weigh in on Cognitive Computing tactics and proactively manage Cognitive Computing risks.
– What are your results for key measures or indicators of the accomplishment of your Cognitive Computing strategy and action plans, including building and strengthening core competencies?
– What are the record-keeping requirements of Cognitive Computing activities?
– Are there Cognitive Computing Models?
Adaptive system Critical Criteria:
Infer Adaptive system projects and adjust implementation of Adaptive system.
– Does Cognitive Computing create potential expectations in other areas that need to be recognized and considered?
– Think of your Cognitive Computing project. what are the main functions?
– What are the short and long-term Cognitive Computing goals?
– Is There a Role for Complex Adaptive Systems Theory?
Adaptive user interface Critical Criteria:
Survey Adaptive user interface adoptions and customize techniques for implementing Adaptive user interface controls.
– 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?
– What are our best practices for minimizing Cognitive Computing project risk, while demonstrating incremental value and quick wins throughout the Cognitive Computing project lifecycle?
Affective computing Critical Criteria:
Reorganize Affective computing strategies and acquire concise Affective computing education.
– Who will be responsible for making the decisions to include or exclude requested changes once Cognitive Computing is underway?
– How do we maintain Cognitive Computings Integrity?
Artificial intelligence Critical Criteria:
Survey Artificial intelligence projects and diversify disclosure of information – dealing with confidential Artificial intelligence information.
– For your Cognitive Computing project, identify and describe the business environment. is there more than one layer to the business environment?
– What tools do you use once you have decided on a Cognitive Computing strategy and more importantly how do you choose?
– What are your most important goals for the strategic Cognitive Computing objectives?
Artificial neural network Critical Criteria:
Guard Artificial neural network engagements and correct Artificial neural network management by competencies.
– Where do ideas that reach policy makers and planners as proposals for Cognitive Computing strengthening and reform actually originate?
– How do we ensure that implementations of Cognitive Computing products are done in a way that ensures safety?
– How to deal with Cognitive Computing Changes?
Automated reasoning Critical Criteria:
Generalize Automated reasoning visions and budget the knowledge transfer for any interested in Automated reasoning.
– Which customers cant participate in our Cognitive Computing domain because they lack skills, wealth, or convenient access to existing solutions?
– Are there any disadvantages to implementing Cognitive Computing? There might be some that are less obvious?
– Do Cognitive Computing rules make a reasonable demand on a users capabilities?
Cognitive computer Critical Criteria:
Facilitate Cognitive computer engagements and don’t overlook the obvious.
– What role does communication play in the success or failure of a Cognitive Computing project?
– How do we know that any Cognitive Computing analysis is complete and comprehensive?
– Which individuals, teams or departments will be involved in Cognitive Computing?
Cognitive reasoning Critical Criteria:
Map Cognitive reasoning projects and shift your focus.
– In what ways are Cognitive Computing vendors and us interacting to ensure safe and effective use?
– To what extent does management recognize Cognitive Computing as a tool to increase the results?
– What are current Cognitive Computing Paradigms?
Computer vision Critical Criteria:
Drive Computer vision decisions and triple focus on important concepts of Computer vision relationship management.
– What are the key elements of your Cognitive Computing performance improvement system, including your evaluation, organizational learning, and innovation processes?
– How do senior leaders actions reflect a commitment to the organizations Cognitive Computing values?
– How do mission and objectives affect the Cognitive Computing processes of our organization?
Computing platform Critical Criteria:
Drive Computing platform projects and remodel and develop an effective Computing platform strategy.
– Is Cognitive Computing Realistic, or are you setting yourself up for failure?
– What are the Key enablers to make this Cognitive Computing move?
Context awareness Critical Criteria:
Scrutinze Context awareness visions and oversee Context awareness management by competencies.
– Information/context awareness: how can a developer/participant restore awareness in project activity after having been offline for a few hours, days, or weeks?
– Will new equipment/products be required to facilitate Cognitive Computing delivery for example is new software needed?
Data analysis Critical Criteria:
Use past Data analysis results and know what your objective is.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Cognitive Computing services/products?
– Think about the functions involved in your Cognitive Computing project. what processes flow from these functions?
– In a project to restructure Cognitive Computing outcomes, which stakeholders would you involve?
– 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:
Concentrate on Dialog system adoptions and tour deciding if Dialog system progress is made.
– Is the Cognitive Computing organization completing tasks effectively and efficiently?
Enterprise cognitive system Critical Criteria:
Graph Enterprise cognitive system management and define Enterprise cognitive system competency-based leadership.
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Cognitive Computing?
– What is our Cognitive Computing Strategy?
Face detection Critical Criteria:
Revitalize Face detection engagements and modify and define the unique characteristics of interactive Face detection projects.
– What are the disruptive Cognitive Computing technologies that enable our organization to radically change our business processes?
– How can you measure Cognitive Computing in a systematic way?
Fraud detection Critical Criteria:
Apply Fraud detection visions and adjust implementation of Fraud detection.
– What other organizational variables, such as reward systems or communication systems, affect the performance of this Cognitive Computing process?
– What other jobs or tasks affect the performance of the steps in the Cognitive Computing process?
– What are specific Cognitive Computing Rules to follow?
Human brain Critical Criteria:
Accumulate Human brain quality and perfect Human brain conflict management.
– How do your measurements capture actionable Cognitive Computing information for use in exceeding your customers expectations and securing your customers engagement?
– How do we Lead with Cognitive Computing in Mind?
Human–computer interaction Critical Criteria:
Inquire about Human–computer interaction governance and point out improvements in Human–computer interaction.
– Are there any easy-to-implement alternatives to Cognitive Computing? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– Does Cognitive Computing appropriately measure and monitor risk?
Machine learning Critical Criteria:
Study Machine learning issues and oversee Machine learning requirements.
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– How do we Identify specific Cognitive Computing investment and emerging trends?
– How can we improve Cognitive Computing?
Risk assessment Critical Criteria:
Administer Risk assessment tasks and create Risk assessment explanations for all managers.
– 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?
– Is the risk assessment approach defined and suited to the ISMS, identified business information security, legal and regulatory requirements?
– Does the risk assessment approach helps to develop the criteria for accepting risks and identify the acceptable level risk?
– Are standards for risk assessment methodology established, so risk information can be compared across entities?
– What core IT system are you using? Does it have an ERM or risk assessment module; and if so, have you used it?
– What operating practices represent major roadblocks to success or require careful risk assessment?
– 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?
– Are assumptions made in Cognitive Computing stated explicitly?
– Are regular risk assessments executed across all entities?
– Do you use any homegrown IT system for ERM or risk assessments?
– What drives the timing of your risk assessments?
– Are regular risk assessments executed across all entities?
– Do you use any homegrown IT system for risk assessments?
– Are risk assessments at planned intervals reviewed?
– What triggers a risk assessment?
Sentiment analysis Critical Criteria:
Examine Sentiment analysis strategies and forecast involvement of future Sentiment analysis projects in development.
– What will be the consequences to the business (financial, reputation etc) if Cognitive Computing does not go ahead or fails to deliver the objectives?
– How representative is twitter sentiment analysis relative to our customer base?
– Do you monitor the effectiveness of your Cognitive Computing activities?
– What are the long-term Cognitive Computing goals?
Signal processing Critical Criteria:
Think about Signal processing management and reduce Signal processing costs.
– Are accountability and ownership for Cognitive Computing clearly defined?
– Are we Assessing Cognitive Computing and Risk?
Social neuroscience Critical Criteria:
Grade Social neuroscience decisions and inform on and uncover unspoken needs and breakthrough Social neuroscience results.
– Who will be responsible for deciding whether Cognitive Computing goes ahead or not after the initial investigations?
– What is the purpose of Cognitive Computing in relation to the mission?
Speech recognition Critical Criteria:
Refer to Speech recognition planning and grade techniques for implementing Speech recognition controls.
– Consider your own Cognitive Computing project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– What is our formula for success in Cognitive Computing ?
Synthetic intelligence Critical Criteria:
Model after Synthetic intelligence tasks and oversee Synthetic intelligence requirements.
– Have all basic functions of Cognitive Computing been defined?
Unstructured data Critical Criteria:
Merge Unstructured data planning and separate what are the business goals Unstructured data is aiming to achieve.
– 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)?
– What tools and technologies are needed for a custom Cognitive Computing project?
– How will you measure your Cognitive Computing effectiveness?
Unstructured information Critical Criteria:
Adapt Unstructured information outcomes and find the essential reading for Unstructured information researchers.
– 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?
– Why is it important to have senior management support for a Cognitive Computing project?
– Do the Cognitive Computing decisions we make today help people and the planet tomorrow?
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.
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” by Haluk Demirkan, Seth Earley et al.
What is cognitive computing? – Definition from …
Adaptive system External links:
TF Adaptive System Dentist – YouTube
Pat Ebright – Complex Adaptive System Theory – YouTube
Adaptive user interface External links:
An Adaptive User Interface in Healthcare – ScienceDirect
What is Adaptive User Interface | FlowPaper
Affective computing External links:
People ‹ 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:
What is bias in artificial neural network? – Quora
Best Artificial Neural Network Software in 2018 | G2 Crowd
Training an Artificial Neural Network – Intro | solver
Automated reasoning External links:
UCLA Automated Reasoning Group – YouTube
ARCOE – Workshop on Automated Reasoning about …
Handbook of Automated Reasoning – ScienceDirect
Cognitive computer External links:
Restb.ai – Cognitive Computer Vision | Crunchbase
Cognitive Computer Solutions – Home | Facebook
Cognitive reasoning External links:
What Is Cognitive Reasoning? – YouTube
Cognitive Reasoning – Parrot Software
Brubaker Cognitive Reasoning Package – alimed.com
Computer vision External links:
Computer Vision Syndrome – VSP Vision Care
Computer vision – Microsoft Research
Sighthound – Industry Leading Computer Vision
Computing platform External links:
Microsoft Azure Cloud Computing Platform & Services
DeepBrainChain: Decentralized AI Computing Platform
In-Memory Computing Platform | GigaSpaces
Context awareness External links:
Semusi – Context Awareness Made Easy
Data analysis External links:
Data Analysis – Illinois State Board of Education
[PPT]Qualitative Data Analysis and Interpretation
The Difference Between Data Analysis and Data Modeling
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:
Debit Card Security | Fraud Detection & Protection | RushCard
Fraud Detection and Fraud Prevention Services | TransUnion
Business Fraud Detection | Fraud Shield by Experian
Human brain External links:
Brain Anatomy, Anatomy of the Human Brain
Human Brain: Major Structures and their Functions – YouTube
OHBM 2018 – Organization for Human Brain Mapping
Machine learning External links:
DataRobot – Automated Machine Learning for Predictive …
Machine Learning: What it is and why it matters | SAS
Appen: high-quality training data for machine learning
Risk assessment External links:
Risk Assessment Tools | OpioidRisk
[PDF]DELIBERATE RISK ASSESSMENT WORKSHEET
Ground Risk Assessment Tool – United States Army …
Sentiment analysis External links:
Sentiment Analysis – Brandwatch
Sentiment Analysis on Movie Reviews | Kaggle
Sentiment Analysis | Lexalytics
Signal processing External links:
Deep Learning | Signal Processing | DeepSig Inc.
Social neuroscience External links:
[PDF]The Social Neuroscience of Empathy – Greater Good
Home | Developmental Social Neuroscience Laboratory
Social Neuroscience – Michigan State University
Speech recognition External links:
Speech API – Speech Recognition | Google Cloud Platform
Amazon Transcribe – Automatic Speech Recognition – AWS
Dictate text using Speech Recognition – Windows Help
Synthetic intelligence External links:
What is SYNTHETIC INTELLIGENCE? What does …
Synthetic Intelligence Network – Home | Facebook
SIML – The Synthetic Intelligence Markup Language
Unstructured data External links:
Differences Between Structured & Unstructured Data – …
Structured vs. Unstructured data – BrightPlanet
Scale-Out NAS for Unstructured Data | Dell EMC US
Unstructured information External links:
Manage Unstructured Information as Part of EIM |ASUG
Unstructured Information Management Architecture SDK – IBM
An unstructured information management system (UIMS…