Overview of Cognitive Edge SensemakerTM

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    Overview of Cognitive Edge SensemakerTM - Presentation Transcript

    1. Overview of SenseMakerTM
    2. Greenspan testimony to Congress, 24 October 2008 •  Conceded that the credit crunch in the banking industry had left him in a state of shocked disbelief, calling the financial crisis a "once-in-a-century credit tsunami," saying that it is “much broader than anything I could have imagined.”
 •  Greenspan said his level of shock was based on the fact that the ideology to which he subscribes seemed to be working “exceptionally well” for “40 years or so” until this crisis hit
 •  The expectations of the Federal Reserve were heavily reliant on highly complicated quantitative models that scanned for known risks and left no room for unprecedented events
 •  Quant-driven hedge funds and risk managers at major banks took the same approach and very few spotted the emerging crisis
    3. Some facts about humans…. Some facts - Humans... •  can only see 0.01% of their visual range in sharp focus at any one time •  will only ever seen approximately 5% of what is available •  see the world as a series of dots based previous experience •  make decisions by scanning thousands of fragmented patterns stored in long term memory and applying the first pattern that matches •  are pattern recognition intelligences NOT information processing devices Source: Theories of Visual Perception - Ian E. Gordon
    4. Everything is fragmented Everything is Fragmented •  IF the world as a series of dots joined up on the basis of past experience •  IF Humans are Pattern Recognition beings NOT Information Processing machines...... How do we make sense of the world so we can act? •  Narrative and visual images are ways to convey complex knowledge and ideas - a supplement to traditional ways of learning and interpretation of our world •  Decision making occurs through the blending of fragmented experiences gained through narrative and personal understanding •  Multiple fragments provide the basis for interpretation
    5. Surveys & Interview limitations Survey & Interview limitations Traditional surveys & interviews have limitations: •  the questions utilised for these techniques assume the validity of a pre- existing hypothesis (it is virtually impossible to develop the survey questions without a hypothesis) •  interviewees tend to provide neat (rationalised) answers when asked for their opinions which normally doesn’t resemble their real-world experiences at all •  survey and interview questions provide minimal context—how many times have you answered a survey and found yourself thinking: ‘It depends…’? •  traditional survey techniques are too open to gaming or manipulation to provide any value at all. If interesting patterns are discovered, they often cannot be explained unless further research is commissioned. SenseMakerTM reduces the influence of “Experts”
    6. Narrative fragment collection Narrative fragment collection Photo Paper survey You Tube Voice recording Anecdote Circles Websites Physical object Blog SenseMakerTM enables narrative capture from many different sources
    7. Narrative fragments Narrative fragments Whose "increased selfishness"?? Litigators?? That will hinder many volunteers, regardless of time, attitudes, and generations. Who can seriously afford to be sued for any perceived wrong doing while do gooding?? Like everything in our highly dynamic society today, volunteering attitudes and experiences are shifting. Some more positive, some negative, and many traditional volunteer beliefs and services need to mirror these changes to move with the times to survive the times. Who killed the Volunteer? SenseMakerTM uses fragments to uncover patterns not readily visible
    8. Quantitative & Qualitative data Quantitative & Qualitative Data Summary Statistics for graph: In this story people feel they are -- Lacking choice X The people in this story could be described as -- Old ways But everything else is great.. Number of items: 36 ~~~~~ X axis (In this story people feel they are -- Lacking choice) If your lucky you'll get a competent supervisor. If not you can end up with someone who doesn't do their job Mean: 68.6667 but will always appear to others that they are helpful Median: 79.5 25th percentile: 36.25 and hard working. They will take credit for your hard 75th percentile: 97.75 work and even put their name to it. They will quietly Standard deviation: 31.9616 and without witnesses bully you all the while justifying Skewness: -0.6409 (skewed to the left) why they need you to do as they say. If your not good Skewness standard error (SSE, sqrt(6/n)): 0.4082 at dealing with this type of conflict you often feel angry Skewness Z score (skewness / SSE): -1.5699 and frustrated. Skewness indicates normal distribution (abs Z score < 2): yes Kurtosis: -1.1866 (platykurtic or heavier in the tails) Standard error for kurtosis (KSE, sqrt(24/n)): 0.8165 Kurtosis Z score (Kurtosis / KSE): -1.4533 Kurtosis indicates normal distribution (abs Z score < 2): yes ~~~~~ Y axis (The people in this story could be described as -- Old ways) Mean: 65.8056 Median: 79.0 25th percentile: 24.0 75th percentile: 99.0 Standard deviation: 33.0427 Skewness: -0.4929 (skewed to the left) Skewness standard error (SSE, sqrt(6/n)): 0.4082 Skewness Z score (skewness / SSE): -1.2074 Skewness indicates normal distribution (abs Z score < 2): yes Kurtosis: -1.4432 (platykurtic or heavier in the tails) Standard error for kurtosis (KSE, sqrt(24/n)): 0.8165 Kurtosis Z score (kurtosis / KSE): -1.7676 Restrictions Kurtosis indicates normal distribution (abs Z score < 2): yes Correlation We're under staffed, under resourced, aging demographic. Use parametric correlation test? yes Pearson product-moment correlation coefficient: 0.4346 Pearson correlation significance: 0.0081 Significance threshold: 0.05 Correlation is significant? yes SenseMakerTM provides hard and soft data for actionable results
    9. Quantitative & Qualitative data Measurement
    10. Quantitative & Qualitative data Fitness Landscapes
    11. SenseMaker TM Demonstration
    12. Example analysis
    13. Example analysis
    14. Example Analysis
    15. Example Analysis
    16. Example Analysis
    17. Example Analysis
    18. Example Analysis
    19. Example Analysis
    20. Example Analysis
    21. Example Analysis

    + Chris FletcherChris Fletcher, 9 months ago

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