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Last Updated on: May 21, 2022

CHAOS Report Beyond Infinity: a hardcover version

May 21, 2022

 CHAOS Report Beyond Infinity: a hardcover version is a collector’s item.   This 260-page printed book is in full color with hundreds of charts, tables, and graphics. This book is broken down into 10 sections. In the first section, we start with the three new Factors of Success, Good Place, Good Team, and Good Sponsor. Then we look at the root cause of project failure which is poor decision latency. Then we look at the root cause poor decision latency which is low emotional maturity. In Section 2, We then look at the Classic CHAOS charts. We follow these charts with more charts in Section 3: Type and Styles of Projects, In the next three sections are details of The Good Sponsor, The Good Team and The Good Place. Section 7 is an overview of the current CHAOS Database. The next section is an overview of New Resolution Database Benchmark. The Dutch Connection describes the contributions made by the Netherlands and Belgium and their effect on our research. Myths and Illusions debunks some typical beliefs about “project improvement.” The Epilogue looks at 60 years of software development.

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The Elephant and the 1,000 Mice

Apr 12, 2021

Infinite Flow uses the elephant and the mice together to form a more perfect union and to allow continuous innovation at the business operations level.

CHAOS Tuesday News

Ethics and AIML

May 20, 2022

In Wisdom Wednesday # 11 and CHAOS Tuesday Show # 132 we discuss the concerns on ethical issues around artificial intelligence and machine learning (AIML). Our guest of this show is Minerva Tantoco, a startup founder, author, advisor, and speaker on Ethical AI.  In this program, Minerva will discuss the history of AIML and how this technology can be used for good and how to use it ethically.  Minerva will also discuss some of the ways AIML can be used unethically either intentionally or unintentionally. Minerva has stories of how AIML can be bias because of how you collect the data and use it.  She also talks about how AIML is used for good. 

In this show you will take away: 

·      History of AIML 

·      Why be concerned? 

·      Who is responsible for errors? 

·      Privacy of data

·      AIML for good

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