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Bill Schmarzo
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  • Palo Alto, CA
  • United States
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Latest Activity

Bill Schmarzo posted a blog post

Crossing the Analytics Chasm with Nanoeconomics

“I love it when a plan comes together” – John (Hannibal) Smith, The A TeamOne of the biggest challenges that I continue to see are organizations struggling to cross the Analytics Chasm; to transition their use of data and analytics from retrospective Business Intelligence that monitors what has happened to AI/ML-driven analytics that predict what is likely to happen and…See More
Sunday
Bill Schmarzo's blog post was featured

Crossing the Analytics Chasm with Nanoeconomics

“I love it when a plan comes together” – John (Hannibal) Smith, The A TeamOne of the biggest challenges that I continue to see are organizations struggling to cross the Analytics Chasm; to transition their use of data and analytics from retrospective Business Intelligence that monitors what has happened to AI/ML-driven analytics that predict what is likely to happen and…See More
Sunday
Jag Bedi liked Bill Schmarzo's blog post A Winning Game Plan For Building Your Data Science Team
Jan 8
Bill Schmarzo posted blog posts
Jan 4
Bill Schmarzo's blog post was featured

Ethical AI, Monetizing False Negatives and Growing Total Addressable Market

What if I told you that companies that don’t embrace Ethical AI are leaving significant amounts of “Money on the Table”; that they are not only missing out on potentially profitable customers, but that over time they are eroding their Total Addressable Market (TAM)?  Do I have your attention now?After I published the blog “…See More
Jan 3
Norberto J. Sanchez liked Bill Schmarzo's blog post Human Decision-making in a Big Data World
Dec 29, 2020
Norberto J. Sanchez liked Bill Schmarzo's blog post Human Decision-making in a Big Data World
Dec 29, 2020
Bill Schmarzo commented on Bill Schmarzo's blog post The Ethical AI Application Pyramid
"Lance, great point on how professional sports teams (my son played in the Orioles organization) do keep track of their False Negatives by tracking the development and success of the "ones that got away."  That data can be used to not…"
Dec 23, 2020
Lance Norskog commented on Bill Schmarzo's blog post The Ethical AI Application Pyramid
"There are false negative hiring databases available for pro sports (the stats) and academics (papers and rankings). Someone did a study on pro sports and decided that the big teams always overbid for the highest talent, relative to the value the…"
Dec 23, 2020
Bill Schmarzo's blog post was featured
Dec 22, 2020
Bill Schmarzo posted a blog post
Dec 22, 2020
Bill Schmarzo commented on Bill Schmarzo's blog post The Ethical AI Application Pyramid
"I agree that any analysis of False Positives (or False Negatives) takes a lot of human diligence.  But at least with False Positives (the people that you hired but did not succeed, or the students you admitted but they dropped out, or the loan…"
Dec 22, 2020
Bill Schmarzo's blog post was featured

The Ethical AI Application Pyramid

In the blog “How Can Your Organization Manage AI Model Biases?”, I wrote:“In a world more and more driven by AI models, Data Scientists cannot effectively ascertain on their own the costs associated with the unintended consequences of False Positives and False Negatives. Mitigating unintended consequences requires the collaboration across a diverse set of stakeholders in order to…See More
Dec 21, 2020
Roy Wilsker commented on Bill Schmarzo's blog post The Ethical AI Application Pyramid
"Unfortunately, the False Positive hiring issue you mention is much more difficult than what your article indicates. If the reason the hirees don't do well is because of institutional issues, e.g., harassment, biased evaluations, lack of…"
Dec 21, 2020
Bill Schmarzo posted a blog post

The Ethical AI Application Pyramid

In the blog “How Can Your Organization Manage AI Model Biases?”, I wrote:“In a world more and more driven by AI models, Data Scientists cannot effectively ascertain on their own the costs associated with the unintended consequences of False Positives and False Negatives. Mitigating unintended consequences requires the collaboration across a diverse set of stakeholders in order to…See More
Dec 20, 2020
William Vorhies liked Bill Schmarzo's blog post Introducing the “4 Stages of Data Monetization”
Dec 17, 2020

Profile Information

Company:
Hitachi Vantara
Job Title:
CTO IoT and Analytics
Seniority:
C-Level
Job Function:
Data Science, AI, Business Analytics, IoT
Industry:
Technology
Short Bio:
Currently, CTO, IoT & Analytics Hitachi Vantara. 30+ years of data and analytics experience. Write, speak and lecture frequently on Data Science, Digital Transformation and the Economic Value of Data.

Also teach at the University of San Francisco School of Management and National University of Ireland-Galway.
LinkedIn Profile:
http://https://infocus.emc.com/author/william_schmarzo/
Interests:
Contributing, Other

Bill Schmarzo's Blog

Crossing the Analytics Chasm with Nanoeconomics

Posted on January 11, 2021 at 8:30am 0 Comments

I love it when a plan comes together” – John (Hannibal) Smith, The A Team

One of the biggest challenges that I continue to see are organizations struggling to cross the Analytics Chasm; to transition their use of data and analytics from retrospective Business Intelligence that monitors what has happened to AI/ML-driven…

Continue

Ethical AI, Monetizing False Negatives and Growing Total Addressable Market

Posted on January 3, 2021 at 11:30pm 0 Comments

What if I told you that companies that don’t embrace Ethical AI are leaving significant amounts of “Money on the Table”; that they are not only missing out on potentially profitable customers, but that over time they are eroding their Total Addressable Market (TAM)?  Do I have your attention now?

After I published the blog “…

Continue

Mastering Nanoeconomics in the Era of Digital Transformation

Posted on December 22, 2020 at 4:36pm 0 Comments

As I state in the opening paragraph of my new book “The Economics of Data, Analytics, and Digital…

Continue

The Ethical AI Application Pyramid

Posted on December 19, 2020 at 3:08pm 4 Comments

In the blog “How Can Your Organization Manage AI Model Biases?”, I wrote:

“In a world more and more driven by AI models, Data Scientists cannot effectively ascertain on their own the costs associated with the unintended consequences of False Positives and False Negatives. Mitigating unintended consequences requires the collaboration across a diverse set of stakeholders in…

Continue

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