“The term “data provenance”, sometimes called “data lineage,” refers to a documented trail that accounts for the origin of a piece of data and where it has moved from to where it is presently.” – National Library of Medicine
In my September 3rd post, I referred to the Black Box Challenge and how it has paralyzed many CFOs from embracing AI to the extent they should.
Why is there a Black Box challenge – why are its inner workings such a mystery?
In his recent LinkedIn post, Daniel J. Finkenstadt wrote about “the amazing ease with which one can merge data, clean data, analyze data etc. with code interpreter AND the concerning ease with which one can create and manipulate data for the results we want.” In other words, what’s in the black box shouldn’t be a mystery, let alone a challenge. Yet, for many, it is just that – a mystery of unknown AI machinations. It doesn’t make sense, or does it?
To help shed some light on the above paradox that is at the crossroads of human involvement and human abdication, is the following excerpt from a discussion stream on LinkedIn featuring some of the best data minds in the industry:
Think about the implications for new clinical trials, and the damage that could be done here… not to mention the slough of empirical studies that will falsify data. How do we now validate datasets?
Rob Handfield, we’ll have to mandate access to the collection platform and the way we’ve focused on provenance of supply and sw will now extend to raw data.
“You nailed it, Michael Lamoureux, e.g., the following excerpt:
“Deterministic algorithms developed by smart people that have studied the problem, tested their assumptions, and been consistently proven reliable are the answer. They may be based on machine learning, but machine learning that is expertly selected, tuned, and monitored by validation code that detects when the algorithm is not performing to expectation and interjects a human into the process.”
In a recent post, I wrote the following:
“The critical play is not the tech but the expertise behind the tech – the market expertise and experience to leverage tech to solve a problem.” – https://bit.ly/3R2SdT9“
The only way to ensure “data provenance and integrity” is through human oversight and intervention. In short we cannot abdicate our critical thinking responsibility to AI.
CONCLUSION: The only way to solve the mystery of the AI Black Box is to step into “The Box.” We are not simply spectators to the AI evolution; we are its facilitators. AI is an extension of human thought, not a replacement for it!
What do you think, or as Michael Lamoreaux so aptly put it – Thunk?
Procurement Insights
Getting Beyond The “Black Box”: Why Data Provenance and Integrity Is Up To You, Not AI!
Posted on September 5, 2023
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“The term “data provenance”, sometimes called “data lineage,” refers to a documented trail that accounts for the origin of a piece of data and where it has moved from to where it is presently.” – National Library of Medicine
In my September 3rd post, I referred to the Black Box Challenge and how it has paralyzed many CFOs from embracing AI to the extent they should.
Why is there a Black Box challenge – why are its inner workings such a mystery?
In his recent LinkedIn post, Daniel J. Finkenstadt wrote about “the amazing ease with which one can merge data, clean data, analyze data etc. with code interpreter AND the concerning ease with which one can create and manipulate data for the results we want.” In other words, what’s in the black box shouldn’t be a mystery, let alone a challenge. Yet, for many, it is just that – a mystery of unknown AI machinations. It doesn’t make sense, or does it?
To help shed some light on the above paradox that is at the crossroads of human involvement and human abdication, is the following excerpt from a discussion stream on LinkedIn featuring some of the best data minds in the industry:
Rob Handfield – Professor, Advisor, Consultant
Think about the implications for new clinical trials, and the damage that could be done here… not to mention the slough of empirical studies that will falsify data. How do we now validate datasets?
Replies on Rob Handfield’s comment
Daniel J. Finkenstadt – Author of Bioinspired Strategic Design (2024) | USAF Officer | Consultant
Rob Handfield, we’ll have to mandate access to the collection platform and the way we’ve focused on provenance of supply and sw will now extend to raw data.
Manu Fontaine – Founder & CEO at Hushmesh Inc. The Mesh is the next Web.
Daniel and Rob agreed. We are moving into a world where we need global assurance of data provenance and integrity for everyone and everything.
Jon W. Hansen – Sales Strategist and Ghostwriter: Creating the “write” words for you! Thinkers360 Top 50 Global Thought Leaders & Influencers on Procurement! (April 2021)
Rob Handfield, Daniel J. Finkenstadt, Manu Fontaine, reading your comments, reminded me of a saying from my early days in high-tech, e.g., “garbage in-garbage out.”
Here is my response to a great post by Michael Lamoureux:
“You nailed it, Michael Lamoureux, e.g., the following excerpt:
“Deterministic algorithms developed by smart people that have studied the problem, tested their assumptions, and been consistently proven reliable are the answer. They may be based on machine learning, but machine learning that is expertly selected, tuned, and monitored by validation code that detects when the algorithm is not performing to expectation and interjects a human into the process.”
In a recent post, I wrote the following:
“The critical play is not the tech but the expertise behind the tech – the market expertise and experience to leverage tech to solve a problem.” – https://bit.ly/3R2SdT9“
The only way to ensure “data provenance and integrity” is through human oversight and intervention. In short we cannot abdicate our critical thinking responsibility to AI.
Here is the link to Michael’s post – https://bit.ly/3Z5WQhp
Tagging for comment David Loseby Kelly Barner Dr. Thierry Fausten Tom Redman Greg Tennyson Michael Cadieux
CONCLUSION: The only way to solve the mystery of the AI Black Box is to step into “The Box.” We are not simply spectators to the AI evolution; we are its facilitators. AI is an extension of human thought, not a replacement for it!
What do you think, or as Michael Lamoreaux so aptly put it – Thunk?
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