Stop "Envangelizing" Generative AI Without Data Governance
To paraphrase Lutz Finger, investing in a business — or using a service — which relies on public vs proprietary data should be amongst the first steps of due diligence by a Product team.
How real is the moat of training data, which has non-trivial costs?
Even Andreessen Horowitz has public articles making it clear that the compute costs are high (they will come down).
The business case for the information architecture also has to cover external expenses, such as potential legal claims.
Future Ready
The CEO of Databricks said:
“The leading companies in the future are going to be data and AI companies — healthcare, retail, you name it….in five or 10 years, to be the CEO in any of these industries, you’ll need to have a data-and-AI background.”
Product thought leaders are writing today about how the function needs to up-skill.
The implication is that data products will be even more entrenched in B2B workflows and B2C offerings.
The phrase “data is the new oil” was coined by a mathematician in 2006.
Note: dinosaur juice is a volatile material that is highly-regulated for a reason and it can literally blow up in your face.
If “software is eating the world” and digital transformation is inevitable, then integrating data governance should be Step 0 for leading Product organizations.
Put On Your Thinking Cap
There's information asymmetry between all of Porter's Five Forces.
A Product team evaluating the return on investment for AI-augmentation should consider:
Where did the words in the language model come from?
Where will training data come from in the future?
Do we trust the quality of the content?
Is the extraction, transform, and load of data sustainable and non-toxic to operators and consumers?
Have we staffed a "red team" to jail-break our use case?
Is it true that the future promised by AI is written with stolen words?
I think it’s a business imperative that future-ready Product teams be ruthless in pursuing answers to these questions while doing due diligence.
The value of Ruthless has deep reasons...it’s derived from Old English “rue”, meaning to pity or lament. To have less rue is good and a complete absence of rue is better. The team is clear on vision, priorities, conflicts, responsibilities, expected outcomes, risks, and issues. The team is focused on getting the most juice for the budgeted amount of squeeze. Ruthless implies a vacuum of rue. There are no bitter regrets.
Adopt systems thinking, acknowledge contrarian views, and then decide whether to build, own, and operate - or not - the future-ready system.