Building ‘idiot proof’ systems is not the answer

A group of academics recently asked me, “In the technology space, how much do you need to know today to be considered not ignorant?”

Both philosophers (the folks who study knowledge) and cognitive scientists (the folks who study the acquisition and application of knowledge) agree that the base of knowledge required to remain relevant in society is expanding. Wiley, which published my book The New Know, annually adds approximately 100 new books to its 2,500-title For Dummies series.

Knowledge is a moving target. There is new knowledge. There is bad knowledge — beliefs that were always flat out erroneous. There is no longer good knowledge — things that once were true but no longer are.

Like the Central Intelligence Agency, CIOs are tasked with supporting decision-makers with analyses of the current situation, with advisories regarding when those conditions are likely to change, and warning of risks inherent to the full spectrum of technology investment choices.

Historically, the 18 federal organizations that make up the US Intelligence Community will not make policy recommendations. They just provide the analysis. CIOs have to do more. The first Director of National Intelligence, John Negroponte, once noted, “Vigilance is not enough.”

Experience tells us that there is no such thing as an “idiot proof” system. It is not enough to deploy great systems. CIOs have to ensure that the stakeholders using these systems know enough to extract full value from the technology being provided.

Knowledge pumping — providing the baseline of facts necessary to make decisions — has to be accompanied by multi-constituent executive education. CIOs have to ensure that key stakeholders understand underlying technology conditions; have to be able forecast future conditions or outcomes; and test hypotheses or theories.

Ideally, this would involve portraying and communicating results using data visualization. Vince Kellen, CIO for The Texas A&M University System, who is typically three or four standard deviations in front of the curve, refers to such illustrations as “anchor visuals.”

What anchor visuals are you using to keep your community of stakeholders moving in the right direction?

The level of satisfaction or dissatisfaction stakeholders have toward technology in general and artificial intelligence specifically are directly tied to the quality of the narrative surrounding the technology.

In Ancient Wisdom for Polarized Times: Why Humanity Needs Herodotus, the Man Who Invented History, Emily Katz Anhalt insists “stories have a profound influence on who we are and who we become.”

Does your technology and AI messaging link to mission and the ability to solve a hard problem? If that story is couched solely in terms of monetary gains, you may have a problem.

In an internal memo, OpenAI CEO Sam Altman opined that “[AI] missionaries will beat [AI] mercenaries.”

Currently an enormous amount of resource is being devoted to agentic AI with the objective of automating workflows. In Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work and Life, Pascal Bornet and Jochen Wirtz express concern that “We’re treating humans like robots and AI like creatives. It’s time to flip the equation.” It is ironic that we are spending huge amounts of money training models and very little educating the humans using these models.

Deloitte’s 2025 Connected Consumer Survey observed, “Among those surveyed who are using gen AI for work, 40% say their companies provide training.” Does this mean that 60% of the economy is simply deploying the tools and hoping for the best?

The mainstream business press tells us that the tech ecosystem has moved from a phase of “move fast and break things” to an infrastructure groundwork focused on “moving slow and building things.” Experienced CIOs know at the essence of their beings that before moving they and their stakeholders have to “know things.”

By investing in muggle tech knowledge (knowledge pumping) we are increasing human agency and expanding our capacity for innovation.

Generally, people want to understand the technology that surrounds them. This willingness to know is tempered by what Keith E. Stanovich in The Bias That Divides Us: The Science and Politics of Myside Thinking, refers to as “myside bias”: “we evaluate evidence, generate evidence, and test hypotheses in a manner biased toward our own prior beliefs, opinions, and attitudes.”

Effective knowledge pumping has to be individualized to the mental starting point of the stakeholder.

A switched-on, tech-savvy user base has been the White Whale of CIO Ahabs for decades.