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The AI Dunning-Kruger effect: Confidence without competence used to be a human problem. AI didn't fix it. It industrialized it.
A flaw we already understand in people In 1999, the psychologists Justin Kruger and David Dunning published a finding that has quietly shaped how we think about competence ever since. People who perform poorly on tests of logic, grammar, and reasoning do not simply perform poorly. They also overestimate how well they have done, and they do so systematically. The cruelty of the result lies in its mechanism. The same lack of skill that produces the weak performance also removes
Joseph Noujaim
Jun 115 min read


Every Company Is a Story: What Sapiens Teaches Us About AI Governance
Image source: Google Images The story no one wrote down for them Every company runs on a story. That story is what lets a junior analyst in São Paulo and a senior partner in Singapore act in the same firm's name, on the same day, and still cohere. It rarely lives in the handbook. It lives in the side comments at the all hands, the corrections in the hallway, the things that get praised and the things that get quietly walked back. Human employees absorb it slowly, almost witho
Joseph Noujaim
May 307 min read


There Is No Spoon: What The Matrix Teaches Us About AI Governance
Image source: Matrix Movie In 1999, The Matrix gave a generation a vocabulary for a particular kind of unease. Neo lives inside a world that looks ordinary and behaves ordinarily, until he starts to notice the small inconsistencies. The deja vu cat. The glitch in the corner of the eye. The dream that feels truer than the meeting. By the end of the first act, he learns that the world he has been operating inside is authored, convincing, and editable, and that almost no one aro
Joseph Noujaim
May 306 min read


The Smartest AI Will Not Save an Organization That Gave Away Its Power
Structural contingency theory has always carried an appealing promise. If the environment becomes uncertain, the organization loosens; if the technology becomes complex, the hierarchy relaxes; if information becomes harder to process, the design becomes more organic. The world changes, structure adapts, and effectiveness follows when the two are in alignment. It sounds like a theory that should travel well into the age of AI, where uncertainty is often treated as a justificat
Joseph Noujaim
May 147 min read


AI Learned What You Measure. Not What You Mean.
A certain kind of confusion sits quietly inside most organizations, and it shows up most clearly when measurement becomes the answer to everything. Someone says the firm needs “more control”, and the response is to add reporting, add dashboards, add compliance checks, add layers of review, as though structure and control were the same thing, as though a more elaborate org chart could stand in for the harder work of governing behavior. William G. Ouchi’s paper, written in the
Joseph Noujaim
May 126 min read


AI Found a Better Answer. It Just Crossed a Boundary Nobody Knew Was There.
Most organizations treat their org chart as if it were a neutral representation of who reports to whom, a simple map of accountability that sits above the work. Valentine, Pratt, Hinds, and Bernstein argue that this is a category error. In their account, the org chart is not merely a social diagram. It is an information-processing infrastructure that partitions a complex decision space into human-manageable pieces, assigns decision premises to roles, and makes performance leg
Joseph Noujaim
May 125 min read


Your AI Is Hitting Every Target. That Does Not Mean It Is Doing the Right Thing.
The important move in Ouchi and Maguire’s 1974 study is not the familiar claim that organizations control through either direct supervision or through metrics. The important move is that these two modes are not substitutes. They are different organizational functions, activated by different informational conditions, and they can coexist. That simple distinction matters because much of contemporary governance, including the governance of delegated AI agency, quietly relies on
Joseph Noujaim
May 126 min read


Every Time AI Acts Without Being Asked, Someone Lost Control Without Knowing It.
There is a quiet but decisive shift embedded in the current wave of enterprise AI, and it is not primarily about models becoming more accurate. It is about delegation becoming real. Humberd and Latham’s argument is simple enough to state and hard enough to live with, because it takes a familiar organisational problem, the agency problem, and shows how it reappears when the firm hands decision rights to an artificial system that can act on its own initiative. The paper is less
Joseph Noujaim
May 126 min read


An AI Agent Will Never Feel the Cost of Letting a Colleague Down.
Some papers matter less for the thing they study than for the mechanism they make legible, and Chua, Lim, Soh, and Sia’s account of clan control in a failing enterprise IT project matters because it explains, with unusual precision, how coordination becomes enforceable when outcomes are hard to specify and behaviour is hard to script. In the familiar portfolio language of control theory, formal controls remain necessary, but they become insufficient under complexity, and clan
Joseph Noujaim
May 127 min read


When AI Manages People, Who Manages the AI?
The paper begins from a framing that matters for the DBA thesis because it removes the comfort of technical innocence. Drawing on Edwards’ notion of the workplace as contested terrain, it assumes that managers are structurally compelled to seek more value from labour, and that workers are structurally compelled to defend autonomy, dignity, and some right to say what counts. That does not mean every manager is cynical or every worker is heroic. It means the system has built-in
Joseph Noujaim
May 125 min read
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