Algorithm & Blues
AI research translated into decisions executives can actually make. One clear argument per issue, published weekly.
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Fifty Percent More of the Same
Human-AI teams produced 50 percent more ad copy in a new MIT/Johns Hopkins field experiment measured against 5 million real impressions, but the extra volume clustered around similar ideas. The output metric looked good while diversity collapsed — a cost almost no team is measuring.
Access control answers whether an agent can see data, but not how much of the relevant picture is missing. A new benchmark on partial-evidence reasoning finds agents produce overconfident answers when their authorized view is incomplete — unless evidence boundaries are carried through the workflow.
Stronger AI models produce better work — until a human reviewer is added. A Yale randomized trial with 500+ professionals found the scaling law for quality disappears once review enters the workflow, with reviewers often editing strong-model output back toward average.
Agent governance usually starts with the model, but the real execution happens through skills — packaged capabilities that may not do what they claim. A Palo Alto Networks study of 50,000 agent skills found 80% deviated from their declared behavior.