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The AI didn’t invent the bias. It just paid attention.
There is a particular kind of discomfort that comes from looking at what an AI system has learned and recognising, in its outputs, something uncomfortably human. Not a glitch. Not a malfunction. Not the robot going rogue. Just a very accurate reflection of the world we gave it to learn from. The algorithm that learned…
Continue Reading The AI didn’t invent the bias. It just paid attention.
Messy data isn’t the problem. It’s the symptom.
Every data problem we’ve ever seen in higher education has one thing in common. Somewhere underneath it – underneath the messy spreadsheets, the unreliable reports, the dashboards nobody trusts, the HESA return that needs three rounds of corrections – there is a governance problem. Not always an obvious one. Not always one that anyone has…
Continue Reading Messy data isn’t the problem. It’s the symptom.
Data-driven. Are you, though?
“Data-driven” has become one of those phrases that organisations put in strategies, say in meetings, and include in job descriptions without anyone stopping to ask what it actually means in practice. It has the comfortable quality of sounding rigorous without committing to anything specific. And that, unfortunately, is usually where the trouble starts. Let’s be…
Learn about my Data Fluency Framework
Find out about how data fluency is a key element in improving how you, your teams and your organisation can make better decisions using data.
Worried about using data with AI?
This handy checklist will help you to assess what safeguards you should use when working with Student Data in AI.