Gary Ackerman @garyackerman@qoto.org

Generative AI is capturing public interest, driving discussions and seen as a key driver for the next wave of digital transformation. It's fundamentally different from traditional AI. #GenerativeAI #DigitalTransformation

Can machines truly think or merely simulate thought?

Technologies are non-neutral. They influence how we act, interact, and especially how we think. Information itself may be treated neutrally by systems, but its impact on humans is not.

Problems that are complex, irreducible, and have a social dimension, like education, are recognized as wicked problems. Unlike tame problems, their causes aren't clear, they're hard to understand, and solutions are tentative.

Educational planning has historically focused on setting goals & measuring outcomes, often based on standardized tests. This approach, common for tame problems, is applied despite contentious debates about validity.

Unlike engineered tools, language technology don't have a blueprint or goal of optimality. Its evolution is gradual, piecemeal, and non-unilinear, shaped by adaptation and the co-option of existing structures.

School assessment answering the question "Can they create valued work?" seems more valuable than what we have.

Imagine a school assessment system that answers the question: Do students have good work habits?

AI-Induced Bias: Systematic and repeatable errors in an AI system's output that create unfair outcomes, often reflecting biases present in the data the AI was trained on

AI systems are being used for employee surveillance through monitoring emails, tracking online activity, analyzing facial expressions, and even gauging emotions through voice analysis software.

AI-based hiring is no more effective than traditional hiring methods, despite the appearance of efficiency and objectivity provided by AI.

#educators “are obsessed with perpetual evaluation of a very limited range of skills even as they ignore, even discourage, curiosity and explanation.” -Geerat Vermeij Yup that pretty much captures what is wrong with it.

Gerry’s Vetmeij wrote of evolution, “Skeptics harbor legitimate questions and reservations as well as ill informed grievances.” This describes many areas of #science. Difficulties arises what advocates cannot differentiate the two.

Purposeful, meaningful, challenging, engaging are four adjectives I see and hear applied to curriculum we should be designing. I don’t hear them applied by #students often enough. #highschool #HigherEducation #highered

It is always reassuring to get to the section of a research article in which the author discusses limitations in the study. At least #science can still be self-aware and realize articulating limitations demonstrates you know what you are doing. #research #scientists

So, I just went to YouTube to find a Warren Zevon song that I haven't searched in several months. I typed "Warren Zevon" into the search bar, and the song was first on the list. I understand algorithms and coincidence, but it is still *creepy* when this happens.

Dunning–Kruger effect https://t.co/MFeRlVtbza This affects so much #education policy-making.

Still an interesting read:
https://www.scientificamerican.com/blog/beautiful-minds/enough-with-the-learning-styles-already/

A blog post, now with audio:
https://hackscience.education/2018/05/16/three-choices-when-faced-with-technology/

Looking at AI:
https://hackscience.education/2025/04/29/ai-generative-and-traditional/