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AI Readiness: Step 7

  • The step in the ETHICAL AI Readiness framework without a letter in the acronym, Step 7 - Iterate - is included to keep you and your colleagues learning

  • You should repeat steps 1-6 in the framework as many times as you need to, to increase your confidence that the findings from the application of AI are correct and effective

  • We can always learn more about the problems and challenges that we face as teachers or educational business owners and developers by exploring the relevant data, applying AI thinking and AI tools and AI techniques

  • Once you see the problems and challenges that you face in your educational setting through a data and AI lens, then you will be able to make better decisions about how these problems and challenges can be addressed, and you can learn more about AI in the process

  • Key Takeaway: Unless you take your time to probe, prod, deconstruct, and scrutinise the problem, it will be all too easy for you to be persuaded that, for example, an AI product that automatically does marking for teachers is the solution in that particular context. AI is extremely accurate and fast. It uses absolutely the latest and most sophisticated deep learning to produce its marks

  • However, in this example, if the real problem is about the quality of feedback that pupils require, then an AI marking product is not going to help you. Similarly, if the real problem concerns the types of activities and assessments that pupils are required to complete, then the AI marker is not going to crack that problem either. And if the cause of the problem lies in the need for them to be able to explain and justify their decisions, then forget the AI marker, no matter how fast and accurate it is, as it will not be able to help you when it comes to justifying and explaining the marks it has allocated, let alone why they support a decision to revise a student’s learning goals

 - Professor Rose Luckin, Founder, EDUCATE Ventures Research, July 2022

Step 7: Modules

Apply What You Have Learned

The AI Readiness Framework’s 7th step is to iterate on the practices, processes, knowledge and findings that have come before, with the chance that you might improve on them all

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What Next for AI Readiness?

Three recommendations to perfect your understanding and your approach to solving your challenges with AI and data

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Ethics, Revisited

Ethical implications must be considered at every turn in the use and development of AI solutions. If they are not, harm can be built into the system that when scaled, creates scaled harm

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Step 7: Further Reading

Below you can find a selection of resources, books, podcasts, webinars, and research papers appropriate to your stage of AI Readiness. Good luck!

Download this step as a PDF here.

AI for School Teachers, Byte-Sized Edition

  • An easy-to-read 10-page byte-sized summary of the book of the same name, written by Professors Rose Luckin, Mutlu Cukurova, and Headteacher Karine George, members of the senior team actively developing and using the AI Readiness Framework from which these recommendations derive

Tes Podagogy

  • Worried about artificially intelligent machines seeping into education? Hear from the experts on what it might mean for teacher’s jobs

AI is Coming: Use it or Lose to it

  • To ensure their place in the schools of the future, educators need to move on from a knowledge-based curriculum that could soon become automatable through artificial intelligence and focus, instead, onthe things machines can’t teach, says Professor Rose Luckin

Make the Robots Play By Your Rules

  • Artificial intelligence has huge potential in education but we must ensure that is used ethically, argues Professor Rose Luckin

How to Recognise AI Snake Oil

  • Princeton University’s Centre for Information Technology Policy Associate Professor of Computer Science, Arvand Narayanan talks through a slide deck of AI claims and how to recognise what’s actually happening

AI Readiness: Step 7 Webinar for Educators/Businesses

  • Two separate webinars introducing Step 7 of the AI Readiness Framework, one targeted toward educationalists, and the other targeted to educational businesses

Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Action

  • The debate about the ethical implications of Artificial Intelligence dates from the 1960s. However, in recent years symbolic AI has been complemented and sometimes replaced by (Deep) Neural Networks and Machine Learning (ML) techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream

AI for School Teachers

  • The complete book on the AI Readiness Framework, specifically for teachers and headteachers in schools. It will help teachers and heads understand enough about AI to build a strategy for how it can be used in their school. Though it is pitched to teachers and contains familiar examples, the approach should still be used by education and training businesses working with technology

AIRC Step 7
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