🤖 Artificial Intelligence (AI) Literacy[a]
A crowdsourced[1] guide to the emerging competencies of artificial intelligence.
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The purpose of this document is to outline the facets of AI literacy for students and educators. These are also the emerging competencies we all rely on as we explore and interact with these tools.
The audience are curious educators, teachers and students.
The problem we are solving with this documentation, is How educators and students can leverage Artificial Intelligence (AI) tools as assistants and coaches in the learning and creative process.
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🤖 AI Literacy
Dispositions
Skills
Knowledge
Tools
Ponderings
References and Readings
Dispositions
💡What are the mindsets and dispositions critical to effective use of AI assistive technology?
Critical thinking / healthy scepticism
Recognise that output from AI is not necessarily totally accurate or complete
Caution
AI technologies have large elements of open source development. Tools, sites and uses of AI are appearing regularly. Some of these could be scams, used to steal data or for other undesirable practices. A cautious approach to sharing data, requests for payment needs to be used.
Patience
Competent use of AI tools develops through practice.
Resilience
Use of creative resilience to adjust an approach, respond to feedback and persist.
Authenticity
Understanding the ‘intent’ behind posts and content and how to present authentically.
Process as product
Have an increasing awareness and perspective that the process of creating is part of the outcome.
Creative thinking
AI can produce divergent and, at times, unexpected output. It has the capacity to generate many different kinds of ideas, manipulate ideas in unusual ways and make unconventional connections. This will often demand approaches that involve innovative problem-solving techniques.
Revision
AI evolves rapidly, therefore, constant revision of new nuances and features (as well as new harms) must take place.
Critical assessment
There are appropriate and less appropriate AI applications in the classroom. Critical assessment should judge (if or) where AI is applicable.
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Skills
💡What skills (existing, emerging, new) are needed to fulfil the potential of an AI assistive technology?
Attribution
A new type of citation and attribution is required that displays the use of AI assistance.
Prompt craft
AI requires effective prompts to produce a desired output.
Prompt engineering / Drafting / Iteration
AI output often requires fine-tuning, expansion of ideas and/or greater precision in prompts to get a desired outcome. Editing and adapting prompts to alter the outcomes.
Reading comprehension and analysis
To be able to critically analyse written text and deconstruct meaning and information. This is crucial to consider the accuracy of the information created.
Goal setting
Having a clear intention for what you are attempting to create is helpful, but not always essential.
Use determination
Being able to determine when to utilise AI assistance, when not to and determine which part of learning or the creative process needs AI assistance.
Discipline
To understand the significance of learning skills even though AI tools might be able to perform tasks easily. Eg basic mathematics, basic writing, basic reading, basic drawing; as these are necessary to develop physical and cognitive skills necessary to build on further in life.
Knowledge
💡What knowledge and understanding of AI, machine learning or LLMs contribute to higher levels of competency?
ALPHA, BETA software development phases
Appreciating that ChatGPT and other tools are often in research or BETA stages of development and will likely change in a variety of ways including their interface, how they work, etc.
AI Foundations
Elaboration needed
Knowledge of what is actually being output from the AI tool - knowledge-elements or statistically optimal word-pairings
Ethics & Social Impact
That technology is not neutral[2]. Bias detection, societal representation
Algorithms
Elaboration needed
Data literacy
Information interrogation and sensemaking; awareness of data generation and platform-ization
Data privacy/sharing
Any data shared online while using AI tools is owned by the tool provider. This includes the data input and the output provided
AI tool limitations
Knowing that the AI tool may have been trained with data from a specific time period.
AI and data governance
(for educators mostly) what are your responsibilities in relation to regulation. Who has access to data, how do you check and take responsibility for data quality,)
Ownership
What it means to create something and based on whose labour something is created. (e.g. the current ownership challenges of training larger AI models on public but not un-licensed data-points).
Tools
💡What tools, methods and technologies are relevant and accessible to students and teachers? (not just AI tools)
Search, Image + Art generators
Keyword online search techniques (example needed)
Bing, Perplexity
Text Generators
Autocomplete in GMail or Docs, GPT-3, Github Co-pilot, OpenAI, Codex, Canva Magic Write, Copy.AI, Wordtune, PEER (German)
Text Editing
Grammarly, Spellchecks, Quillbot, DeepL Write
Questioning
Socratic questioning routines, Conker.ai
Curation
Digital curation methods (example needed)
Chatbots
ChatGPT; Claude; Bard
Text to image
DALLE-2, Midjourney, Stable Diffusion. Text to Image - Canva, Adobe Express
Image editors
LensAI, cleanup.pictures
Video editors
RunwayML, Capcut
Voice editors
Voicemod
Video, Audio capture, transcription, editing
Descript, Microsoft Word (365) built-in transcription tools[3].
Otter.ai, Elevenlabs
Others
PhotoMath (answering math-assignments), Socratic
AI Tool Curators and Aggregators
gpte.ai, Poe
Ponderings
* How different is this literacy to any other tech or media related literacy?
* WIll some of the skills become swept aside by better technology?
* Are the mindsets/dispositions of educators and students different when using AI tools?
* How can AI be helped to tackle the bias and historical challenges contained in the data/information it has learned from?
* How can we move from the creators of learning pathways and content towards facilitating students in the design of their own pathways and related content?
References and Readings
* K-12 AI curricula: a mapping of government-endorsed AI curricula
* Google AI Principles
* How to delete your account | OpenAI Help Center
* How to... use AI to generate ideas - by Ethan Mollick
* Introduction to Artificial Intelligence (lesson for 8th grade students created by HS students)
* Intro to Artificial Intelligence - GWC - Capstone Project - Group 7.pptx
* Promises of AI in Education (SURF) Promises of AI in Education | SURF.nl (p.20-25 specifically discusses GPT-3 and PhotoMath)
* Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators (European Commission) Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators - Publications Office of the EU (p.28 'emerging competences for ethical use of AI and data' is relevant for educators)
* Platformisation Platform Pedagogies –Toward a Research Agenda
* “the technical and economic features of platforms leave imprints on both the data processes they modulate (Helmond, 2015) and the social practices of their users (Gillespie, 2018), a phenomenon known as “platformization” (Poell, Nieborg, & van Dijck, 2019). In education, platformization is evident in the tendency for platforms to shape instructional and learning practices.” (Datafication Meets Platformization: Materializing Data Processes in Teaching and Learning)
* Microsoft Introduction to Prompt Engineering.
* AI Padlet : Impact on T&L https://padlet.com/DarenWhite/jt3xhxs25xipojxa
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[1] Built from the generous contributions of the education community.
[2] https://plato.stanford.edu/entries/technology/#NeutVersMoraAgen
[3] I used Microsoft Word (365) to transcribe the interviews I had with my participants in a recent study. It was more accurate than Otter.AI. ~ Juliana Peloche
[a]Hi - I’ve added a few ideas. This is great by the way! Darren Coxon