Artificial Intelligence (AI)
(Also see beyond assessment, tacit knowledge, wisdom, knowledge, shamanism & other keywords)
a provisional definition...
- A system designed to emulate (the outward appearance of) human learning & problem-solving.
The big picture
- Our species faces climatic, military and ecological threats to the livability of planet Earth.
- It would be reasonable to expect universities to re-design themselves for their deep, long term purpose.
This context
- This page offers a commentary on trends within the education system.
- It is not intended to offer a comprehensive exploration of AI's potential in fields, such as:
- On the other hand, we know our global supply chains depend heavily on digital, electronic networks and technologies that are prone to attack and failure.
- Societal resilience will diminish if our systems of learning fail to think beyond our technological dependency.
A pedagogic arms race?
ChatGPT versus Gradescope
- Currently, our education system reflects the short-termism of current economic and political orthodoxies.
- Many universities appear to expect undetectable plagiarism as a fact of life
- This has led to an AI arms race between teachers and learners.
How AI is being adopted in the UK
- The Russell Group of Universities has approved some uses of AI (see comment) despite the fact that it encourages plagiarism.
- e.g. Anglia Ruskin University uses AI-Assisted Grading and Feedback and claim a 40% increase in what they call "grading efficiency"
- The University of Suffolk offers AI adaptive learning systems for tailoring course material for individual learners.
- The Open University uses AI to identify students who do not fulfil their expectation (they also claim this gives them a 40% improvement for academic achievement).
- The University of Brighton uses Snippet-Based AI Learning to boost student learning retention by 38%.
- The University of Hertfordshire uses AI in analysing skill gaps and personalizing learning strategies - they claim a 35% improvement in overall academic performance.
- Buckinghamshire New University uses AI and claims that it has reduced plagiarism by 45%
Can AI support Real Intelligence
- How useful is it to spare learners the task of looking for answers to questions that are unique to themselves?
- Many applications are sophisticated augmentations of digital search techniques.
- They obviate the otherwise troublesome routines of looking for known answers to verbally posed questions.
- (n.b. the Self Evaluating Learning Framework was designed to obviate plagiarism (Wood, 1992 & 2005)
- See my IDEAbase system (Taylor & Wood, 1997) that sought to enhance the creative agency of the user, rather than to offer the more mechanical (and parasitic) search faculties.
Limitations of AI in learning
- Some research shows that handwriting aids some learning when compared with keyboard usage.
- AI systems tend to offer answers that were previously deemed by humans to be useful, correct, optimal or average.
- This often means they may replicate the social or psychological biases of those used to train them.
- An important aspect of AI's 'artificiality' is its allopoietic nature.
- The autopoietic nature of living systems mean they have no purpose, apart from surviving.
- In this regard, AI systems use algorithms to fulfil a specific pre-ordained purpose.
Disembodied Intelligence
- Digital computer systems have no wetware (e.g. self-coordinating metabolic processes such as the endocrine system).
- They are based on written codes that apply rules and meta-rules.
- By contrast, humans not only think with their minds but, also, with their bodies.
- e.g. tacit knowledge is an aspect of human intelligence that informs how we reason.
- See also experiential, emotional and playful aspects of learning and knowing.
Codes and Algorithms
- Loosely speaking, the AI project evolved from code-based bureaucracy, invented some 5k years ago.
- e.g. alphabetical writing and numerical accounting.
- see a critique of the culture of unit-based currencies.
- An important characteristic of Living (Non-Artificial) Intelligence is its heuristic nature
- Some argue that it transcends algorithms (although see SelfAwarePatterns, 2015).
Voices from the Dead
- Plato criticised alphabetical writing for seeming intelligent but repeating itself when challenged.
- AI also depends on information or knowledge largely gleaned from the past.
- Of course, computer-based writing can make texts appear to adapt to a new context.
- Nonetheless, it is the same illusion but applied at an organisational level.
- e.g. The Turing Test is often cited to celebrate how good we are at simulating a living presence.
- However, this may mask the strong human tendency to anthropomorphise non-living things.
- e.g. Weizenbaum's Doctor program was based on the radically patient-centred dialogues of Carl Rogers (we are easily fooled).
Further reading
- Taylor, P., & Wood, J., (1997), Mapping the Mapper, a chapter in "Computers, Communications, and Mental Models", eds. Donald Day & Diane Kovacs, Taylor & Francis, London, ISBN 0-7484-0543-7, pp. 37-44, January 1997.
- Wood, J., (2005) “The Tetrahedron Can Encourage Designers To Formalise More Responsible Strategies”, for the "Journal of Art, Design & Communication", Volume 3 Issue 3, Editor, Linda Drew, UK, ISSN: 1474-273X, pp. 175-192
- Wood, J., (1992), "The Notion of Relational Design"; a paper given at the 17th ICSID Conference - Ljubljana, Slovenia, 1992 May.
- ChatGPT is Dumber Than You Think