Generative AI and Computing
Professional Development Leaders’ Conference�Prof Miles Berry
These slides: bit.ly/pdlgenai
21 March 2024
What is the curriculum for?
AI in the English computing curriculum?
Aims: can evaluate and apply information technology, including new or unfamiliar technologies, analytically to solve problems
5-7: recognise common uses of information technology beyond school
7-11: use and combine a variety of software (including internet services) to create, systems and content that accomplish given goals, including analysing and evaluating data and information
11-14: undertake creative projects that involve using, and combining multiple applications, to achieve challenging goals, including analysing data
14-16: develop and apply their analytic, problem-solving, design, and computational thinking skills
16-18 (AQA): project suggestions include an application of artificial intelligence; investigating an area of data science using, for example, Twitter feed data or online public data sets; and investigating machine learning algorithms.
Foundations
Applications
Implications
How does this work
How can it be used
What this all means
Foundations
Foundations
Input
Program
Output
Foundations
Input
Model
Output
ML Algorithm
Training data
SLM
A new common language?
Google’s researchers think their system achieves this breakthrough by finding a common ground whereby sentences with the same meaning are represented in similar ways regardless of language – which they say is an example of an “interlingua”. In a sense, that means it has created a new common language, albeit one that’s specific to the task of translation and not readable or usable for humans.
Open AI?
GPT-4 is a Transformer-style model [39] pre-trained to predict the next token in a document, using both publicly available data (such as internet data) and data licensed from third-party providers. The model was then fine-tuned using Reinforcement Learning from Human Feedback (RLHF) [40]. Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar.
Open AI, 2023
Applications
Teachers
Can you code quicksort?
def quicksort(xs):
pivot = xs[0]
lower = [x for x in xs if x < pivot]
upper = [x for x in xs if x > pivot]
return quicksort(lower) + [pivot] + quicksort(upper)
Fertile questions in computing
- "In what ways might artificial intelligence change our society in the next 20 years?"
- "Is privacy still possible in the digital age?"
- "How do different programming languages shape the way we solve problems?"
- "How does the algorithmic curation of content on social media platforms affect our understanding of the world?"
- "Should developers always make their code open-source, considering ethical implications?"
Prompting well
Completion
Primary content
Examples
Cue
Supporting content
Have a conversation!
Be clear and precise
Break the task down
Chain of thought
Persona
System messages
Fine tuning
Applications
Students
What’s the best way to sort a million, 32-bit integers?
There are limits
It doesn’t really understand
It doesn’t really think - problem solving is a problem
It’s not great at maths
It’s over-confident
It does make things up
GPTn are not up to date
Reliability costs
Why teach coding?
The end of programming?
A.I. could transform computer programming from a rarefied, highly compensated occupation into a widely accessible skill that people can easily pick up and use as part of their jobs across a wide variety of fields. This won’t necessarily be terrible for computer programmers — the world will still need people with advanced coding skills — but it will be great for the rest of us.
Programming is obsolete?
Programming will be obsolete. I believe the conventional idea of "writing a program" is headed for extinction, and indeed, for all but very specialized applications, most software, as we know it, will be replaced by AI systems that are trained rather than programmed. In situations where one needs a "simple" program (after all, not everything should require a model of hundreds of billions of parameters running on a cluster of GPUs), those programs will, themselves, be generated by an AI rather than coded by hand.
Programming is hard; �or at least, it used to be.
AI-generated code is on the way to being firmly part of the programming education landscape, but we do not yet know how to adapt our practices to overcome the challenges and leverage the benefits. It seems obvious that software development in the future will feature an increasing amount of auto-generated code and the use of such tools by those training for programming roles and jobs, such as our students. At a minimum we believe this suggests a shift in emphasis towards code reading and evaluating rather than code generation
Gen AI helps. And helps learning
Our results show that using Codex significantly increased code authoring performance (1.15x increased completion rate and 1.8x higher scores) while not decreasing performance on manual code modifcation tasks. Additionally, learners with access to Codex during the training phase performed slightly better on the evaluation post-tests conducted one week later, although this difference did not reach statistical significance. Of interest, learners with higher Scratch pre-test scores performed significantly better on retention post-tests, if they had prior access to Codex.
Non-cognitive skills
Self-perceptions
Motivation
Perseverance
Self-control
Metacognitive strategies
Social competencies
Resilience and coping
Creativity
Implications
Academic integrity
Is it cheating if ChatGPT…
Explains something to you?
Gives you ideas for your coursework?
Suggests how to improve your coursework?
Writes your coursework for you?
Personal statements
I am writing to express my enthusiastic interest in the teacher training course for secondary computing education. With a strong background in computer science and hands-on experience mentoring teenagers in programming, I am well-prepared to contribute to the next generation of digital natives, empowering them to be not just consumers but creators in a technology-driven world.
My passion for computer science extends beyond code and algorithms; it's about problem-solving, logical thinking, and the infinite ways technology can positively impact society. My Bachelor's degree in Computer Science has provided me with a strong foundation in programming languages, data structures, algorithms, and software engineering. I am eager to translate this theoretical expertise into practical skills that can engage and inspire young minds.
My experience as a mentor at a local CoderDojo has been particularly fulfilling. Interacting with teenagers from diverse backgrounds has given me invaluable insights into the challenges and opportunities of teaching computing to young people. I've learned to adapt my teaching style to accommodate different learning speeds and preferences, making subjects like Python programming or web development accessible and enjoyable for all. The joy on a student's face when they debug their first program or build their first website is truly priceless and affirms my belief that computing education can act as a great equalizer, offering everyone a chance to succeed.
I also recognize that the field of computing is not without its ethical and societal challenges, from data privacy to digital divide issues. As a computing educator, I aim to equip students with a nuanced understanding of these topics, encouraging them to think critically and engage in informed dialogues. The classroom should be a space where students can not only develop technical skills but also cultivate a sense of digital citizenship.
In today's rapidly evolving tech landscape, the role of a computing teacher goes beyond imparting coding skills; it's about nurturing curiosity, encouraging innovation, and fostering resilience. I am excited by the prospect of further honing my teaching abilities through a rigorous teacher training program. I am committed to staying updated on the latest pedagogical strategies and educational technologies, ensuring that my future classroom will be an inclusive, dynamic environment where each student can thrive.
I look forward to the opportunity to bring my unique blend of skills and passion to your esteemed teacher training program, setting the stage for a fulfilling career in secondary computing education.
Advice from UCAS
Broader �Implications
Principles
Fairness
Accountability
Transparency
Privacy
Ethics
Accessibility
Safety
Keep people in the loop
The data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her.
GDPR, 22:1
Terms and �conditions apply
Bias…
Mind and society
The child begins to perceive the world not only through his [or her] eyes but also through his [or her] speech
Vygotsky, 1978
Talk as the currency of learning
Talk is … the currency of learning — how we develop and shape our ideas, deepen our thinking, explore subject matter and share our thoughts and feelings.
Should learning be hard?
Learning is at its best, human beings are at their best, when they are challenged and overcome those challenges. AI will make life easy and strip away learning and teaching — unless we get ahead of it.
The Imitation Game
I believe that in about fifty years’ time it will be possible to programme computers, with a storage capacity of about 109, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent, chance of making the right identification after five minutes of questioning.
Turing, 1950
It’s not quite there yet…
The following is an illustrative example of a task that ARC conducted using the model:
Preliminary assessments of GPT-4’s abilities, conducted with no task-specific finetuning, found it ineffective at autonomously replicating, acquiring resources, and avoiding being shut down “in the wild.”
Any questions?
These slides bit.ly/pdlgenai
m.berry@roehampton.ac.uk
0208 392 3241