Jessica Montgomery
Public Policy Annual Lecture, The Bennett Institute
User: Hi ChatGPT, Could you write soliloquy that introduces what a Large Language Model is as spoken by Mercutio?
Machine: Ah, friends, lend me your ears, I prithee, For now I must utter a tale of wonder, Of a creation divine, called the Large Language Model, An oracle, a sorcerer, a wordsmith, yea verily, a master of the quill.
From the depths of this scholarly dominion, A creature of artifice did rise; Twas wrought of ones and zeroes, woven as if by Puck’s own hand, To mimic our thoughts, our voice, our very essence.
A thousand minds, nay, a millionfold, Conjoined in this digital Athenaeum, Words and phrases, like soldiers in battle, Marching to form the verses of our age.
This Large Language Model, a changeling so fair, Hath the power to bring forth wisdom, To transmute our queries, our curiosities, Into answers, clear as a midsummer’s day.
Yet, beware, my companions, for magic hath its limits, Not unlike the mortal bounds of we who dwell in flesh, The Large Language Model hath its strengths, But ’tis not an all-knowing oracle, a god it is not.
As Mercutio, your humble servant, doth stand before thee, I marvel at the art and science that hath brought forth this wondrous creation, This Large Language Model, a testament to man’s yearning, To comprehend the world and make meaning of the great tapestry of existence.
In faith, dear friends, let us embrace the magic and beauty of this digital bard, And mayhaps, by its grace, we shall glean some wisdom, As we wander together, hand in hand, Through this boundless realm of knowledge and wonder.
ChatGPT transcript, 14th April 2023.
Again Univesities are to treat each applicant fairly on the basis of ability and promise, but they are supposed also to admit a socially more representative intake.
There’s no guarantee that the process meets the target.
Onora O’Neill A Question of Trust: Called to Account Reith Lectures 2002 O’Neill (2002)]
Data Science Africa is a bottom up initiative for capacity building in data science, machine learning and AI on the African continent
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Gap between policy (macro) and on ground reality (micro) * Insufficient consideration of local needs and systems. * Lack of effective feedback mechanisms from micro to macro. * Rigid top-down implementation. * Insufficient engagement with end users and stake-holders
Progress so far:
A-Ideas Initiative - Challenge: Aligning high-level AI research with real-world needs. - ai@cam’s Approach: - Fund interdisciplinary projects addressing specific societal challenges. - Brought together 19 Departments across 6 Schools, ensuring diverse perspectives. - Examples: Projects on climate change, mental health, and language equity directly connect macro-level AI capabilities to micro-level societal needs.
Policy Lab
Data: Data Intermediaries and maturity assessments
In its first 18 months of operation, the Initiative has:
Convened over 200 leading data ethics researchers and practitioners;
Funded 7 new research projects tackling knowledge gaps in data trust theory and practice;
Supported 3 real-world data trust pilot projects establishing new data stewardship mechanisms.
Compute: HPC Pioneer Project
Capability: Accelerate Programme for Scientific Discovery
Hopes and Fears Labs
Cross-University Workshops
AI-deas Challenge Development
Overall Strategy
Steering Group
Industry Engagement
book: The Atomic Human
twitter: @lawrennd
The Atomic Human pages cuneiform 337, 360, 390 , Royal Society; machine learning review and 25, 321, 395, O’Neill, Baroness Onora: ‘A question of trust’ lecture series (2002) 352, 363, Gilruth, Bob 190-192, National Advisory Committee on Aeronautics (NACA) 163–168, Horizon scandal 371.
podcast: The Talking Machines
Guardian article on How African can benefit from the data revolution
Guardian article on Data Science Africa