Top Tweets for #EconAI
How to make #CrisisEarlyWarning more impactful? #PREVIEW discussed this & more questions at the interdisciplinary conference of our scientific partner #EconAI @bse_barcelona
🎙 New Project
🔷 Economic AI (ECONAI)
🔶 Economic AI is an AI-powered platform on the BSC that wants to revolutionize cryptocurrency investments and how traders and investors engage with the crypto markets.
🔶 Details: https://t.co/ZzYpxtcz9V
#Crypto #ECONAI #ICOAnnouncement
@wbmosler @StephanieKelton Too bad there isn’t a commercial market for a fact-based #EconAI to confront them with their ignorance since they seem impervious to human intelligence and logic.
So, #EconAI community, be ready, the (sunny) future of AI research is in @VilledeNice! Also, a big thanks to @SPRU @SussexUBusiness @SussexUni for these 5 years - once a SPRUer, always a SPRUer!
"Superhuman science"
This paper explores the potential impact of AI on scientific fields where innovation is about searching big spaces of possibility (e.g. new drugs, materials, architectures to build better AI systems...).
https://t.co/rfQKx5xZ0E
#econai ht @mattsclancy
"The de-democratisation of AI research"
This is another modern classic in #econAI. It uses a synthetic control method to show that the arrival of deep learning has made AI research less democratic (i.e. more dominated by elite firms and universities).
https://t.co/iMthVuVIrq
"Deep learning in science"
This is a modern classic in #econai. They map the adoption of deep learning in science, showing interesting differences between countries.
This is followed by a deep dive on deep learning in health research.
https://t.co/z81L3MOxX6
"Is attention all we need, really?"
Excellent exploration of the implications / risks of the unification of machine learning research brought about by large / foundation models.
https://t.co/q8Qab2h9Wr
#econai
"The evolutionary dynamics of the Artificial Intelligence ecosystem"
This paper shows the value of bringing an evolutionary perspective into the economics of AI. Without it, it is hard to make sense of its trajectory and impacts.
Key points:
https://t.co/7z1VCJHr3a
#econai
"Harms of AI"
Daron Acemoglu describes various channels through which the deployment of AI might harm consumers, workers and democracy. This is generally caused by power imbalances in how AI is developed and deployed, and externalities.
https://t.co/lEWgBONkEa
#econai
“Assigning decision authority between humans and AI systems”
Another nice model of AI adoption in firms, this time considering how to organise decision-making when workers are potentially misaligned, and AI systems potentially fallible.
https://t.co/Kx6VO9DwWx
#econai
"AI adoption and system-wide change"
Fun paper modelling the link between AI adoption and an organisation's structure. It highlights the challenges of realising the benefits of innovations in decision-making even when actors are aligned.
https://t.co/gPXpTVVj8S
#econai
"AI as a general purpose technology: a historical perspective"
Economic historian Nick Crafts compares AI with the technologies underpinning previous industrial revolutions and considers their impact on productivity (& jobs).
https://t.co/za0RsiKGwH
#econai
Is AI a GPT according to patent data?
This paper looks this question using four definitions of AI based on different methods.
The answer is: it depends.
https://t.co/6yeVExN6DX
#econai
Modelling the complex economics of AI (complexly)
This paper presents an agent-based model of AI (data, tech, workers) markets. It finds that industrial structure is not technologically determined but depends on complementary factors & policy. #econai
https://t.co/gR0OCkBYhZ
PS. I tagged the thread as #econai adjacent for three reasons:
1. It illustrates complex dynamics of science that might be transformed by AI: what will be the impact of AlphaFold 2 on all this?
2. There is qualitative evidence of racing dynamics in ML/AI research...
"Racing to the bottom"
Fantastic new paper about the impact of publication races on the quality of (structural biology) research.
Tl;dr: it is negative.
https://t.co/a9k8gYVWXb
#econai adjacent
"Machine learning for medical imaging"
Comprehensive tour of innovation system failures leading to a situation where the "state of the art" is advanced without actual improvements in clinical outcomes.
Co-author @DrVeronikaCH summarises:
https://t.co/5OzdN7qqI5
#econai
🎉🥳🎈Happy to announce that our work with @GaelVaroquaux "Machine learning for medical imaging: methodological failures and recommendations for the future" has been published in Nature Digital Medicine @npjDigitalMed 🎈🥳🎉!
A thread 🧵 1/ https://t.co/JxyJPG5JMb
"Mapping the evolution of AI benchmarks"
AI researchers test their models against benchmark datasets to evaluate and guide progress.
This paper finds 3 broad patterns: continuous improvement, stagnation and ~punctuated equilibria
https://t.co/Qj6SEU34m3
#econai ht @jackclarkSF
"China’s catching-up in AI seen as a co-evolution of corporate and national innovation systems"
This paper explores the interaction between government policy and corporate strategy that is shaping the development of AI & its geopolitics. #econai
https://t.co/ObWCFERqq8 gated 😢
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