Is it possible for engineers and humans to advance intelligence 1) to progress safe affordable homes for families 2) better nutrition for all; 3) better health for all; 4) smarter livelihood education; 5) cultural reust for women as much as men 6) better access of water for all; 7 more efficient and sustainable energy for all; 8 better opportunities for youth to generart? Of course it is but as we look around the world can we help humans everywhere that these intelligent systems are not yet being scaled.?. .
AIworld: Can we data map & celebrate places where education wants youth and tech to design healthy, wealthy and joyful jobs : Taiwan, West Coast USA, India, UK, Singapore/HK, UAE, Korea, Japan, Nordica, Canada France Germany

Probable First 10 priorities of 25X energy efficient supercomputers
  • India Billion peoples basic ai health system & universal finance id
  • Agentic AI transformation womens education 9 to 15
  • Startup open ai ecosystem bridging hundreds of first mile agri and arts/garments etc startups with nations top 10 industries (Elon)
    UK-Valley Alphafold biotech segment leaps include tropical diseases as well as worldwide cancer data
  • Translation of all mother tongues to everyone codes ai via top 2 language llms and decolonial ai geonomic maps
  • Doudna Deepest continent scaled maths problems starting with energy and health transmission
  • First follower humanoid digital twins- eg community safety jobs nobody wants
  • Open profession AI startups
  • Colossus space ai including drone & cable ai
  • Chat+inference+physical ai everywhere self driving cars' "road of things AI"
  • Taiwan AI Digital twin ai factories etc- from Asia to West
  • Earth 2.0 & all deep global data others dont want to first
  • HUmanoids on streets ai
    Japan AI 5 asian supercity benchmark 5 or more western capitals including green model for half of countries with next to no critical minerals
  • Transgeneration Mapping (beyond multilateral relocation of education for millennial generation- eg united mayors ai)
  • HK and diaspora chinese: Digital twin university health colleges
  • Neuroscience etc Mapping start up ecosystem bridging cultures of 10 + regional nations and superport value chains
  • nft and womens metagames ai - eg beingai.org
  • UAE Water ai and Parallel geo-ai system but for middle east primarily desert superports and 360 degree trade maps sustainability
  • France - nuclear datacentre ai micro open ai and top 10 eu continent industries>
  • Sports AI owned by youth- end bad media and bring eg swiss into open euro models
  • Open history- culture ai
  • 25 years of knowledge city ai uniting nordia elearning & human capital- livelihoods new to millennils
  • PLus one
    Help welcomed ongoing intelligence Case Search - source Nvidia top 100 partners in 21st C accelerated computing - alphabet olf engineering inteligence - AI, BioI, Trillion$CoroprateI, DiscoveryI, EnergyI, FinananceI, GovI, HealthI, Icubed : 1) your real 1; 2 your digital 1; 3 your brain body and communal wellbeing support from agentic ai

    Tuesday, January 30, 2024

     MEASURING DEVELOPMENT 2024- AI The Next Generation


    May 2, 2024


    Washington, DC | World Bank I Building, Room 2-220


    1:50 PM

    Research Session II | AI-Informed Safety and Algorithmic Bias

    https://drive.google.com/file/d/1XtKxfij3fYA3wHV_Gt0fJSktPRqgmujM/view?pli=1

    Chair: Charles Mberi (African Institute of Mathematical Sciences (AIMS))

    Carina Ines Hausladen (ETH Zürich) | Using Controlled Image Synthesis to Measure Social Bias in Vision-language

    Models

    Sung Hyun (SK) Kwon (University of Maryland) | Please Take a Second Look: Improving Labeling Quality for Toxic

    Content Using Nudges

    Daniel Nkemelu (Georgia Institute of Technology) | Hate Speech Detection in Limited Data Contexts Using

    Synthetic Data Generation

    Philipp Zimmer, Samuel Fraiberger (World Bank) | Detecting and Reducing Harmful Online Content at Scale Using

    Large Language Models


    2:50 PM Lightning Talks | Transparency and Accountability in AI Design


    Katie Wetstone (Driven Data) | Deon: An Ethics Checklist for Data Science


    Taylor Lynn Curtis (MIT) | Document Before You Deploy: A Proposal for Accountability in Generative AI Decision-

    Making


    3:05 PM Coffee

    3:20 PM

    Research Session III | LLM-enabled Behavioral Insights

    Chair: Vice minister Jessica Niño (Ministry of Development and Social Inclusion, Republic of Peru)

    Hong-Yi TuYe (MIT Sloan) | Early Experimental Evidence on the Behavioral Dynamics of Prompt Engineering

    Rem Koning (Harvard Business School) | The Uneven Impact of Generative AI on Entrepreneurial Performance

    Paloma Bellatin, Mayra Cabrera (Behavioural Insights Team) | Gamified and Narrative Chatbot for Infant Nutrition

    and Perinatal Depression

    Brian Jabarian (University of Chicago) | Critical Thinking and Storytelling


    4:20 PM Lightning Talks | Reasoning with LLMs


    Edmond Dilworth (Stanford University) | ClimateX: Do LLMs Accurately Assess Human Expert Confidence in Climate

    Statements?

    Julian Ashwin (Maastricht University) | Using Large Language Models for Qualitative Analysis can Introduce Serious

    Bias

    Rweyemamu Barongo (Bank of Tanzania) | Strategy for Institutional AI Adoption

    4:35 PM Tools Demo II | Structuring, Verifying, and Extending LLM-informed Research


    Chris Robert (Higher Bar AI, PBC) | Maintaining Human Oversight and Agency in AI-assisted Development Research:

    Instrument Evaluation as Case Study

    Dimitri Stoelinga (Laterite) | LLM Knowledge Hubs: A Transformative Leap for Development Data

    Virginia Ziulu (Independent Evaluation Group-IEG) | Leveraging Text Data and Generative AI in Complex Thematic

    Evaluations

    Michael Norton (World Bank) | Agrifood Data Lab: Using AI to Facilitate Access to Agricultural Data and Use Cases

    Jude Mwenda (Fastagger Inc.) | Democratizing AI


    5:25 PM Closing & Acknowledgements | Sean Luna McAdams (CEGA) & Maria Ruth Jones (World Bank)

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