10 épisodes

Every week, we discuss a paper relevant to AI ethics. We try to explain the key ideas, to highlights the limits of the paper and to suggest further research questions related to the paper.

Robustly Beneficial Podcast Lê-nguyen Hoang

    • Technologies

Every week, we discuss a paper relevant to AI ethics. We try to explain the key ideas, to highlights the limits of the paper and to suggest further research questions related to the paper.

    The Mathematical Ethics of Clinical Trials #RB12

    The Mathematical Ethics of Clinical Trials #RB12

    We discuss the exploration-exploitation dilemma and near-optimal solutions found by mathematicians.

    Some relevant ressources include:

    Bayesian Adaptive Methods for Clinical Trials. CRC Press. Berry, Carlin, Lee & Muller (2010).
    https://www.crcpress.com/Bayesian-Adaptive-Methods-for-Clinical-Trials/Berry-Carlin-Lee-Muller/p/book/9781439825488

    Bayesian adaptive clinical trials: a dream for statisticians only? Statistics in Medicine. Chrevret (2011).
    https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.4363

    Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges. Statistical Science. Villar, Bowden & Wason (2015).
    "Across this literature, the use of bandit models to optimally design clinical trials became a typical motivating application, yet little of the resulting theory has ever been used in the actual design and analysis of clinical trials."
    https://arxiv.org/pdf/1507.08025.pdf

    Machine learning applications in drug development. Computational and Structural Biotechnology Journal. Réda, Kaufmann & Delahaye-Duriez (2019).
    https://www.sciencedirect.com/science/article/pii/S2001037019303988

    Rethinking the Gold Standard With Multi-armed Bandits: Machine Learning Allocation Algorithms for Experiments. Kaibel & Bieman (2019)
    https://journals.sagepub.com/doi/abs/10.1177/1094428119854153

    Cancer specialists in disagreement about purpose of clinical trials. Journal of the National Cancer Institute (2012).
    https://www.eurekalert.org/pub_releases/2002-12/jotn-csi121202.php

    WHO launches global megatrial of the four most promising coronavirus treatments. Science Mag. Kupferschmidt & Cohen (2020).
    https://www.sciencemag.org/news/2020/03/who-launches-global-megatrial-four-most-promising-coronavirus-treatments

    • 37 min
    User-driven ethics #RB9

    User-driven ethics #RB9

    WeBuildAI: Participatory Framework for Algorithmic Governance. LKKKY+19
    https://www.cs.cmu.edu/~akahng/papers/webuildai.pdf

    Find out more on the RB Wiki:
    https://robustlybeneficial.org/wiki/index.php?title=Social_choice
    https://robustlybeneficial.org/wiki/index.php?title=Interpretability

    • 51 min
    A roadmap towards robustly beneficial AIs #RB8

    A roadmap towards robustly beneficial AIs #RB8

    A Roadmap for Robust End-to-End Alignment. Lê Nguyên Hoang 18.
    https://arxiv.org/pdf/1809.01036

    Find out more on the Robustly Beneficial Wiki:
    https://robustlybeneficial.org/wiki/index.php?title=ABCDE_roadmap

    Next week's paper is WeBuildAI: Participatory Framework for Algorithmic
    Governance. PACMHCI. LKKKY+19.
    https://www.cs.cmu.edu/~akahng/papers/webuildai.pdf

    • 50 min
    Reinforcement learning #RB7

    Reinforcement learning #RB7

    Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model.
    SAHSS+19.
    https://arxiv.org/abs/1911.08265

    Find out more on the Robustly Beneficial Wiki:
    https://robustlybeneficial.org/wiki/index.php?title=Reinforcement_learning

    Next week's paper is:
    A Roadmap for Robust End-to-End Alignment. LN Hoang 18.
    https://arxiv.org/abs/1809.01036

    • 46 min
    Can autonomous weapons be safe? #RB6

    Can autonomous weapons be safe? #RB6

    Intelligent Autonomous Things on the Battlefield. AI for the Internet of Everything. A Kott and E Stump 19.
    https://arxiv.org/ftp/arxiv/papers/1902/1902.10086.pdf

    Slaughterbots. Future of life Institute 17.
    https://www.youtube.com/watch?v=HipTO_7mUOw

    The Future of War, and How It Affects YOU (Multi-Domain Operations). Smarter Every Day 211.
    https://www.youtube.com/watch?v=qOTYgcdNrXE

    Find out more on the Robustly Beneficial Wiki:
    https://robustlybeneficial.org/wiki/index.php?title=Robustly_beneficial
    https://robustlybeneficial.org/wiki/index.php?title=Robust_statistics

    Next week's paper is about MuZero.
    Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model. SAHSS+20.
    https://arxiv.org/abs/1911.08265

    • 37 min
    Preference learning from comparisons #RB5

    Preference learning from comparisons #RB5

    Preference learning from comparisons. Lucas Maystre 2018. EPFL PhD Thesis.
    https://infoscience.epfl.ch/record/255399/files/EPFL_TH8637.pdf

    Find out more on our Wiki:
    https://robustlybeneficial.org/wiki/index.php?title=Volition
    https://robustlybeneficial.org/wiki/index.php?title=Preference_learning_from_comparisons

    • 39 min

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