Timezone: »
Poster
Human-in-the-Loop Interpretability Prior
Isaac Lage · Andrew Ross · Samuel J Gershman · Been Kim · Finale Doshi-Velez
We often desire our models to be interpretable as well as accurate. Prior work on optimizing models for interpretability has relied on easy-to-quantify proxies for interpretability, such as sparsity or the number of operations required. In this work, we optimize for interpretability by directly including humans in the optimization loop. We develop an algorithm that minimizes the number of user studies to find models that are both predictive and interpretable and demonstrate our approach on several data sets. Our human subjects results show trends towards different proxy notions of interpretability on different datasets, which suggests that different proxies are preferred on different tasks.
Author Information
Isaac Lage (Harvard)
Andrew Ross (Harvard University)
Samuel J Gershman (Harvard University)
Been Kim (Google)
Finale Doshi-Velez (Harvard)
Related Events (a corresponding poster, oral, or spotlight)
-
2018 Spotlight: Human-in-the-Loop Interpretability Prior »
Thu. Dec 6th 03:25 -- 03:30 PM Room Room 220 CD
More from the Same Authors
-
2021 : CCNLab: A Benchmarking Framework for Computational Cognitive Neuroscience »
Nikhil Bhattasali · Momchil Tomov · Samuel J Gershman -
2021 Spotlight: Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning »
Kai Wang · Sanket Shah · Haipeng Chen · Andrew Perrault · Finale Doshi-Velez · Milind Tambe -
2021 : Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation »
Ramtin Keramati · Omer Gottesman · Leo Celi · Finale Doshi-Velez · Emma Brunskill -
2022 : An Empirical Analysis of the Advantages of Finite vs.~Infinite Width Bayesian Neural Networks »
Jiayu Yao · Yaniv Yacoby · Beau Coker · Weiwei Pan · Finale Doshi-Velez -
2022 : Feature-Level Synthesis of Human and ML Insights »
Isaac Lage · Sonali Parbhoo · Finale Doshi-Velez -
2022 : What Makes a Good Explanation?: A Unified View of Properties of Interpretable ML »
Varshini Subhash · Zixi Chen · Marton Havasi · Weiwei Pan · Finale Doshi-Velez -
2022 : What Makes a Good Explanation?: A Unified View of Properties of Interpretable ML »
Zixi Chen · Varshini Subhash · Marton Havasi · Weiwei Pan · Finale Doshi-Velez -
2022 : (When) Are Contrastive Explanations of Reinforcement Learning Helpful? »
Sanjana Narayanan · Isaac Lage · Finale Doshi-Velez -
2022 : Leveraging Human Features at Test-Time »
Isaac Lage · Sonali Parbhoo · Finale Doshi-Velez -
2022 : An Empirical Analysis of the Advantages of Finite v.s. Infinite Width Bayesian Neural Networks »
Jiayu Yao · Yaniv Yacoby · Beau Coker · Weiwei Pan · Finale Doshi-Velez -
2023 Poster: Successor-Predecessor Intrinsic Exploration »
Changmin Yu · Neil Burgess · Samuel J Gershman · Maneesh Sahani -
2022 : Closing Remarks »
Samuel J Gershman -
2022 Workshop: Information-Theoretic Principles in Cognitive Systems »
Noga Zaslavsky · Mycal Tucker · Sarah Marzen · Irina Higgins · Stephanie Palmer · Samuel J Gershman -
2022 : Panel Discussion: Opportunities and Challenges »
Kenneth Norman · Janice Chen · Samuel J Gershman · Albert Gu · Sepp Hochreiter · Ida Momennejad · Hava Siegelmann · Sainbayar Sukhbaatar -
2022 : What Makes a Good Explanation?: A Unified View of Properties of Interpretable ML »
Varshini Subhash · Zixi Chen · Marton Havasi · Weiwei Pan · Finale Doshi-Velez -
2022 Poster: Addressing Leakage in Concept Bottleneck Models »
Marton Havasi · Sonali Parbhoo · Finale Doshi-Velez -
2022 Poster: Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare »
Shengpu Tang · Maggie Makar · Michael Sjoding · Finale Doshi-Velez · Jenna Wiens -
2021 : Retrospective Panel »
Sergey Levine · Nando de Freitas · Emma Brunskill · Finale Doshi-Velez · Nan Jiang · Rishabh Agarwal -
2021 : LAF | Panel discussion »
Aaron Snoswell · Jake Goldenfein · Finale Doshi-Velez · Evi Micha · Ivana Dusparic · Jonathan Stray -
2021 : LAF | The Role of Explanation in RL Legitimacy, Accountability, and Feedback »
Finale Doshi-Velez -
2021 : Invited talk #2: Finale Doshi-Velez »
Finale Doshi-Velez -
2021 : Interpretability of Machine Learning in Computer Systems: Analyzing a Caching Model »
Leon Sixt · Evan Liu · Marie Pellat · James Wexler · Milad Hashemi · Been Kim · Martin Maas -
2021 Poster: Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning »
Kai Wang · Sanket Shah · Haipeng Chen · Andrew Perrault · Finale Doshi-Velez · Milind Tambe -
2020 : Batch RL Models Built for Validation »
Finale Doshi-Velez -
2020 : Panel »
Emma Brunskill · Nan Jiang · Nando de Freitas · Finale Doshi-Velez · Sergey Levine · John Langford · Lihong Li · George Tucker · Rishabh Agarwal · Aviral Kumar -
2020 : Q & A and Panel Session with Tom Mitchell, Jenn Wortman Vaughan, Sanjoy Dasgupta, and Finale Doshi-Velez »
Tom Mitchell · Jennifer Wortman Vaughan · Sanjoy Dasgupta · Finale Doshi-Velez · Zachary Lipton -
2020 Workshop: I Can’t Believe It’s Not Better! Bridging the gap between theory and empiricism in probabilistic machine learning »
Jessica Forde · Francisco Ruiz · Melanie Fernandez Pradier · Aaron Schein · Finale Doshi-Velez · Isabel Valera · David Blei · Hanna Wallach -
2020 Poster: Debugging Tests for Model Explanations »
Julius Adebayo · Michael Muelly · Ilaria Liccardi · Been Kim -
2020 Poster: Incorporating Interpretable Output Constraints in Bayesian Neural Networks »
Wanqian Yang · Lars Lorch · Moritz Graule · Himabindu Lakkaraju · Finale Doshi-Velez -
2020 Spotlight: Incorporating Interpretable Output Constraints in Bayesian Neural Networks »
Wanqian Yang · Lars Lorch · Moritz Graule · Himabindu Lakkaraju · Finale Doshi-Velez -
2020 Poster: On Completeness-aware Concept-Based Explanations in Deep Neural Networks »
Chih-Kuan Yeh · Been Kim · Sercan Arik · Chun-Liang Li · Tomas Pfister · Pradeep Ravikumar -
2020 Poster: Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs »
Jianzhun Du · Joseph Futoma · Finale Doshi-Velez -
2020 : Discussion Panel: Hugo Larochelle, Finale Doshi-Velez, Devi Parikh, Marc Deisenroth, Julien Mairal, Katja Hofmann, Phillip Isola, and Michael Bowling »
Hugo Larochelle · Finale Doshi-Velez · Marc Deisenroth · Devi Parikh · Julien Mairal · Katja Hofmann · Phillip Isola · Michael Bowling -
2019 : Panel - The Role of Communication at Large: Aparna Lakshmiratan, Jason Yosinski, Been Kim, Surya Ganguli, Finale Doshi-Velez »
Aparna Lakshmiratan · Finale Doshi-Velez · Surya Ganguli · Zachary Lipton · Michela Paganini · Anima Anandkumar · Jason Yosinski -
2019 : Invited talk #4 »
Finale Doshi-Velez -
2019 : Finale Doshi-Velez: Combining Statistical methods with Human Input for Evaluation and Optimization in Batch Settings »
Finale Doshi-Velez -
2019 : Poster session »
Sebastian Farquhar · Erik Daxberger · Andreas Look · Matt Benatan · Ruiyi Zhang · Marton Havasi · Fredrik Gustafsson · James A Brofos · Nabeel Seedat · Micha Livne · Ivan Ustyuzhaninov · Adam Cobb · Felix D McGregor · Patrick McClure · Tim R. Davidson · Gaurush Hiranandani · Sanjeev Arora · Masha Itkina · Didrik Nielsen · William Harvey · Matias Valdenegro-Toro · Stefano Peluchetti · Riccardo Moriconi · Tianyu Cui · Vaclav Smidl · Taylan Cemgil · Jack Fitzsimons · He Zhao · · mariana vargas vieyra · Apratim Bhattacharyya · Rahul Sharma · Geoffroy Dubourg-Felonneau · Jonathan Warrell · Slava Voloshynovskiy · Mihaela Rosca · Jiaming Song · Andrew Ross · Homa Fashandi · Ruiqi Gao · Hooshmand Shokri Razaghi · Joshua Chang · Zhenzhong Xiao · Vanessa Boehm · Giorgio Giannone · Ranganath Krishnan · Joe Davison · Arsenii Ashukha · Jeremiah Liu · Sicong (Sheldon) Huang · Evgenii Nikishin · Sunho Park · Nilesh Ahuja · Mahesh Subedar · · Artyom Gadetsky · Jhosimar Arias Figueroa · Tim G. J. Rudner · Waseem Aslam · Adrián Csiszárik · John Moberg · Ali Hebbal · Kathrin Grosse · Pekka Marttinen · Bang An · Hlynur Jónsson · Samuel Kessler · Abhishek Kumar · Mikhail Figurnov · Omesh Tickoo · Steindor Saemundsson · Ari Heljakka · Dániel Varga · Niklas Heim · Simone Rossi · Max Laves · Waseem Gharbieh · Nicholas Roberts · Luis Armando Pérez Rey · Matthew Willetts · Prithvijit Chakrabarty · Sumedh Ghaisas · Carl Shneider · Wray Buntine · Kamil Adamczewski · Xavier Gitiaux · Suwen Lin · Hao Fu · Gunnar Rätsch · Aidan Gomez · Erik Bodin · Dinh Phung · Lennart Svensson · Juliano Tusi Amaral Laganá Pinto · Milad Alizadeh · Jianzhun Du · Kevin Murphy · Beatrix Benkő · Shashaank Vattikuti · Jonathan Gordon · Christopher Kanan · Sontje Ihler · Darin Graham · Michael Teng · Louis Kirsch · Tomas Pevny · Taras Holotyak -
2019 Poster: Towards Automatic Concept-based Explanations »
Amirata Ghorbani · James Wexler · James Zou · Been Kim -
2019 Poster: Visualizing and Measuring the Geometry of BERT »
Emily Reif · Ann Yuan · Martin Wattenberg · Fernanda Viegas · Andy Coenen · Adam Pearce · Been Kim -
2019 Poster: A Benchmark for Interpretability Methods in Deep Neural Networks »
Sara Hooker · Dumitru Erhan · Pieter-Jan Kindermans · Been Kim -
2018 : Finale Doshi-Velez »
Finale Doshi-Velez -
2018 : Panel on research process »
Zachary Lipton · Charles Sutton · Finale Doshi-Velez · Hanna Wallach · Suchi Saria · Rich Caruana · Thomas Rainforth -
2018 : Interpretability for when NOT to use machine learning by Been Kim »
Been Kim -
2018 : Finale Doshi-Velez »
Finale Doshi-Velez -
2018 : Poster Session 1 (note there are numerous missing names here, all papers appear in all poster sessions) »
Akhilesh Gotmare · Kenneth Holstein · Jan Brabec · Michal Uricar · Kaleigh Clary · Cynthia Rudin · Sam Witty · Andrew Ross · Shayne O'Brien · Babak Esmaeili · Jessica Forde · Massimo Caccia · Ali Emami · Scott Jordan · Bronwyn Woods · D. Sculley · Rebekah Overdorf · Nicolas Le Roux · Peter Henderson · Brandon Yang · Tzu-Yu Liu · David Jensen · Niccolo Dalmasso · Weitang Liu · Paul Marc TRICHELAIR · Jun Ki Lee · Akanksha Atrey · Matt Groh · Yotam Hechtlinger · Emma Tosch -
2018 Poster: Representation Balancing MDPs for Off-policy Policy Evaluation »
Yao Liu · Omer Gottesman · Aniruddh Raghu · Matthieu Komorowski · Aldo Faisal · Finale Doshi-Velez · Emma Brunskill -
2018 Poster: Sanity Checks for Saliency Maps »
Julius Adebayo · Justin Gilmer · Michael Muelly · Ian Goodfellow · Moritz Hardt · Been Kim -
2018 Spotlight: Sanity Checks for Saliency Maps »
Julius Adebayo · Justin Gilmer · Michael Muelly · Ian Goodfellow · Moritz Hardt · Been Kim -
2018 Poster: To Trust Or Not To Trust A Classifier »
Heinrich Jiang · Been Kim · Melody Guan · Maya Gupta -
2017 : Panel Session »
Neil Lawrence · Finale Doshi-Velez · Zoubin Ghahramani · Yann LeCun · Max Welling · Yee Whye Teh · Ole Winther -
2017 : Finale Doshi-Velez »
Finale Doshi-Velez -
2017 : Automatic Model Selection in BNNs with Horseshoe Priors »
Finale Doshi-Velez -
2017 : Poster spotlights »
Hiroshi Kuwajima · Masayuki Tanaka · Qingkai Liang · Matthieu Komorowski · Fanyu Que · Thalita F Drumond · Aniruddh Raghu · Leo Anthony Celi · Christina Göpfert · Andrew Ross · Sarah Tan · Rich Caruana · Yin Lou · Devinder Kumar · Graham Taylor · Forough Poursabzi-Sangdeh · Jennifer Wortman Vaughan · Hanna Wallach -
2017 : Coffee break and Poster Session I »
Nishith Khandwala · Steve Gallant · Gregory Way · Aniruddh Raghu · Li Shen · Aydan Gasimova · Alican Bozkurt · William Boag · Daniel Lopez-Martinez · Ulrich Bodenhofer · Samaneh Nasiri GhoshehBolagh · Michelle Guo · Christoph Kurz · Kirubin Pillay · Kimis Perros · George H Chen · Alexandre Yahi · Madhumita Sushil · Sanjay Purushotham · Elena Tutubalina · Tejpal Virdi · Marc-Andre Schulz · Samuel Weisenthal · Bharat Srikishan · Petar Veličković · Kartik Ahuja · Andrew Miller · Erin Craig · Disi Ji · Filip Dabek · Chloé Pou-Prom · Hejia Zhang · Janani Kalyanam · Wei-Hung Weng · Harish Bhat · Hugh Chen · Simon Kohl · Mingwu Gao · Tingting Zhu · Ming-Zher Poh · Iñigo Urteaga · Antoine Honoré · Alessandro De Palma · Maruan Al-Shedivat · Pranav Rajpurkar · Matthew McDermott · Vincent Chen · Yanan Sui · Yun-Geun Lee · Li-Fang Cheng · Chen Fang · Sibt ul Hussain · Cesare Furlanello · Zeev Waks · Hiba Chougrad · Hedvig Kjellstrom · Finale Doshi-Velez · Wolfgang Fruehwirt · Yanqing Zhang · Lily Hu · Junfang Chen · Sunho Park · Gatis Mikelsons · Jumana Dakka · Stephanie Hyland · yann chevaleyre · Hyunwoo Lee · Xavier Giro-i-Nieto · David Kale · Michael Hughes · Gabriel Erion · Rishab Mehra · William Zame · Stojan Trajanovski · Prithwish Chakraborty · Kelly Peterson · Muktabh Mayank Srivastava · Amy Jin · Heliodoro Tejeda Lemus · Priyadip Ray · Tamas Madl · Joseph Futoma · Enhao Gong · Syed Rameel Ahmad · Eric Lei · Ferdinand Legros -
2017 : Contributed talk: Beyond Sparsity: Tree-based Regularization of Deep Models for Interpretability »
Mike Wu · Sonali Parbhoo · Finale Doshi-Velez -
2017 : Invited talk: The Role of Explanation in Holding AIs Accountable »
Finale Doshi-Velez -
2017 Poster: Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes »
Taylor Killian · Samuel Daulton · Finale Doshi-Velez · George Konidaris -
2017 Oral: Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes »
Taylor Killian · Samuel Daulton · Finale Doshi-Velez · George Konidaris -
2016 : BNNs for RL: A Success Story and Open Questions »
Finale Doshi-Velez -
2016 Poster: Probing the Compositionality of Intuitive Functions »
Eric Schulz · Josh Tenenbaum · David Duvenaud · Maarten Speekenbrink · Samuel J Gershman -
2015 Workshop: Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization »
Joseph Jay Williams · Yasin Abbasi Yadkori · Finale Doshi-Velez -
2015 : Data Driven Phenotyping for Diseases »
Finale Doshi-Velez -
2015 Workshop: Bounded Optimality and Rational Metareasoning »
Samuel J Gershman · Falk Lieder · Tom Griffiths · Noah Goodman -
2015 Poster: Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction »
Been Kim · Julie A Shah · Finale Doshi-Velez -
2014 Poster: Design Principles of the Hippocampal Cognitive Map »
Kimberly Stachenfeld · Matthew Botvinick · Samuel J Gershman -
2014 Spotlight: Design Principles of the Hippocampal Cognitive Map »
Kimberly Stachenfeld · Matthew Botvinick · Samuel J Gershman -
2010 Poster: The Neural Costs of Optimal Control »
Samuel J Gershman · Robert C Wilson -
2009 Poster: Perceptual Multistability as Markov Chain Monte Carlo Inference »
Samuel J Gershman · Edward Vul · Josh Tenenbaum -
2009 Spotlight: Perceptual Multistability as Markov Chain Monte Carlo Inference »
Samuel J Gershman · Edward Vul · Josh Tenenbaum -
2009 Poster: A Bayesian Analysis of Dynamics in Free Recall »
Richard Socher · Samuel J Gershman · Adler Perotte · Per Sederberg · David Blei · Kenneth Norman