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We describe cases where real recommender systems were modified in the service of various human values such as diversity, fairness, well-being, time well spent, and factual accuracy.
Does Watching TV Make Us Happy?
Frey, B. S., Benesch, C., and Stutzer, A · 2007
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Concepts and Measures of Agency
Alkire, S · 2008
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Teaching ethics in the clinic. The theory and practice of moral case deliberation
Molewijk, A. C., Abma, T., Stolper, M., and Widdershoven, G · 2008
Earlier work this paper cites.
Faith in the algorithm, part 2: Computational eudaemonics
Rodriguez, M. A. and Watkins, J. H · 2009
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Coherent Extrapolated Volition: A Meta-Level Approach to Machine Ethics
Tarleton, N · 2010
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Click-baiting, 2014
Khalid El-Arini and Joyce Tang · 2014
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Wellbeing and Policy
O’Donnell, G., Deaton, A., Durand, M., Halpern, D., and Layard, R · 2014
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Beyond clicks: Dwell time for personalization
Yi, X., Hong, L., Zhong, E., Liu, N. N., and Rajan, S · 2014
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Online Social Network Site Addiction: A Comprehensive Review
Andreassen, C. S · 2015
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Novelty and diversity in recommender systems
Castells, P., Hurley, N. J., and Vargas, S · 2015
Earlier work this paper cites.
Recommender systems for self-actualization
Knijnenburg, B. P., Sivakumar, S., and Wilkinson, D · 2016
Earlier work this paper cites.
Further Reducing Clickbait in Feed. Facebook, 2016
Peysakhovich, A. and Hendrix, K · 2016
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Detecting Trustworthy Domains
Cora, M. V · 2017
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The Times Sharply Increases Articles Open for Comments, Using Google’s Technology, June 2017
Etim, B · 2017
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Inverse reward design
Hadfield-Menell, D., Milli, S., Abbeel, P., Russell, S. J., and Dragan, A · 2017
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Network propaganda: Manipulation, disinformation, and radicalization in American politics
Benkler, Y., Faris, R., and Roberts, H · 2018
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Want to Design User Behavior? Pass the ‘Regret Test’ First, 2018
Eyal, N · 2018
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Measuring healthy conversation. Twitter, 2018
Gadde, V. and Gasca, D · 2018
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Excessive use of online video streaming services: Impact of recommender system use, psychological factors, and motives
Hasan, M. R., Jha, A. K., and Liu, Y · 2018
Cited alongside, same era.
Exposure diversity as a design principle for recommender systems
Helberger, N., Karppinen, K., and D’Acunto, L · 2018
Cited alongside, same era.
Specification gaming examples in ai, 2018
Krakovna, V · 2018
Cited alongside, same era.
Towards a fair marketplace: Counterfactual evaluation of the trade-off between relevance, fairness & satisfaction in recommendation systems
Mehrotra, R., McInerney, J., Bouchard, H., Lalmas, M., and Diaz, F · 2018
Cited alongside, same era.
Simplifying reward design through divide-and-conquer
Ratner, E., Hadfield-Mennell, D., and Dragan, A. D · 2018
Cited alongside, same era.
How Facebook and Google Accidentally Created a Perfect Ecosystem for Targeted Disinformation
Stöcker, C · 2019
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Inside Twitter’s ambitious plan to change the way we tweet
Wagner, K · 2019
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Moderating the Public Sphere
York, J. and Zuckerman, E · 2019
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Recommending what video to watch next: A Multitask Ranking System
Zhao, Z., Chi, E., Hong, L., Wei, L., Chen, J., Nath, A., Andrews, S., Kumthekar, A., Sathiamoorthy, M., and Yi, X · 2019
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Social choice ethics in artificial intelligence
Baum, S. D · 2020
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Active preference-based gaussian process regression for reward learning
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Rohde, D., Bonner, S., Dunlop, T., Vasile, F., and Karatzoglou, A · 2018
Cited alongside, same era.
Beyond GDP
Stiglitz, J. E., Fitoussi, J.-P., and Durand, M · 2018
Cited alongside, same era.
Increasing Our Efforts to Fight False News
Tessa Lyons · 2018
Cited alongside, same era.
Facebook Opens Up About False News
Thompson, N · 2018
Cited alongside, same era.
Beyond Personalization: Research Directions in Multistakeholder Recommendation
Abdollahpouri, H., Adomavicius, G., Burke, R., Guy, I., Jannach, D., Kamishima, T., Krasnodebski, J., and Pizzato, L · 2019
Cited alongside, same era.
Fairness and machine learning, 2019
Barocas, S., Hardt, M., and Narayanan, A · 2019
Cited alongside, same era.
Are Filter Bubbles Real?
Bruns, A · 2019
Cited alongside, same era.
Bıyık, E., Huynh, N., Kochenderfer, M. J., and Sadigh, D · 2020
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Safe imitation learning via fast bayesian reward inference from preferences
Brown, D. S., Coleman, R., Srinivasan, R., and Niekum, S · 2020
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Reflective equilibrium
Daniels, N · 2020
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Using AI to detect COVID-19 misinformation and exploitative content, 2020
Facebook · 2020
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Artificial intelligence, values and alignment
Gabriel, I · 2020
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Toward creating a fairer ranking in search engine results
Gao, R. and Shah, C · 2020
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Pots: Protective optimization technologies
Kulynych, B., Overdorf, R., Troncoso, C., and Gürses, S · 2020
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Beyond Optimizing for Clicks: Incorporating Editorial Values in News Recommendation
Lu, F., Dumitrache, A., and Graus, D · 2020
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To Apply Machine Learning Responsibly, We Use It In Moderation
Salganik, M. J. and Lee, R. C · 2020
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Ieee 7010: A new standard for assessing the well-being implications of artificial intelligence
Schiff, D., Ayesh, A., Musikanski, L., and Havens, J. C · 2020
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The Verification Handbook for Disinformation And Media Manipulation
Silverman, C. (ed.) · 2020
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Aligning AI to Human Values means Picking the Right Metrics. Partnership on AI, 2020
Stray, J · 2020
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Reliance on Metrics is a Fundamental Challenge for AI
Thomas, R. L. and Uminsky, D · 2020
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