Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3665463.3678859acmconferencesArticle/Chapter ViewAbstractPublication Pageschi-playConference Proceedingsconference-collections
research-article
Open access

Ethics and Transparency in Game Data

Published: 14 October 2024 Publication History

Abstract

While existing work has discussed ethics and fairness in relation to data generally, and a small number of papers have raised the same issues within games specifically, work on addressing fairness and ethical issues with game data collection and usage is still rare. With game AI, LLM integration, data analytics, and machine learning on the rise, a new dimension to the responsible and ethical treatment of data opens up, comprising factors unique to video games. Our goal for this workshop is, thus, to bring together researchers and professionals working in the spaces of game human–computer interaction (HCI), game data and AI, and ethics in both games and AI to discuss and identify interdisciplinary research opportunities and devise potential solutions to existing problems.

References

[1]
Ana Paula Afonso, Maria Beatriz Carmo, Tiago Gonçalves, and Pedro Vieira. 2019. VisuaLeague: Player performance analysis using spatial-temporal data. Multimedia Tools and Applications 78, 23 (2019), 33069–33090.
[2]
Reuben Binns, Max Van Kleek, Michael Veale, Ulrik Lyngs, Jun Zhao, and Nigel Shadbolt. 2018. ’It’s Reducing a Human Being to a Percentage’: Perceptions of Justice in Algorithmic Decisions. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). ACM, New York, NY, USA, 1–14. https://doi.org/10.1145/3173574.3173951
[3]
Maude Bonenfant, Fabien Richert, and Patrick Deslauriers. 2017. Using big data tools and techniques to study a gamer community: Technical, epistemological, and ethical problems. Loading... 10, 16 (2017), 87–108.
[4]
Nick Bostrom and Eliezer Yudkowsky. 2014. The ethics of artificial intelligence. The Cambridge handbook of artificial intelligence 316 (2014), 334.
[5]
Alessandro Canossa, Anders Drachen, and Janus Rau Møller Sørensen. 2011. Arrrgghh!!! blending quantitative and qualitative methods to detect player frustration. In Proceedings of the 6th International Conference on Foundations of Digital Games (Bordeaux, France) (FDG ’11). ACM, New York, NY, USA, 61–68. https://doi.org/10.1145/2159365.2159374
[6]
Alessandro Canossa, Sasha Makarovych, Julian Togelius, and Anders Drachen. 2018. Like a DNA string: sequence-based player profiling in Tom clancy’s the division. In Proceedings of the Fourteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment(AIIDE’18). AAAI Press, Edmonton, Alberta, Canada, Article 22, 7 pages.
[7]
Sven Charleer, Kathrin Gerling, Francisco Gutiérrez, Hans Cauwenbergh, Bram Luycx, and Katrien Verbert. 2018. Real-Time Dashboards to Support eSports Spectating. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play (Melbourne, VIC, Australia) (CHI PLAY ’18). ACM, New York, NY, USA, 59–71. https://doi.org/10.1145/3242671.3242680
[8]
Zhengxing Chen, Truong-Huy D Nguyen, Yuyu Xu, Christopher Amato, Seth Cooper, Yizhou Sun, and Magy Seif El-Nasr. 2018. The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games. In Proceedings of the 12th ACM Conference on Recommender Systems (Vancouver, British Columbia, Canada) (RecSys ’18). ACM, New York, NY, USA, 200–208. https://doi.org/10.1145/3240323.3240345
[9]
Anders Harboell Christiansen, Emil Gensby, and Bryan S. Weber. 2019. Resolving Simultaneity Bias: Using Features to Estimate Causal Effects in Competitive Games. In 2019 IEEE Conference on Games (CoG). IEEE, London, UK, 1–8. https://doi.org/10.1109/CIG.2019.8848059
[10]
David Danks and Alex John London. 2017. Algorithmic bias in autonomous systems. In Proceedings of the 26th International Joint Conference on Artificial Intelligence(IJCAI’17). AAAI Press, Melbourne, Australia, 4691–4697.
[11]
Anders Drachen, Rafet Sifa, Christian Bauckhage, and Christian Thurau. 2012. Guns, swords and data: Clustering of player behavior in computer games in the wild. In 2012 IEEE conference on Computational Intelligence and Games (CIG). IEEE, Granada, Spain, 163–170.
[12]
Joshua A Eaton, David J Mendonça, and Matthew-Donald D Sangster. 2018. Attack, Damage and Carry: Role Familiarity and Team Performance in League of Legends. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 62. SAGE Publications, Sage CA: Los Angeles, CA, 130–134.
[13]
Markus Eger and Pablo Sauma Chacón. 2020. Deck Archetype Prediction in Hearthstone. In International Conference on the Foundations of Digital Games. ACM, New York, NY, United States, 1–11.
[14]
Magy Seif El-Nasr, Truong-Huy D Nguyen, Alessandro Canossa, and Anders Drachen. 2021. Game Data Science. Oxford University Press, Oxford, UK.
[15]
Motahhare Eslami, Kristen Vaccaro, Min Kyung Lee, Amit Elazari Bar On, Eric Gilbert, and Karrie Karahalios. 2019. User Attitudes towards Algorithmic Opacity and Transparency in Online Reviewing Platforms. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, United States, 1–14.
[16]
Nour Halabi, Günter Wallner, and Pejman Mirza-Babaei. 2019. Assessing the impact of visual design on the interpretation of aggregated playtesting data visualization. In Proceedings of the Annual Symposium on Computer-Human Interaction in Play. ACM, New York, NY, United States, 639–650.
[17]
Nathan Henderson, Wookhee Min, Jonathan Rowe, and James Lester. 2020. Multimodal player affect modeling with auxiliary classifier generative adversarial networks. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, Vol. 16. AAAI, Washington, DC, US, 224–230.
[18]
Danial Hooshyar, Moslem Yousefi, and Heuiseok Lim. 2019. A systematic review of data-driven approaches in player modeling of educational games. Artificial Intelligence Review 52, 3 (2019), 1997–2017.
[19]
Robin Hunicke. 2005. The case for dynamic difficulty adjustment in games. In Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology. ACM, New York, NY, United States, 429–433.
[20]
Daniel Kepplinger, Günter Wallner, Simone Kriglstein, and Michael Lankes. 2020. See, Feel, Move: player behaviour analysis through combined visualization of gaze, emotions, and movement. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1–14.
[21]
Erica Kleinman, Sabbir Ahmad, Zhaoqing Teng, Andy Bryant, Truong-Huy D. Nguyen, Casper Harteveld, and Magy Seif El-Nasr. 2020. ”And Then They Died”: Using Action Sequences for Data Driven, Context Aware Gameplay Analysis. In International Conference on the Foundations of Digital Games (Bugibba, Malta) (FDG ’20). ACM, New York, NY, USA, Article 63, 12 pages. https://doi.org/10.1145/3402942.3402962
[22]
Erica Kleinman, Murtuza N Shergadwala, and Magy Seif El-Nasr. 2022. Kills, Deaths, and (Computational) Assists: Identifying Opportunities for Computational Support in Esport Learning. In CHI Conference on Human Factors in Computing Systems. 1–13.
[23]
Athanasios Vasileios Kokkinakis, Simon Demediuk, Isabelle Nölle, Oluseyi Olarewaju, Sagarika Patra, Justus Robertson, Peter York, Alan Pedrassoli Pedrassoli Chitayat, Alistair Coates, Daniel Slawson, 2020. DAX: Data-Driven Audience Experiences in Esports. In ACM International Conference on Interactive Media Experiences. 94–105.
[24]
Yen-Ting Kuan, Yu-Shuen Wang, and Jung-Hong Chuang. 2017. Visualizing real-time strategy games: The example of starcraft ii. In 2017 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 71–80.
[25]
Ben Medler, Michael John, and Jeff Lane. 2011. Data cracker: developing a visual game analytic tool for analyzing online gameplay. In Proceedings of the SIGCHI conference on human factors in computing systems. 2365–2374.
[26]
David Melhart, Daniele Gravina, and Georgios N Yannakakis. 2020. Moment-to-moment Engagement Prediction through the Eyes of the Observer: PUBG Streaming on Twitch. In International Conference on the Foundations of Digital Games. 1–10.
[27]
David Melhart, Julian Togelius, Benedikte Mikkelsen, Christoffer Holmgård, and Georgios N. Yannakakis. 2023. The Ethics of AI in Games. IEEE Transactions on Affective Computing (2023), 1–14. https://doi.org/10.1109/TAFFC.2023.3276425
[28]
Benedikte Mikkelsen, Christoffer Holmgård, and Julian Togelius. 2017. Ethical considerations for player modeling. In Workshops at the Thirty-First AAAI Conference on Artificial Intelligence.
[29]
Dinara Moura, Magy Seif el Nasr, and Christopher D Shaw. 2011. Visualizing and understanding players’ behavior in video games: discovering patterns and supporting aggregation and comparison. In Proceedings of the 2011 ACM SIGGRAPH symposium on video games. ACM, 11–15.
[30]
Cathy O’neil. 2016. Weapons of math destruction: How big data increases inequality and threatens democracy. Broadway Books.
[31]
Nathan Partlan, Abdelrahman Madkour, Chaima Jemmali, Josh Aaron Miller, Christoffer Holmgård, and Magy Seif El-Nasr. 2019. Player imitation for build actions in a real-time strategy game. In AIIDE workshop on Artificial Intelligence for Strategy Games.
[32]
Johannes Pfau, Antonios Liapis, Georg Volkmar, Georgios N Yannakakis, and Rainer Malaka. 2020. Dungeons & replicants: automated game balancing via deep player behavior modeling. In 2020 IEEE Conference on Games (CoG). IEEE, 431–438.
[33]
Johannes Pfau, Jan David Smeddinck, Ioannis Bikas, and Rainer Malaka. 2020. Bot or Not? User Perceptions of Player Substitution with Deep Player Behavior Models. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). ACM, New York, NY, USA, 1–10. https://doi.org/10.1145/3313831.3376223
[34]
Daniel Ramirez-Cano, Simon Colton, and Robin Baumgarten. 2010. Player classification using a meta-clustering approach. In Proceedings of the 3rd Annual International Conference Computer Games, Multimedia & Allied Technology. 297–304.
[35]
Magy Seif El-Nasr and Erica Kleinman. 2020. Data-driven game development: ethical considerations. In International Conference on the Foundations of Digital Games. 1–10.
[36]
Murtuza N Shergadwala and Magy Seif El-Nasr. 2021. Esports agents with a theory of mind: towards better engagement, education, and engineering. arXiv preprint arXiv:2103.04940 (2021).
[37]
Penny Sweetser. 2024. Large Language Models and Video Games: A Preliminary Scoping Review. arXiv preprint arXiv:2403.02613 (2024).
[38]
Graham Todd, Sam Earle, Muhammad Umair Nasir, Michael Cerny Green, and Julian Togelius. 2023. Level Generation Through Large Language Models. In Proceedings of the 18th International Conference on the Foundations of Digital Games. 1–8.
[39]
Daijin Yang, Erica Kleinman, and Casper Harteveld. 2024. GPT for Games: A Scoping Review (2020-2023). arXiv preprint arXiv:2404.17794 (2024).
[40]
Georgios N Yannakakis, Pieter Spronck, Daniele Loiacono, and Elisabeth André. 2013. Player modeling. (2013).
[41]
Georgios N Yannakakis and Julian Togelius. 2018. Artificial intelligence and games. Vol. 2. Springer.
[42]
Deheng Ye, Guibin Chen, Wen Zhang, Sheng Chen, Bo Yuan, Bo Liu, Jia Chen, Zhao Liu, Fuhao Qiu, Hongsheng Yu, 2020. Towards playing full moba games with deep reinforcement learning. Advances in Neural Information Processing Systems 33 (2020), 621–632.
[43]
Deheng Ye, Zhao Liu, Mingfei Sun, Bei Shi, Peilin Zhao, Hao Wu, Hongsheng Yu, Shaojie Yang, Xipeng Wu, Qingwei Guo, 2020. Mastering complex control in moba games with deep reinforcement learning. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34. 6672–6679.
[44]
Andrew Zhu, Lara J Martin, Andrew Head, and Chris Callison-Burch. 2023. CALYPSO: LLMs as Dungeon Masters’ Assistants. arXiv preprint arXiv:2308.07540 (2023).
[45]
Alexander Zook, Stephen Lee-Urban, Michael R Drinkwater, and Mark O Riedl. 2012. Skill-based mission generation: A data-driven temporal player modeling approach. In Proceedings of the The third workshop on Procedural Content Generation in Games. 1–8.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
CHI PLAY Companion '24: Companion Proceedings of the 2024 Annual Symposium on Computer-Human Interaction in Play
October 2024
500 pages
ISBN:9798400706929
DOI:10.1145/3665463
This work is licensed under a Creative Commons Attribution International 4.0 License.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 October 2024

Check for updates

Author Tags

  1. AI
  2. Machine Learning
  3. ethics
  4. game AI
  5. game data
  6. transparency

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

CHI PLAY '24
Sponsor:

Acceptance Rates

Overall Acceptance Rate 421 of 1,386 submissions, 30%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 249
    Total Downloads
  • Downloads (Last 12 months)249
  • Downloads (Last 6 weeks)78
Reflects downloads up to 25 Jan 2025

Other Metrics

Citations

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Login options

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media