Background

 

The University of York and Goldsmiths University of London would like to invite you to take part in the following research project: Using Interactive Machine Learning for Designing Motion Control Schemes in Games. The project has been funded under the EPSRC Centre for Doctoral Training in Intelligent Games & Game Intelligence (IGGI).

EPSRC Reference: EP/L015846/1.

Before agreeing to take part, please read this information sheet carefully and let us know if anything is unclear or you would like further information.  

 

What is the purpose of the study?

 

Overview

 

In this study you will be asked to join different online game design workshops and develop a digital game using an interactive machine learning (IML) plugin for the Unity3D game engine called InteractML. You are not being assessed on your performance, just feel free to be creative and participate in the different activities organised. I will let you know when each of the activities are done and you can continue with development.

The aim of this project is to investigate the opportunities and challenges of designing movement interactions and motion control schemes using InteractML, a node-based interactive machine learning framework for the Unity3D game engine.

 

People involved in the research

 

The research is being carried out by Carlos Gonzalez Diaz as part of the Intelligent Games and Games Intelligence (IGGI) PhD programme.

His supervisor at the University of York is Prof. Christoph Sebastian Deterding, Professor of Digital Creativity at the Digital Creativity Lab.

His supervisor at Goldsmiths University of London is Prof. Marco Gillies, Reader at the Computing Department.

In addition, Phoenix Perry, Course Leader at the Creative Computing Institute from University of the Arts London will act as a collaborator.

 

Ethical review

 

The research has been subject to the ethical review of the Ethics Committee of the Computer Science at the University of York. For further details, please contact me at carlos.gonzalezdiaz@york.ac.uk in the first instance. If you are still dissatisfied, please contact the Computer Science Ethics Committee at cs-ethics@york.ac.uk or the University’s Acting Data Protection Officer at dataprotection@york.ac.uk.

 

Instructions and timing

 

In this study you will be asked to join our Discord community and take part in different online game design workshop that will help you develop a digital game using an interactive machine learning (IML) plugin for the Unity3D game engine called InteractML. InteractML offers a visual node-based interface to create and test machine learning models. You are not being assessed on your performance, just feel free to be creative and participate in the different activities organised.
During the study, we will give you video tutorials introducing you to interactive machine learning and looking at the example projects provided. You can request additional tutorials and support either through text or video chat in Discord. In addition, we will organise collaborative brainstorming sessions where you will be encouraged to think of different motion control schemes and game ideas to use IML in VR. The outcome of the brainstorming sessions will be a series of movement interactions, control schemes and interfaces that you can implement during the study. The brainstorming sessions will last 1 hour each, and they will be organised through video-call or through social VR platforms (i.e. Rec Room or Mozilla Hubs). The tutorials and the brainstorming might happen at different times online, and not necessarily one after the other.  
Once there are some interesting ideas, you are free to schedule your time during the study to develop your project using InteractML. During the study, feel free to share any progress or raise any issues with the tool in the Discord server. People can benefit from it and we are there to help each others! During the study, either on premises or in a separate follow-up, you will be interviewed about your experience with InteractML and your game project. Photographs and/or video will be taken occasionally to allow you to explain and demonstrate your usage experience during the interview.
Don’t worry, video recordings and photographs with faces or other identifiable features will not be publicly shared. Exemplary interface screenshots, photographs, and stills may be publicised to demonstrate particular issues identified by participants in scientific publications and presentations. On this imagery, any faces and other identifying features will be blacked out.

By joining these events and signing the informed consent, you agree that the content you share there will follow the rules stated above. Text, video and audio shared in the platform might be used for research purposes, but all data will be anonymized following the procedure previously mentioned.

What kind of data will you collect from me?

 

During this study we will collect basic descriptive demographics, ideas and sketches from the brainstorming session, occasional photographs and video recordings, and follow-up audio or video interviews about your overall experience, combined with occasional video or photo imagery to allow you to demonstrate the usage experience of the tool. We will also collect automatic telemetry data from your usage of InteractML (i.e. buttons clicked, training and testing datasets generated, etc.), simple answers to on-screen prompts about your experience with InteractML and the source code of the app you created. The intellectual property of anything you create of course stays with you. We only want to improve our understanding of the technology :)

In addition, we will collect in this form your email and your Discord username. This is to make sure that we can reach you in case you have any issues connecting to Discord and to identify you in Discord. Please, be aware that your Discord username will be visible to everyone in the Discord server and could potentially identify you. Make sure as well to not share any sensitive information with others. Don't worry, we will anonymise all your data in publications and any context outside of the Discord server so you can't be identified.

Your name won’t be collected throughout any part of the study. All data will be anonymised. We will give you a unique study ID in order for us to correctly delete your data if you wish to exercise your right to be forgotten from this study.

 

Discomfort risk

 

There is a potential risk of discomfort by using a virtual reality (VR) headset. Our system should not produce any, but if at any moment you feel like you want to stop, go for a drink or go to the toilet, please let me know and we can stop/pause the session.

 

Voluntary Participation

Your participation is voluntary. There won’t be a compensation, but you will learn about machine learning in games! And hopefully create a fun and interesting game that will make you stand out there :)

If you decide to take part, you will be given access to the online interactML Discord server. If you change your mind at any point during the study, you will be able to withdraw your participation without having to provide a reason.

Why have I been invited to take part?

 

We are asking you to participate because you are a developer/designer and have some previous experience with Unity 3D, and that is the profile we are interested in.

 

On what basis will you process my data?

 

Under the General Data Protection Regulation (GDPR), the University has to identify a legal basis for processing personal data and, where appropriate, an additional condition for processing special category data.

Personal data is defined as data from which someone could be identified. For example, in this study I will NOT be collecting your name or address. Special category data is personal data which the GDPR says is more sensitive, and so needs more protection. In this study, I will NOT be collecting any special category data.

In line with our charter which states that we advance learning and knowledge by teaching and research, the University processes personal data for research purposes under Article 6 (1) (e) of the GDPR:  

Processing is necessary for the performance of a task carried out in the public interest

Special category data is processed under Article 9 (2) (j):

Processing is necessary for archiving purposes in the public interest, or scientific and historical research purposes or statistical purposes

Research will only be undertaken where ethical approval has been obtained, where there is a clear public interest and where appropriate safeguards have been put in place to protect data.

In line with ethical expectations and in order to comply with common law duty of confidentiality, we will seek your consent to participate where appropriate. This consent will not, however, be our legal basis for processing your data under the GDPR.  

 

How will you use my data?

 

Your name is not collected throughout any part of the study. You will be give an unique anonymous ID that will be used your email or Discord username.

Imagery with identifiable faces will not be publicly shared beyond the investigator team. Exemplary imagery may be used in academic publications to demonstrate particular issues identified by you. On this imagery, any faces or other identifiable characteristics of the person will be blacked out. Raw, non-anonymised imagery will be deleted after data analysis and publication have been concluded.

Voice recordings will be transcribed and then deleted. Any names and other information potentially identifying a person (such as your email or your Discord username) will be replaced by the ID or other anonymising aliases.

Now, in order to analyse all your anonymised data, we will follow a qualitative procedure called "Thematic Analysis". In thematic analysis, we will generate a number of tags for your data describing as best as possible what participants are doing. After we have number of tags meaningful enough, we will be able to converge several of them into bigger "themes", hence its name. You can check more about thematic analysis in wikipedia.

 

Will you share my data with 3rd parties?

 

We won't directly share your data with 3rd parties, but bear in mind that we are using Discord as the platform for online communication and that is a 3rd party. The data we anonymise and analyse will be accessible to the project team at York, Goldsmiths and University of the Arts London. However, any information that is shared in the Discord server is stored in Discord data centers. Discord is GDPR compliant and you can request full deletion of your data in different ways. See Discord Request copy of data and Discord Data Package.  

We will only collect data from Discord, but we won't share any data from an external source to Discord. That is, collection is one way (from Discord to us). We might use other GDPR online services, and the same rule applies, we will only use these services to collect data and never to share.

Anonymised data may be reused by the research team for secondary research purposes such as writing scientific papers or giving scientific presentations, but never shared with any third parties. All data will be stored in secured servers managed by the University of York.

 

How will you keep my data secure?

 

The University will put in place appropriate technical and organisational measures to protect your personal data and/or special category data. For the purposes of this project we will make sure that your data will be anonymised as soon as possible and non-anonymised data deleted as soon as possible. Only the researchers on this study will see non-anonymised information about you. No reports or publications will use information that can identify you in any way or any individual as being of this project. These are only linked and identified by a unique number, not your name, email, Discord username or any other information that could identify you. The digital files will be stored on a secure computer and backed up on a secure server.

Information will be treated confidentiality and shared on a need-to-know basis only within the researcher team. The University of York is committed to the principle of data protection by design and default and will collect the minimum amount of data necessary for the project. In addition, we will anonymise or pseudonymise data wherever possible.

The University of York cloud storage solution is provided by Google which means that data can be located at any of Google’s globally spread data centres. The University has data protection complaint arrangements in place with this provider. For further information see, https://www.york.ac.uk/it-services/google/policy/privacy/.

 

Will I be identified in any research outputs?

 

No, data will be anonymised and it won’t be possible to identify you from any other participant.


Nevertheless, bear in mind that if you choose to post or share any videos or imagery from your own work on publicly available services like Youtube, you might become publicly identifiable even if we anonymise everything from your data.

 

How long will you keep my data?

 

Data will be retained in line with legal requirements or where there is a business need. Retention are determined in line with the University’s Records Retention Schedule. The data collected from this study will be securely protected in the University’s cloud storage for up to 5 years. Any local copies will be deleted once analysis is completed.

 

What rights do I have in relation to my data?

 

Under the GDPR, you have a general right of access to your data, a right to rectification, erasure, restriction, objection or portability. You also have a right to withdrawal. Please note, not all rights apply where data is processed purely for research purposes. For further information see, https://www.york.ac.uk/records-management/generaldataprotectionregulation/individualsrights/.

If you want us to delete or perform any changes to your data, please contact the lead researcher at carlos.gonzalezdiaz@york.ac.uk in the first instance. If you don’t receive an answer in less than a month, please contact any of the additional researchers at sebastian.deterding@york.ac.uk, m.gillies@gold.ac.uk, or phoenix.perry@arts.ac.uk. You can as well let us know verbally through a video call, or texting us directly in the online platform.

Questions or concerns

 

If you have any questions about this participant information sheet or concerns about how your data is being processed, please contact the University of York Computer Science Ethics Chair (cs-ethics@york.ac.uk) in the first instance.

If you have any questions about the project itself, please contact the lead researcher, the academic project supervisors and collaborators at

 

 

Carlos González Díaz

Lead Researcher

carlos.gonzalezdiaz@york.ac.uk

University of York, Computer Science, The Ron Cooke Hub, YO10 5GE, Heslington, York, UK

 

Dr Sebastian Deterding

Academic Supervisor

sebastian.deterding@york.ac.uk

University of York, Digital Creativity Labs, The Ron Cooke Hub, YO10 5GE, Heslington, York, UK

 

Dr Marco Gillies

Academic Supervisor

m.gillies@gold.ac.uk

Senior Lecturer, Computing Department, Goldsmiths, University of London, New Cross, SE14 6NW

London, UK

Phoenix Perry

Collaborator

phoenix.perry@arts.ac.uk

Course Leader, Creative Computing Institute, University of the Arts London, 272 High Holborn

WC1V 7EY, London, UK

Rebecca Fiebrink

Collaborator

c.hilton@gold.ac.uk

Reader, Creative Computing Institute, University of the Arts London, 272 High Holborn

WC1V 7EY, London, UK

Nicola Plant

Collaborator

n.plant@gold.ac.uk

Post Doctoral Researcher, Computing Department, Goldsmiths, University of London, New Cross, SE14 6NW

London, UK

Clarice Hilton

Collaborator

c.hilton@gold.ac.uk

Developer, Computing Department, Goldsmiths, University of London, New Cross, SE14 6NW

London, UK


 

Right to complain


 

 

If you are unhappy with the way in which the University has handled your personal data, you have a right to complain to the Information Commissioner’s Office. For information on reporting a concern to the Information Commissioner’s Office, see     www.ico.org.uk/concerns