designers, or as parents? And so again, through Ukie and through other mechanisms, we’ve been really focused in the last couple of years about figuring out ways that we can leverage this kind of data, data from play, and turn players into citizen scientists.
of my business partner and wife Kirsty being extremely stressed with various life and work problems, and watching powerwashing videos to self soothe. When we were looking to make a first-person shooter as a small studio, we thought, “what’s a small, bite-sized first-person shooter that we could do as a small team?” And just off the cuff I suggested you could have a powerwasher. And Kirsty said, “oh my god, powerwash simulator! That’s the game we should make.” So then we made a prototype demo – this was just at the start of lockdown in 2020 – and one of our marketing coordinators suggested that we release the demo for free. There was a voracious appetite for it.
What happened next? JM: We started getting anecdotal stories about how people with anxiety, ADHD, and various other mental health conditions, felt that this game was like no other in its ability to calm those particular conditions. We even had a friend reach out and tell me that his son, who has autism and really enjoys games, often gets wound up after playing those games and it’s somewhat difficult to manage his temperament, but not so with PowerWash. And so we thought, “there’s so much anecdotal evidence here, what can we do to maybe formalize it and just investigate whether there’s actually something here or not.”
Andrew, what attracted you to the collaboration with FuturLab? Andrew Przybylski: So, we kind of have a “monster of the week” thing about how games are either great or really bad. But most of the time, what we have is anecdotal. We’ve been working 15 years, specifically to move past anecdotes. And to get some idea of the kind of data that players generate when they’re having a good time – when they’re relaxing, when they’re unwinding, when they’re collaborating, when they’re competing – can that data actually be useful for understanding things that we would actually care about? Either as psychologists, as game
So is the appeal the access that you have to affect the game, the game itself, or the nature of the game? AP: It’s pretty molecular. A lot of what we do when we study games and how they might help or hurt people is really zoomed out. Because we just ask questionnaires a lot of the time, the really nice thing about PowerWash is it’s really zoomed in, like there’s individual sessions to look at. And we can ask people about how they feel and really get down into the mechanisms around mental health. And that’s the value proposition. The fact of the matter is that getting down into the play experience is what’s really exciting. If this game is really relaxing, it’d be really nice to know what about it is relaxing.
How will you gather data? JM: We’ve hired a programmer on our team who will branch a version of the game and will essentially do the Oxford researchers’ bidding in terms of implementing new features. Whatever path Oxford chooses to go down and look into, there’s a programmer on our side to facilitate any changes to the game, essentially. [As to gathering the data] we’ve yet to work out the fine details of that, but it seems like it will be an opt-in for owners of the game on Steam. But the method of sending that out to people and collecting participants, I’m not sure about that yet.
AP: There’s a bit of a loop that’s potentially a virtuous loop. But I mean, honestly, with a handful of exceptions in the industry, there really aren’t many models of opting in players to donate their own data to science. Some companies – the very large companies with very, very large teams – maintain a branch of the game or a branch of players who opt in specifically to learn about themselves and to improve the product. The largest one I’ve run into in the last couple of years is 12,000 potential people who participate.
March 2022 MCV/DEVELOP | 33
From top:
James Marsden, FuturLab, founder Professor Andrew Przybylski,Oxford Internet Institute
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72
