Time to start preparing for the next summer’s chili season. This time I have promised myself that I will not fool around with any silly Ikea “passive hydroponics” system or similar. Just old-fashioned soil, some peat, water and a light. But I will make use of the Ikea cultivation pots and led lights, as much as possible.
I will also try to radically cut down the number of plants that I’ll grow this time. Last summer was cold, damp, dark and bad in so many ways, but one part of the problem was that I had just too many plants in the end. Packing plants too densely into a small greenhouse will just predispose all plants to pests and diseases. Smaller number is also good for getting enough sunshine and good airflow around all plants.
I am again putting my trust in Finnish chili seeds from Fatalii.net (Jukka Kilpinen’s “Chile Pepper Empire”). I am trying to grow five plants:
Naga Morich (C. chinense)
Carolina Reaper x 7pot Douglah (C. Chinense hybrid, F2 generation)
7pot Primo Orange (C. chinense)
Moruga Scorpion (C. chinense)
Rocoto Riesen, Yellow (C. pubescens)
You might spot a pattern here: this is apparently the year of superhots for me (the Rocoto Riesen is the odd one out – thanks to Fatalii for dropping it into my order as a “surprise extra”). Originally I was planning on focusing on just my regular kitchen varieties (Lemon Drop, etc.), but losing all my hot chilies last summer left some kind of craving for retribution. If all these grow into proper plants, and yield proper crops, I will be in trouble. But: let’s see!
The key research infrastructures these days include e.g. access to online publication databases, and ability to communicate with your colleagues (including such prosaic things as email, file sharing and real-time chat). While an astrophysicist relies on satellite data and a physicist to a particle accelerator, for example, in research and humanities and human sciences is less reliant on expensive technical infrastructures. Understanding how to do an interview, design a reliable survey, or being able to carefully read, analyse and interpret human texts and expressions is often enough.
Said that, there are tools that are useful for researchers of many kinds and fields. Solid reference database system is one (I use Zotero). In everyday meetings and in the field, note taking is one of the key skills and practices. While most of us carry our trusty laptops everywhere, one can do with a lightweight device, such as iPad Pro. There are nice keyboard covers and precise active pens available for today’s tablet computers. When I type more, I usually pick up my trusty Logitech K810 (I have several of those). But Lenovo Yoga 510 that I have at home has also that kind of keyboard that I love: snappy and precise, but light of touch, and of low profile. It is also a two-in-one, convertible laptop, but a much better version from same company is X1 Yoga (2nd generation). That one is equipped with a built-in active pen, while being also flexible and powerful enough so that it can run both utility software, and contemporary games and VR applications – at least when linked with an eGPU system. For that, I use Asus ROG XG Station 2, which connects to X1 Yoga with a Thunderbolt 3 cable, thereby plugging into the graphics power of NVIDIA GeForce GTX 1070. A system like this has the benefit that one can carry around a reasonably light and thin laptop computer, which scales up to workstation class capabilities when plugged in at the desk.
One of the most useful research tools is actually a capable smartphone. For example, with a good mobile camera one can take photos to make visual notes, photograph one’s handwritten notes, or shoot copies of projected presentation slides at seminars and conferences. When coupled with a fast 4G or Wi-Fi connection and automatic upload to a cloud service, the same photo notes almost immediately appear also the laptop computer, so that they can be attached to the right folder, or combined with typed observation notes and metadata. This is much faster than having a high-resolution video recording of the event; that kind of more robust documentation setups are necessary in certain experimental settings, focus group interview sessions, collaborative innovation workshops, etc., but in many occasions written notes and mobile phone photos are just enough. I personally use both iPhone (8 Plus) and Android systems (Samsung Galaxy Note 4 and S7).
Writing is one of they key things academics do, and writing software is a research tool category on its own. For active pen handwriting I use both Microsoft OneNote and Nebo by MyScript. Nebo is particularly good in real-time text recognition and automatic conversion of drawn shapes into vector graphics. I link a video by them below:
My main note database is at Evernote, while online collaborative writing and planning is mostly done in Google Docs/Drive, and consortium project file sharing is done either in Dropbox or in Office365.
Microsoft Word may be the gold standard of writing software in stand-alone documents, but their relative share has radically gone down in today’s distributed and collaborative work. And while MS Word might still have the best multi-lingual proofing tools, for example, the first draft might come from an online Google Document, and the final copy end up into WordPress, to be published in some research project blog or website, or in a peer-reviewed online academic publication, for example. The long, book length projects are best handled in dedicated writing environment such as Scrivener, but most collaborative book projects are best handled with a combination of different tools, combined with cloud based sharing and collaboration in services like Dropbox, Drive, or Office365.
If you have not collaborated in this kind of environment, have a look at tutorials, here is just a short video introduction by Google into sharing in Docs:
What are your favourite research and writing tools?
The past year, 2017, has been so intense and packed to the brim, that it is hard to produce any sort of coherent picture, what it was all about. There remains just some flashes from the road: some new places visited, Wroclaw Poland, Hong Kong China, start as the vice dean of the new Faculty of Communication Sciences, cultivating chili peppers (only to be let down by one of the worst summer weathers in years), testing and adopting to daily use new technologies, Apple Airpods, Lenovo Yoga 2-in-1s, playing Pokémon GO in streets and parks, around the world, making plans and proposals, presenting and negotiating, being happy with the people, frustrated with the people, enjoying nature, enjoying good food, taking photographs, editing and sharing photographs, working late, sleeping badly, sleeping well, playing games, not being able to play games, getting the Centre of Excellence approved, working with colleagues on new degree programs, working with colleagues on Tampere3 university merger, working, taking kids to school, to hobbies, making food and reading bedtime stories, feeding birds, walking out in the snow, in sunshine, in rain, going to sauna. There have been many things worth remembering, some worth forgetting. Have a better year, next year, everyone!
There are several games researcher positions open right now: the Academy of Finland has granted funding for the new Centre of Excellence in Game Culture Studies (CoE GameCult: 2018-2025 CoE Program), and there are currently 5 Postdoc or University Researcher (a senior researcher) positions available for application in the University of Tampere Game Research Lab (in UTA/COMS/TRIM). The total number of new researcher positions is larger, as there will be additional calls opening within the same CoE in the University of Jyväskylä and Turku/Pori Unit. There is general text of the call here: https://coe-gamecult.org/
and link to the UTA recruitment system here: https://uta.rekrytointi.com/paikat/?o=A_RJ&jgid=1&jid=1062.
Campus Luigi Einaudi, Università di Torino, Turin, Italy
Lungo Dora Siena, 100 A, 10153 Turin, Italy
Conference chairs: Riccardo Fassone and Matteo Bittanti
Games have long since moved out of the toy drawer, but our understanding of them can still benefit from seeing them in a wider context of mediated meaning-making. DiGRA 2018 follows Marshall McLuhan, and sees games as extensions of ourselves. They recalibrate our senses and redefine our social relationships. The environments they create are more conspicuous than their content. They are revealing, both of our own desires and of the society within which we live. Their message is their effect. Games change us.
To explore this change, we invite scholars, artists and industry to engage in discussions over the following tracks:
Game platforms invite new textualities, new technologies and new networks of power relations. Game structures, their integration with and use of the technology, as well as the affordances and restrictions offered by the platforms on which they live, influence our experience of them.
Games invite new relations between their users, and players strive for and achieve new modes of perception. This reconfigures our attention, and establishes new patterns and forms of engagement.
The connection between a game and its content is often interchangeable – a game is clearly recognizable even if the surface fiction is changed. But games still produce meanings and convey messages. We ask, what are the modes of signification and the aesthetic devices used in games? In this context we particularly invite authors to look at games that claim to be about serious topics or deal with political and social issues.
The playing of the game has become content, and we invite authors to explore spectatorship, streaming, allied practices and hybrid media surrounding play and the players. How can we describe and examine the complex interweaving of practices found in these environments?
Games are subject to material, economic and cultural constraints. This track invites reflection on how these contingencies as well as production tools, industry and business demands and player interventions contribute to the process of signification.
Games are created within constraints, affordances, rules and permissions which give us a frame in which games generate meaning. Games have voice, a language, and they do speak. This is the poetics of games, and we invite our fellows to explore and uncover it.
Games tend to break out of the formats given them, and so for this track we invite the outstanding abstracts, papers and panels on alternative topics to the pre-determined tracks.
We invite full papers, 5000 – 7000 words plus references using the DiGRA 2018 submission template (http://www.digra.org/?attachment_id=148233), extended abstracts (from 500 words, maximum 1000, excluding references), and panel submissions (1000 words excluding references, with a 100 word biography of each participant). Full papers will be subject to a double-blind peer review. Extended abstracts will be blinded and peer reviewed by committees organised by the track chairs. Panels will be reviewed by the track chairs and the program chairs. General inquiries should be addressed to Riccardo Fassone – riccardo.fassone AT unito.it. Artist contributions, industry contributions, performances or non-standard presentations should be addressed to Matteo Bittanti – matteo.bittanti AT iulm.it .
Program chairs are
Martin Gibbs, martin.gibbs AT unimelb.edu.au, University of Melbourne, Australia
Torill Elvira Mortensen, toel AT itu.dk, IT University of Copenhagen, Denmark
Submission opens: December 1st, 2017
Final submission deadline: January 31st, 2018
Results from reviews: March 1st, 2018
Early registration deadline: March 15th, 2018
Reviewed and rewritten full papers final deadline: April 15th, 2018
The main media attention in applications of AI, artificial intelligence and machine learning, has been on such application areas as smart traffic, autonomous cars, recommendation algorithms, and expert systems in all kinds of professional work. There are, however, also very interesting developments taking place around photography currently.
There are multiple areas where AI is augmenting or transforming photography. One is in how the software tools that professional and amateur photographers are using are advancing. It is getting all the time easier to select complex areas in photos, for example, and apply all kinds of useful, interesting or creative effects and functions in them (see e.g. what Adobe is writing about this in: https://blogs.adobe.com/conversations/2017/10/primer-on-artificial-intelligence.html). The technical quality of photos is improving, as AI and advanced algorithmic techniques are applied in e.g. enhancing the level of detail in digital photos. Even a blurry, low-pixel file can be augmented with AI to look like a very realistic, high resolution photo of the subject (on this, see: https://petapixel.com/2017/11/01/photo-enhancement-starting-get-crazy/.
But the applications of AI do not stop there. Google and other developers are experimenting with “AI-augmented cameras” that can recognize persons and events taking place, and take action, making photos and videos at moments and topics that the AI, rather than the human photographer deemed as worthy (see, e.g. Google Clips: https://www.theverge.com/2017/10/4/16405200/google-clips-camera-ai-photos-video-hands-on-wi-fi-direct). This development can go into multiple directions. There are already smart surveillance cameras, for example, that learn to recognize the family members, and differentiate them from unknown persons entering the house, for example. Such a camera, combined with a conversant backend service, can also serve the human users in their various information needs: telling whether kids have come home in time, or in keeping track of any out-of-ordinary events that the camera and algorithms might have noticed. In the below video is featured Lighthouse AI, that combines a smart security camera with such an “interactive assistant”:
In the domain of amateur (and also professional) photographer practices, AI also means many fundamental changes. There are already add-on tools like Arsenal, the “smart camera assistant”, which is based on the idea that manually tweaking all the complex settings of modern DSLR cameras is not that inspiring, or even necessary, for many users, and that a cloud-based intelligence could handle many challenging photography situations with better success than a fumbling regular user (see their Kickstarter video at: https://www.youtube.com/watch?v=mmfGeaBX-0Q). Such algorithms are already also being built into the cameras of flagship smartphones (see, e.g. AI-enhanced camera functionalities in Huawei Mate 10, and in Google’s Pixel 2, which use AI to produce sharper photos with better image stabilization and better optimized dynamic range). Such smartphones, like Apple’s iPhone X, typically come with a dedicated chip for AI/machine learning operations, like the “Neural Engine” of Apple. (See e.g. https://www.wired.com/story/apples-neural-engine-infuses-the-iphone-with-ai-smarts/).
Many of these developments point the way towards a future age of “computational photography”, where algorithms play as crucial role in the creation of visual representations as optics do today (see: https://en.wikipedia.org/wiki/Computational_photography). It is interesting, for example, to think about situations where photographic presentations are constructed from data derived from myriad of different kinds of optical sensors, scattered in wearable technologies and into the environment, and who will try their best to match the mood, tone or message, set by the human “creative director”, who is no longer employed as the actual camera-man/woman. It is also becoming increasingly complex to define authorship and ownership of photos, and most importantly, the privacy and related processing issues related to the visual and photographic data. – We are living interesting times…
In the 1970s and 1980s the concept ‘cognitive engineering’ was used in the industry labs to describe an approach trying to apply cognitive science lessons to the design and engineering fields. There were people like Donald A. Norman, who wanted to devise systems that are not only easy, or powerful, but most importantly pleasant and even fun to use.
One of the classical challenges of making technology suit humans, is that humans change and evolve, and differ greatly in motivations and abilities, while technological systems tend to stay put. Machines are created in a certain manner, and are mostly locked within the strict walls of material and functional specifications they are based on, and (if correctly manufactured) operate reliably within those parameters. Humans, however, are fallible and changeable, but also capable of learning.
In his 1986 article, Norman uses the example of a novice and experienced sailor, who greatly differ in their abilities to take the information from compass, and translate that into a desirable boat movement (through the use of tiller, and rudder). There have been significant advances in multiple industries in making increasingly clear and simple systems, that are easy to use by almost anyone, and this in turn has translated into increasingly ubiquitous or pervasive application of information and communication technologies in all areas of life. The televisions in our living rooms are computing systems (often equipped with apps of various kinds), our cars are filled with online-connected computers and assistive technologies, and in our pockets we carry powerful terminals into information, entertainment, and into the ebb and flows of social networks.
There is, however, also an alternative interpretation of what ‘cognitive engineering’ could be, in this dawning era of pervasive computing and mixed reality. Rather than only limited to engineering products that attempt to adapt to the innate operations, tendencies and limitations of human cognition and psychology, engineering systems that are actively used by large numbers of people also means designing and affecting the spaces, within which our cognitive and learning processes will then evolve, fit in, and adapt into. Cognitive engineering does not only mean designing and manufacturing certain kinds of machines, but it also translates into an impact that is made into the human element of this dialogical relationship.
Graeme Kirkpatrick (2013) has written about the ‘streamlined self’ of the gamer. There are social theorists who argue that living in a society based on computers and information networks produces new difficulties for people. Social, cultural, technological and economic transitions linked with the life in late modern, capitalist societies involve movements from projects to new projects, and associated necessity for constant re-training. There is necessarily no “connecting theme” in life, or even sense of personal progression. Following Boltanski and Chiapello (2005), Kirkpatrick analyses the subjective condition where life in contradiction – between exigency of adaptation and demand for authenticity – means that the rational course in this kind of systemic reality is to “focus on playing the game well today”. As Kirkpatrick writes, “Playing well means maintaining popularity levels on Facebook, or establishing new connections on LinkedIn, while being no less intensely focused on the details of the project I am currently engaged in. It is permissible to enjoy the work but necessary to appear to be enjoying it and to share this feeling with other involved parties. That is the key to success in the game.” (Kirkpatrick 2013, 25.)
One of the key theoretical trajectories of cognitive science has been focused on what has been called “distributed cognition”: our thinking is not only situated within our individual brains, but it is in complex and important ways also embodied and situated within our environments, and our artefacts, in social, cultural and technological means. Gaming is one example of an activity where people can be witnessed to construct a sense of self and its functional parameters out of resources that they are familiar with, and which they can freely exploit and explore in their everyday lives. Such technologically framed play is also increasingly common in working life, and our schools can similarly be approached as complex, designed and evolving systems that are constituted by institutions, (implicit, as well as explicit) social rules and several layers of historically sedimented technologies.
Beyond all hype of new commercial technologies related to virtual reality, augmented reality and mixed reality technologies of various kinds, lies the fact that we have always already lived in complex substrate of mixed realities: a mixture of ideas, values, myths and concepts of various kinds, that are intermixed and communicated within different physical and immaterial expressive forms and media. Cognitive engineering of mixed reality in this, more comprehensive sense, involves involvement in dialogical cycles of design, analysis and interpretation, where practices of adaptation and adoption of technology are also forming the shapes these technologies are realized within. Within the context of game studies, Kirkpatrick (2013, 27) formulates this as follows: “What we see here, then, is an interplay between the social imaginary of the networked society, with its distinctive limitations, and the development of gaming as a practice partly in response to those limitations. […] Ironically, gaming practices are a key driver for the development of the very situation that produces the need for recuperation.” There are multiple other areas of technology-intertwined lives where similar double bind relationships are currently surfacing: in social use of mobile media, in organisational ICT, in so-called smart homes, and smart traffic design and user culture processes. – A summary? We live in interesting times.
– Boltanski, Luc, ja Eve Chiapello (2005) The New Spirit of Capitalism. London & New York: Verso.
– Kirkpatrick, Graeme (2013) Computer Games and the Social Imaginary. Cambridge: Polity.
– Norman, Donald A. (1986) Cognitive engineering. User Centered System Design, 31(61).