Most experienced user researchers will recognise the following: When doing a user test, the things participants say during the interview not always match their facial expressions or how they acted during the test. They seem unable to explain what they, unconsciously, feel or think. To counter this behaviour, we designed the Emogram that helps (student) design researchers capture (unconscious) emotional and intuitive responses of research participants with as little rationalisation by the participants as possible. The work of Daniel Kahneman [1] is used to explain how the Emogram works cognitively. Kahneman showed that the human brain uses two systems to form thoughts: system 1, intuitive and fast, and system 2, rational and slow. System 1 reacts almost immediately while system 2 thinks things over and tries to rationalise the response of system 1. The continues battle between these systems influences the response of research participants. Because of this, inexperienced design students can easily be put on the wrong foot as they are still learning how to read participant responses. Not much is needed to do an Emogram: paper, pencil and some sticky notes will suffice. However, because participants sometimes feel that they don’t have enough time to complete the Emogram, also a web version is being developed. The tool is ‘work in progress’ and there are several issues that need further research. However, first experiences are that student researchers acquire more accurate insights about the participants unconscious thoughts in relation to product design
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Over the past few years a growing number of artists have critiqued the ubiquity of identity recognition technologies. Specifically, the use of these technologies by state security programs, tech-giants and multinational corporations has met with opposition and controversy. A popular form of resistance to recognition technology is sought in strategies of masking and camouflage. Zach Blas, Leo Selvaggio, Sterling Crispin and Adam Harvey are among a group of internationally acclaimed artists who have developed subversive anti-facial recognition masks that disrupt identification technologies. This paper examines the ontological underpinnings of these popular and widely exhibited mask projects. Over and against a binary understanding and criticism of identity recognition technology, I propose to take a relational turn to reimagine these technologies not as an object for our eyes, but as a relationship between living organisms and things. A relational perspective cuts through dualist and anthropocentric conceptions of recognition technology opening pathways to intersectional forms of resistance and critique. Moreover, if human-machine relationships are to be understood as coming into being in mutual dependency, if the boundaries between online and offline are always already blurred, if the human and the machine live intertwined lives and it is no longer clear where the one stops and the other starts, we need to revise our understanding of the self. A relational understanding of recognition technology moves away from a notion of the self as an isolated and demarcated entity in favour of an understanding of the self as relationally connected, embedded and interdependent. This could alter the way we relate to machines and multiplies the lines of flight we can take out of a culture of calculated settings.
We examined the neural correlates of facial attractiveness by presenting pictures of male or female faces (neutral expression) with low/intermediate/high attractiveness to 48 male or female participants while recording their electroencephalogram (EEG). Subjective attractiveness ratings were used to determine the 10% highest, 10% middlemost, and 10% lowest rated faces for each individual participant to allow for high contrast comparisons. These were then split into preferred and dispreferred gender categories. ERP components P1, N1, P2, N2, early posterior negativity (EPN), P300 and late positive potential (LPP) (up until 3000 ms post-stimulus), and the face specific N170 were analysed. A salience effect (attractive/unattractive > intermediate) in an early LPP interval (450–850 ms) and a long-lasting valence related effect (attractive > unattractive) in a late LPP interval (1000–3000 ms) were elicited by the preferred gender faces but not by the dispreferred gender faces. Multi-variate pattern analysis (MVPA)-classifications on whole-brain single-trial EEG patterns further confirmed these salience and valence effects. It is concluded that, facial attractiveness elicits neural responses that are indicative of valenced experiences, but only if these faces are considered relevant. These experiences take time to develop and last well beyond the interval that is commonly explored.
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