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Putting People First

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April 2013
2 April 2013

Michele Visciola speaking on ‘Town_Re-coding’

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On 11 April, Experientia president Michele Visciola will be a guest speaker at the Town Re-coding seminar (pdf), a Turin event to discuss perceptions, tensions and actions for change in the physical and social spaces of cities.

The Italian-language seminar involves the Polytechnic of Turin, the University of Turin, the Alma Mater Studiorum, and the University of Bologna.

The Turin initiative is part of a wider series that started with an inaugural event in Ravenna ten days ago, and will conclude in a conference – again in Ravenna – on 28-30 June 2013.

Guest speakers at the Turin seminar will explore new models for economy and consumption, and ways to reimagine urban spaces.

Michele will speak on “Ethnographic Research and the Evolution of Culture,” looking at ways to positively design and shape changes in the urban arena, so that they will be easily and sustainably adopted by people.

Michele has published multiple articles on behavioural change and participatory design in urban environments, and on natural selection in cultural innovation.

2 April 2013

An uplifting experience – the ethnography of the elevator user experience

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Rebekah Rousi, a researcher of user psychology and PhD candidate of Cognitive Science at the University of Jyväskylä, Finland, describes on EthnographyMatters how the combination of qualitative and quantitative data collection was fruitful in her analysis of elevator usage.

“A few years ago a leading elevator design and manufacturing company gave me the task of examining how people experienced and interacted with elevators. The scope included everything from hall call buttons, to cabin interior design and perception of technical design. When given the brief, the artistic director noted country specific design features (or omissions) and even mentioned that there may be observable elevator habits I would want to take note of. Then, on our bidding a corporate-academic farewell she added that I might want to consider the psychology of the surrounding architectural environment. With that, I was left with a long list of to-do’s and only one method I could think of that would be capable of incorporating so many factors – ethnography. Ethnographic inquiry provides a framework in which the researcher’s own observations and experiences of the phenomenon under study – in this case elevator users’ behaviour in relation to the elevators, other users and the surrounding architectural environment – can be combined with “insiders’” opinions and insights.”

2 April 2013

Why data without soul is meaningless

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As we move towards a quantified society, one shaped by data, we start to dismiss things that are unquantified, writes Om Malik of GigaOm. Empathy, emotion and storytelling — these are as much a part of business as they are of life.

“The problem with data is that the way it is used today, it lacks empathy and emotion. Data is used like a blunt instrument, a scythe trying to cut and tailor a cashmere sweater.” [...]

“What will it take to build emotive-and-empathic data experiences? Less data science and more data art — which, in other words, means that data wranglers have to develop correlations between data much like the human brain finds context. It is actually not about building the fanciest machine, but instead about the ability to ask the human questions. It is not about just being data informed, but being data aware and data intelligent.”

2 April 2013

The hidden biases in Big Data

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Data and data sets are not objective, writes Kate Crawford, principal researcher at Microsoft Research, in the Harvard Business Review.

They are creations of human design. We give numbers their voice, draw inferences from them, and define their meaning through our interpretations. Hidden biases in both the collection and analysis stages present considerable risks, and are as important to the big-data equation as the numbers themselves.

She argues that the next frontier is how to address these weaknesses in big data science.

“Social science methodologies may make the challenge of understanding big data more complex, but they also bring context-awareness to our research to address serious signal problems. Then we can move from the focus on merely “big” data towards something more three-dimensional: data with depth.”