Social psychology – guerillagirl – user experience designer

Orga culture and UX: Competition vs common vision

Image: Cooperation, exemplary image. ;)

The famous robbers cave field experiment conducted by Muzafer Sherif (1954, 1958, 1961) investigated how and why group conflicts occur.

Sherif argued that conflict between groups (intergroup conflicts) occur in case of two groups are in competition for limited resources (like e.g recognition etc)

The research group arranged an artificial competitional environment (which does not necessarily reflect real life conditions) where friction conflict and frustration between the groups was likely to occur.It didn’t take long and the predictions of the researchers came true, the two groups had become strong rivals and behaved hostile to each other. The conflicts only subsided as the researchers began to create situations in which the opposing groups had to solve problems together, thus creating a common goal and vision to achieve these goals.

Sherifs studies could teach us a little bit about organizational conflicts like eg silo thinking, political and ego driven processes, etc – which we are often confronted with in our work as experience designers and which have a direct impact on product development and at the end of the day: the users’s experience. The experiemnts also emphasize how important it is to have common goals and therefore a common vision.

The study was and is ethically questionable and was also biased. Nevertheless I think it can teach us about how intergroup conflicts occur, what to do against it – also in organizational structures and teams.

Reference:
Sherif, M. (1954). Experimental study of positive and negative intergroup attitudes between experimentally produced groups: robbers cave study.

Friend or foe? Social presence is an important factor to consider in Interaction /UX Design

Ever yelled at your computer? Congrats! You’re in good company applying social responses to inanimate things. We as humans are wired to be social creatures. And even digital products may trigger social responses and you might not even be aware of it.

Often, computing technology conveys some sort of social presence. Resulting to that fact people do respond to this technology often as though the technology item is a social entity like eg another human (For reference on that see e.g Reeves, B. and Nass, C. ;1996. The Media Equation: How People Treat Computers, Television, and New Media Like Real People and Places, Stanford University)

Here are a few examples how social presence is conveyed (among other things):

Fig 01: Keepon, a social robot/beatbot for autistic children

Keepon is a computing technology in form of a robot. It conveys social presence for us humans through (obvious) physical cues like a face. It has eyes and also some physical skills like it starts dancing/moving and making funny noises when it listens to music or when you interact with it.

Fig 02: Siri, a voice based digital assistant

Also, voice based digital assistants like Siri convey – in this case despite their very futuristic and techy appearance – social presence through language cues but also through social roles like gender which we implicitly perceive. We will imply implicit assumptions and personality behind it – despite we are knowing it is a machine.

Fig 03: Unhelpful error message found in moodle a while ago

But of course, also technology with no obvious physical cues like faces or other cues like voice/spoken language at all can convey social presence. For example simply in presenting an error message, respectively by using written language/plain copy to communicate with a human. The example error message above is not providing any helpful hint what exactly has happened/has gone wrong and also it uses a strange language (It says: Error found. Error only could be removed by a programmer. Course not usable) – so I will attribute this behavior to the product/company behind it: eg they are blaming me for that error only a programmer can remove, so they are unhelpful and they don’t care about me /their customers/users etc.

So, in all these cases, considering theories provided by social psychology research and lessons learned from human-to-human interaction can serve as a valuable source of information and also guidance when it comes to making design decisions for interactive products or any computing technology. For better understanding, I recommend trying out how the communication would be perceived if it were a human-to-human interaction instead of a human-computer interaction. This works quite well in e.g a role-playing game within your team. One is the user while the other person is playing the computer or application. So you can pay attention to how the communication will feel like. Another way may be simply writing down the interaction as a System/User dialogue and behavior, considering the System as a character.

With that in mind, I’ll leave you with Paul Watzlawick’s “One cannot not communicate”.

Gender stereotypes applied to machines

Amongst other things when it comes to gender stereotyping, studies show that dominant behavior by males tends to be positively received by western society since dominant men tend to be perceived as “independent”,“assertive“ and „successful“, whereas dominant women tend to be perceived as “pushy” or “bossy”.

Nass et al did a series of studies in the late 90s to determine if computers trigger the same scripts and cognitive schemas associated with gender stereotyping – as they conducted an experiment they found out their hypothesis that people mindlessly apply gender stereotypes to computers were supported.

During this experiment, participants used computers for three separate sessions:
a) tutoring (via voice output), b) testing (screen-based), and c) evaluation (via voice output).

„The results supported the hypothesis that individuals would mindlessly gender-stereotype computers. Both male and female participants found the female-voiced evaluator computer to be significantly less friendly than the male-voiced evaluator, even though the content of their comments was identical. In addition, the generally positive praise from a male-voiced computer was more compelling than the same comments from a female-voiced computer: Participants thought the tutor computer was significantly more competent (and friendlier) when it was praised by a male-voiced computer, compared to when it was praised by a female-voiced computer. And finally, the female-voiced tutor computer was rated as significantly more informative about love and relationships compared to the male-voiced tutor, while the male-voiced tutor was rated as significantly more informative about computers.“

(Nass et al., 1997).