By MARIA CURY, MIKKEL KRENCHEL and MILLIE P. ARORA, ReD Associates
To influence the development of artificial intelligence, ethnographers must build more partnerships and new kinds of outputs.
Artificial intelligence (AI) has made huge strides recently in areas like natural language processing and computer-generated images – every other week seems to bring another breathtaking headline. Engineers, developers, and policymakers in the AI community are more seriously grappling with the fundamental risks that AI poses to society, like perpetuating unfair biases, putting privacy and security at risk, harming mental health, or automating tasks that provide livelihoods for people. As people flock to the fields of 'responsible AI,’ ‘AI ethics,’ and ‘AI governance’ that are all about shaping AI towards what is helpful for humanity, it is time we ask: where are the ethnographers and applied anthropologists?
Many are doing ground-breaking work in AI, and reporting back to the EPIC community (see here, here, here, also here for just...
By MIKKEL KRENCHEL, ReD Associates
Three strategies for designing research that captures the social forces shaping people's behavior.
Remember the days when a main challenge of the EPIC community was convincing executives that humans weren’t just rational actors all the time? Back when arguing for the value of ethnographic research, thick data, and so forth, started with getting executives to realize that there was more to people than what could be observed through a spreadsheet?
Fortunately, those days are long gone. Today, most successful leaders of large corporations readily embrace the idea that humans are complex, emotional creatures and that the success of their business in large part rests on making the right bets on how they will behave. In response, research departments across the corporate world have grown exponentially in both size and sophistication, and ‘ethnographic research’ as a term has almost gone mainstream.
It would be easy to conclude that it’s time to declare victory. But if you look a little closer...
Facebook Reality Labs
The not-too-distant future may bring more ubiquitous personal computing technologies seamlessly integrated into people's lives, with the potential to augment reality and support human cognition. For such technology to be truly assistive to people, it must be context-aware. Human experience of context is complex, and so the early development of this technology benefits from a collaborative and interdisciplinary approach to research — what the authors call “hybrid methodology” — that combines (and challenges) the frameworks, approaches, and methods of machine learning, cognitive science, and anthropology. Hybrid methodology suggests new value ethnography can offer, but also new ways ethnographers should adapt their methodologies, deliverables, and ways of collaborating for impact in this space. This paper outlines a few of the data collection and analysis approaches emerging from hybrid methodology, and learnings about impact and team collaboration,...
MILLIE P. ARORA
As algorithms play an increasingly important role in the lives of people and corporations, finding more effective, ethical, and empathetic ways of developing them has become an industry imperative. Ethnography, and the contextual understanding derived from it, has the potential to fundamentally change the way that data science is done. Reciprocally, engaging with data science can help ethnographers focus their efforts, build stronger and more precise insights, and ultimately have greater impact once their work is incorporated into the algorithms that increasingly power our society. In practice, building contextually-informed algorithms requires collaboration between human science and data science teams who are willing to extend their frame of reference beyond their core skill areas. This paper aims to first address the features of ethnography and data science that make collaboration between the two more valuable than the sum of their...
CHRISTIAN MADSBJERG, MIKKEL KRENCHEL, MORGAN RAMSEY-ELLIOT and GITTE HESSELHOLT
In business thinking, ‘core competencies’ have long been seen as the critical factor that distinguishes great from good. Great companies have strong core competencies that they constantly leverage and develop. On the other hand, companies who do not understand their own strengths and weaknesses cannot execute at the highest proficiency. Their growth initiatives fail, not because they lack commercial potential, but because they fail to apply the same due diligence to their competencies they so naturally apply to their finances. Understanding competencies entails understanding culture, and few companies know how to approach this topic beyond the gut feel analyses of executives or the rare employee survey. In this paper, we use a large-scale study for the medico company Coloplast as a case for how to use ethnography to rigorously study competencies and leverage growth. We show how understanding the effects of culture and competence on market performance...