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Lou and Cee Cee prepare for fieldwork in the future: a world where robots conduct ethnography


dudek-hi-res-headshotNote from the Editor, Tricia Wang: Kicking off our Co-designing with machines edition is Alicia Dudek (@aliciadudek), Innovation Insight Lead & Design Ethnographer at Deloitte Digital Australia. Using design thinking, ethnography, and other deep contextual customer research methods, she designs, conducts, and trains others in the world of customer empathy. Her contribution to this edition is the first science fiction to explore robots conducting ethnographic work. She uses a fictional story with Cee Cee, the robo-ethnographer, to examine what aspects of fieldwork can be conducted by a robot. I first met Alicia Dudek at an EPIC conference in London, where I became a fan of her work and promptly interviewed her for our edition that featured the best from EPIC. Read the interview, Play nice – design ethnographer meets management consultant, and find more of her writings on ethnography at her site.

Increasingly we are seeing more conversations about ‘what does it look like when the robots take your job.’ Once upon a time we believed this was some remote future where we’d finally invented the technology that could replace our bio-body’s ingenious functions. Now we are coming into a time where our technology has grown so advanced that the replacement of ourselves with robots is not only imagined, but plausible and even possible. An example of this shift is the imagining of white collar jobs ‘going robo’ that was recently covered by Quartz.

Writing this piece I wanted to have a little fun imagining a wonderful world where we can work hand in hand with robot peers. It is exciting to imagine the day when artificial intelligence is on par with that of our human research team members. Ethnographic technology is sometimes slow to progress due to the art and science nature of our work, but if we had the magic wand to unite all the drones, phones, data smarts, and humanly arts, we might have robo-colleagues as a part of our team one day soon. Friendly humans and friendly robots conducting ethnography together are a powerful combination. Also thank you to Elizabeth Dubois for writing this piece about trace interviews, which has some cool ideas on how we might conduct interviews.

– Alicia Dudek

Lou muses over her tea

Lou muses over her tea as she prepares for fieldwork with Cee Cee.

Lou mused over the steam rising from her cup of tea. She gathered her thoughts around what she’d be looking for in the field next week. She and her team were going to shadow young families and understand how they managed their finances. Field work was always one of the most exciting and exhausting parts of the data collection in her ethnography projects. What would be the right focus area for a trip into this family’s everyday life? She knew she’d have to cover the basics of bank accounts, credit cards, laptop / tablet / phone usage, calendar keeping, overall scheduling, family diaries, but what else might be valuable? What else could help to point the team in the direction of the golden nuggets of insight? All these years of traipsing in and out of the field and analysing scores of transcripts, videos, audios had left her always questioning, what’s next? What were the mental parameters that led her to the deep and meaningful insights from field observations? What was that ineffable thing that clients kept hiring her for again and again? How does an ethnographer see differently to find the golden nuggets?

Lou was jostled out of this reverie as Cee Cee energetically buzzed into the office and landed on Louise’s desk with a plop. “Louise I’m here for my briefing for the field work to be conducted.” Lou looked up from her imagined fieldwork and focused on Cee Cee’s entry into her office. In the past Lou had had dozens of assistants, grad students, and junior ethnographers to help with her work. None of them was quite like Cee Cee, who was rather innovative and definitely pushed Lou’s ways of working to new places. “Alright Cee Cee let’s get going on the briefing and I’ll tell you what we’re looking for and how to behave when you get out there.” Lou readjusted her posture and swung around to meet Cee Cee head on and get into the briefing.Read More… Lou and Cee Cee prepare for fieldwork in the future: a world where robots conduct ethnography

Co-designing with machines: moving beyond the human/machine binary



web-7525squareLetter from the Editor: I am happy to announce the The Co-Designing with Machines edition. As someone with one foot in industry redesigning organizations to flourish in a data-rich world and another foot in research, I’m constantly trying to take an aerial view on technical achievements. Lately, I’ve been obsessed with the future of design in a data-rich world increasingly powered by of artificial intelligence and its algorithms. What started out over a kitchen conversation with my colleague, Che-Wei Wang (contributor to this edition) about generative design and genetic algorithms turned into a big chunk of my talk at Interaction Design 2016 in Helsinki, Finland. That chunk then took up more of a my brain space and expanded into this edition of Ethnography Matters, Co-designing with machines. In this edition’s introductory post, I share a more productive way to frame human and machine collaboration: as a networked system. Then I chased down nine people who are at the forefront of this transformation to share their perspectives with us. Alicia Dudek from Deloitte will kick off the next post with a speculative fiction on whether AI robots can perform any parts of qualitative fieldwork. Janet Vertesi will close this edition giving us a sneak peak from her upcoming book with an article on human and machine collaboration in NASA Mars Rover expeditions. And in between Alicia and Janet are seven contributors coming from marketing to machine learning with super thoughtful articles. Thanks for joining the ride! And if you find this to be engaging, we have a Slack where we can continue the conversations and meet other human-centric folks. Join our twitter @ethnomatters for updates. Thanks. @triciawang

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Who is winning the battle between humans and computers? If you read the headlines about Google’s Artificial Intelligence (AI), DeepMind, beating the world-champion Go player, you might think the machines are winning. CNN’s piece on DeepMind proclaims, “In the ultimate battle of man versus machine, humans are running a close second.” If, on the other hand, you read the headlines about Facebook’s Trending News Section and Personal Assistant, M, you might be convinced that the machines are less pure and perfect than we’ve been led to believe. As the Verge headline puts it, “Facebook admits its trending news algorithm needs a lot of human help.”

The headlines on both sides are based in a false, outdated trope: The binary of humans versus computers. We’re surrounded by similar arguments in popular movies, science fiction, and news. Sometimes computers are intellectually superior to humans, sometimes they are morally superior and free from human bias. Google’s DeepMind is winning a zero-sum game. Facebook’s algorithms are somehow failing by relying on human help, as if collaboration between humans and computers in this epic battle is somehow shameful.

The fact is that humans and computers have always been collaborators. The binary human/computer view is harmful. It’s restricting us from approaching AI innovations more thoughtfully. It’s masking how much we are biased to believe that machines don’t produce biased results. It’s allowing companies to avoid taking responsibility for their discriminatory practices by saying, “it was surfaced by an algorithm.” Furthermore, it’s preventing us from inventing new and meaningful ways to integrate human intelligence and machine intelligence to produce better systems.

giphyAs computers become more human, we need to work even harder to resist the binary of computers versus humans. We have to recognize that humans and machines have always interacted as a symbiotic system. Since the dawn of our species, we’ve changed tools as much as tools have changed us. Up until recently, the ways our brains and our tools changed were limited to the amount of data input, storage, and processing both could handle. But now, we have broken Moore’s Law and we’re sitting on more data than we’re able to process. To make the next leap in getting the full social value out of the data we’ve collected, we need to make a leap in how we conceive of our relationships to machines. We need to see ourselves as one network, not as two separate camps. We can no longer afford to view ourselves in an adversarial position with computers.

To leverage the massive amount of data we’ve collected in a way that’s meaningful for humans, we need to embrace human and machine intelligence as a holistic system. Despite the snazzy zero-sum game headlines, this is the truth behind how DeepMind mastered Go. While the press portrayed DeepMind’s success as a feat independent of human judgement, that wasn’t the case at all. Read More… Co-designing with machines: moving beyond the human/machine binary