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ADP’s Martha Bird on the ground at CES 2020 to talk about NLP/ML and AI, plus the top 5 themes for 2020


ADP’s business anthropologist, Martha Bird, reports on the top five themes at the 2020 Consumer Electronics Show that are important for today’s industry leaders.

With over 4,000 exhibiting companies, 2.9 million square feet of exhibit space, attracting more than 180,000 attendees and 307 Fortune 500 companies, there was a lot to take in at CES 2020 in Las Vegas. Some of the most innovative technologies to come included a flying taxi (Hyundai), electric multi-modal transportation, electric vertical take-off and landing craft (Uber), cool and creepy robotics, green and sustainability tech, 8K bezel-less TVs (Samsung), AI attended drive thru (McDonald’s lab), 150 digital health exhibitors and so much more. Within this tech frenzy, it was my great pleasure to represent ADP on stage and in studio where I discussed how natural language processing, machine learning and artificial intelligence (NLP/ML and AI), in general, is impacting the workplace – the tools, the processes and the people.

While it was impossible to see everything given the sheer magnitude of the event, there are some high-level reflections on what I consider to be the pervasive themes from this year’s event that industry leaders should keep their eyes and ears open for moving into 2020. These are my top five:

1. 5G: Data, data, and more data

On the CES floor, data was the common denominator across products and services on display and those demoed. Given the explosion of data contingent technologies, online privacy and security was a central talking point. How different regions address security concerns around data and privacy was less explicitly articulated although a continuum of highly private to blatantly public could be surmised. Along with a definite trend toward the true consumerization of AI.

Which brings me to 5G. In the next two to three years, networks will expand out exponentially. The first commercial deployments are already being seen but 5G is still in its infancy so it won’t be a matter of simply “flipping a switch” from 4G to 5G.

Along with 5G – increased speed, greater capacity and lower latency – comes huge possibilities for disruptive innovations. There was no limit to 5G talk and imagination at CES 2020. And, of course, there were both pronouncements and announcements on the topic around the coming of 5G handsets. AT&T and Verizon are aggressively developing the infrastructure in an attempt to get out ahead of competition across the globe.

5G will be the “central nervous system of the data age,” according to Steve Koenig, VP, Research at the Consumer Technology Association (CTA).

Martha Bird and others and CES 2020

[Inset above] ADP’s Business Anthropologist Martha Bird (right) took the stage at CES 2020. Bird’s panel “Emerging Technologies Enabling Enterprise” was moderated by Michael Miller, Editor-in-Chief at PC Magazine (middle) joined by fellow panelist Yonatan Wexler, Executive VP of R&D at OrCam Technologies (left).

2. IoI (Internet of Intelligence): The Decade of Connected Intelligence

Just as we were getting accustomed to the term IoT (Internet of Things) the talk this year was around IoI or “Internet of Intelligence.” This new way of thinking is a direct response to the way AI is being integrated into all facets of our technology and consumer culture.

We were told in the plenary keynote that as networks grow, we can expect 5G to unlock more opportunities for enterprise. Building upon what we’ve seen with IoT technologies (think smart home apps that rely on little bits of discrete data), the expansion of 5G and AI capabilities will provide multiple nodes of data informing a much more complex and inter-dependent data landscape. Enterprise applications are expected to lead in IoI in part because of massive data resources and the ability to form mutually beneficial partnerships between OEM, software and engineering. IoI covers things like remote robotic surgery and smart cities. Activities with a heavy data lift and, generally speaking, much higher stakes than let’s say a voice activated light in your home.

3. XR: The New Reality Training Our Future Workforce

XR – the latest technology encompassing augmented, virtual, and mixed reality technologies. Think virtual world up, down, left, or right, and experienced in 360 degrees. Form factors delivering this technology ranged from 5K gaming chairs to sleek eye glasses very much unlike the early Google glasses. Again, enterprise will have a big stake in this area with many use cases including B2B workforce training, safety inspections, AR glasses used by an architect to design a room, training surgeons across geographies, and in travel and tourism where you are able to take a trip to a tropical island right from your living room. Frankly, I prefer the actual trip but foregoing the lines at the airport and customs does sound appealing. Regardless of my preference, there was a lot of excitement for XR in commercial and industrial settings. Not to mention eSports which realized $1 billion in net revenue last year alone.

4. Culture: Pragmatics of Technological Innovation

While attending a panel discussion on “Future Cities” I was struck by a similarity between re-architecting an existing urban space to accommodate new technologies and the work we do at ADP.

A former secretary of transportation listed one of the greatest challenges to innovating cities as the pre-existing roadway infrastructure. He went on to say that between the legacy streets and traffic patterns it was actually the inability to imagine new ways of mobility that was the major barrier.

People get accustomed to “how things are done here” and find it difficult to adapt to changes in the system. This is a cultural and technical matter. Culture, at the most basic level, is the collection of practices and beliefs we take for granted. These habits are slow to change. New technical opportunities can catalyze innovation and cultural change, but this process is never a one-to-one.

Which brings me to humans.

5. Humans: Agency in a Data-driven Era

Humans (people like you and me) when faced with the explosion of new technologies – tech that augments our vision, our speech, our bodies and, even, our memory – begin to question their own reason for being. The existential ponderings around what it means to be human are concomitant with those group of technologies loosely described as “AI”.

Talk of “machine-human partnership” was pervasive on the CES exhibition floor and in panels and keynotes. For my part, I welcome the question as it points to a shared humanity that we often overlook. Yes, partnerships between people and technology will continue to evolve. Who has agency over the relationship will remain a critical point of personal reflection and public debate.

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Driving Innovation with Ethnography


Humans are typically curious by nature, but there’s a deep resource around human behavior that can be tremendously valuable as we design our strategies in business and life in general.

Cultural anthropologists combine curiosity and empirical science to deliver sustained value. They are trained to interpret and translate why people do the things they do and how unconscious and overlapping motivations influence their actions, their attitudes, their approach to the myriad people, products, politics and places of everyday life. We do this by spending time in the places where people make meaning, a method of inquiry known as ethnography. It’s what gets us excited, and it’s where we impact academia and industry.

Part of our work focuses on challenging the things we take for granted and, in so doing, encouraging new ways of looking at ideas, interactions and people we may have overlooked in the forgetfulness of the routine. Curiosity is our “rocket fuel.”

My colleague, Jay Hasbrouck, captures the spirit of the anthropological mindset when he writes, “When used as more than a research tool to expose consumer needs, ethnographic thinking helps companies and organizations build on the cultural meanings and contexts of their offerings, develop the flexibility to embrace cultural change, focus their strategies at critical cultural phenomena, and test and develop business model changes.”1

Where Ethnography Comes In

For those of us in the tech sector, in particular, the focus is quite aggressively on questions around data biases, including how algorithms are constructed and, ultimately, who they advantage and who they don’t. It’s a much bigger issue than simply “feeding the machine” and imagining that the outputs are somehow free of judgment. They’re not.

But, who should be responsible for exploring the roots of these biases? Biases that pre-exist “the machine learning” and biases that are already deeply embedded in culture. We hear a lot of blaming in the popular press about this or that platform creating unfair advantages. Nevertheless, should we leave it to data analysts and computer scientists to untangle these social inequalities? It seems a more appropriate area of investigation for those of us who study culture and the power flows that animate it.

So we begin to ask questions. What’s fair in a data-mediated world? What role does empathy play in communicating evidence and big data? What constitutes evidence in a global context, among others?

Placing blame on “flawed” algorithms and the companies on which data-driven services depend is really missing the critical point. We need to look outside the tech and start to get serious about the very non-technical realities that contribute to an unequal present and, consequently, an inevitably unequal future.

I’ve been giving a lot of thought to the admittedly broad subject of AI viewed from an anthropological perspective. My main goal in doing so is to further challenge the cultural category “AI” (big and small), while also exploring how ethnographic methodology (direct observation/active-listening) might help advance our understanding of the human and machine relationships forming here and now and tomorrow.

Specifically, I’m thinking about two main question areas. First, a definitional focus: How might we begin to articulate an ethnography of AI, what role might AI technologies play in the service of ethnographic practice, and how might (and does) ethnographic inquiry inform AI technologies? Second, a philosophical focus: Who is responsible for bias in data, in algorithms and in outcomes to include discussion around how work related to AI is currently organized within tech companies today?

As companies become increasingly reliant on data-driven insights to build their offerings, market their products and guide scope for future projects, we need to get serious about the reality that data isn’t “raw” or “clean” — but rather deeply reflective of the social and political circumstances from which they are pulled and to which they contribute. It’s an exciting time to be an anthropologist working in technology where the human is deeply enmeshed with the machine.

Martha Bird is a Business Anthropologist working in ADP’s Roseland Innovation Lab. She was selected to co-moderate a session at the premiere international ethnography event 2018 EPIC Conference October 9-12, 2018 in Honolulu.