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image by Zeynep Saygin, from “A Beautiful Brain” exhibition at MIT Museum

I ventured to the Northeast this week: Providence, RI and Cambridge, MA. In part, I did this to get inspired by emerging talent and technologies. In part, to uncover unaddressed skills that we’ll need to add to our teams — through training or hire. I spent time at Rhode Island School of Design — and saw quite a bit of inspiration––and started to form some early opinions on the skills that are emerging, where companies are investing, and what might prove most advantageous for the seasoned designer, looking to up their game.
I also spent two humbling days at EmTech, an annual conference on the MIT Campus, sponsored by MIT Technology Review. It was packed with academic and industry experts speaking about emerging technologies like Big Data, Blockchain, Robotics, Quantum Computing and Genetics. It was fascinating — and more than a few times, quite over my head. Interspersed, MIT introduced 35 Innovators Under 35, each of whom had a 3 minute opportunity to describe their breakthrough work across diverse disciplines.
Needless to say, my brain is full, my heart is beating a little faster, and I am only just starting to form my opinions on where designers will be most helpful in the next ten years of this amazing technology age.

Data visualization has long been framed as graphs, charts and the occasional dashboard. But a true, untapped opportunity for designers to lead will lie in their ability to illustrate the data concepts of Data “states” (dead, fluid, calc’d/dependent), Data Movement (direction, velocity, frequency), Data output v. Data input (what is this data dependent on? What depends on this data?), Data arrangement (associations, priority), Data attributes (‘weight’, sensitivity), Data pathways (the “tubes” through which data is channeled), Data sensitivity (security, privacy), Data accuracy (cleanliness, confidence).
How might our trust in an algorithm change with a visual understanding of its assumptive underpinnings? What might we learn from the data-equivalent of a dye test? How would illustrating the source, flow and destination of data help us better understand its creation, agency, custody, and security?
Again, the dynamic visualizations of your heart rate and calories burned are useful customer experiences — but as we endeavor to leverage millions of data points to automate decision-making for everything from when a self-driving car should change lanes to when components of critical infrastructure should be replaced, this data transparency and storytelling will become incredibly powerful for stakeholders beyond engineers. And as data and UI merge, those that do both well will be in demand.

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“Lost in My Life”, by Rachel Perry, a work from MIT LIST Student Art Loan Program

Building on the idea of making big data more transparent, a designer will need to demonstrate skill for addressing complexity of overlapping systems AND distill that complexity down to simple ideas, stories, actions and outcomes without losing the complex context. As we’ve seen with endeavors like service and systems design, being able to zoom out and zoom in, handle the gestalt of a brand or service and also sweat the details of a 1–3 second moment has become imperative. When to do what, even more so. These are not the competency of your average “UI/UX Designer”. They take experience, curiosity, deep research and technical acumen for rendering the right detail that is helpful. While simplicity has ALWAYS been the call of the designer (thank you John Maeda), appreciating and designing for the right complexity will require slightly different wiring, more akin to architecture mixed with theatrical set and light design.

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A slide from Katie Rae’s talk about Tough Tech

This might not even sound like a skill. But the world needs design talent who will partner with scientists and engineers who care about making progress on really hard problems. Work that takes decades. As Katie Rae from The Engine puts it, “this work takes guts.” I learned one of the greatest failings of emerging technology is that it gets stuck in the lab — outlasting sponsors, funding, the attention span of VCs and the patience of talent. In the business of software, “speed to benefit” is a critical metric, and rightly so. That metric needs to be reframed for ambitions on a larger scale. “Important, incremental goals with value inflection points.” And our talents’ expectations need to be reset accordingly. Especially as our culture has grown unaccustomed to waiting, the idea of investing your career in long-term, fuzzy outcomes is a hard sell for talent surrounded by colleagues making good money on short-term opportunities. But design is needed here maybe most of all: to tell the unfinished story, to frame the human opportunity, to paint the eventuality, and progress to date.
I was surprised how many innovators were reluctant, undisciplined or just plain unprepared to answer questions about whether their area of focus might be of use to the Department of Defense, or similar. It felt like a disconnect, that despite these well-researched, methodically tested, empirically proven technologies, that these ethically-charged decisions weren’t grounded in principles, framed with data, or delivered with confidence — only the sheepish acknowledgement that most technologies have a shadow of nefarious or unintended use. Certainly, though, it’s everyone’s job to spend time and rationale framing the explicit, intended paths? Design can lead there.

The combination of increasing complexity, exponential creation of and leveraging of data, and larger, ever fuzzier implications of technology-driven services, experiences and products means we’ll need designers who are well-versed in the skills of critique, reason and influence. Today, we have rationale — decisions framed with intent, principled criteria, qualitative and quantitative context, a competitive lens, a designer’s gut/POV. But as the impact of our decisions expands with the scale and reach of these new technologies, so does our responsibility. Everything from hypothesis creation to test-modeling to results interpretation will require designers to stretch beyond––but not turn our backs on––our own intuition. That intuition must now be informed, and in many cases swayed, by comprehensive data analysis.

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Mikhail Mansion’s Algorithmic animations of jellyfish, based on research by Dr. John Costello, part of the BioDesign Exhibition at RISD’s Woods Gerry Gallery

Of course designers’ role as champion of humans, as the first line of defense when it comes to questioning the motives to innovate, and as framers of emotional, not just functional need should remain unwavering. Our passion for action-inspiring aesthetics. Our curiosity about human behavior, especially when it contradicts logic. Our experiments that push the boundaries of WHY. Still valuable — in the next 10 years very much as now.

What skills are you honing to stay current, marketable, and addressing the next generation of design and technology challenges?

Written by

Design Leader, Advisor, Speaker, Student, Advocate, Enabler.

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