Illustration from a 1940’s Bell Labs project investigating human speech synthesis and recognition

I recently signed up for SimulScribe, a new service which replaces your existing voicemail system with one that:

1. Transcribes the voice message into text (using a speech-to-text (STT) engine)…
2. wraps the voicemail message into a WAV file…
3. and then emails the raw text and the WAV file (as an attachment) to your email address.

Setting up SimulScribe couldn’t be easier: The free trial doesn’t even require a credit card to start using right away, and they provide you with explicit and shockingly simple instructions for configuring your voicemail for your particular carrier. You can be set up with the SimulScribe service in literally under 3 minutes.

After setting it up (and this may come has a shock to those of you who still think STT is not ready for prime time), the system has performed almost flawlessly.

Below I’ll present some example transcriptions, followed by some ideas on how this technology might be extended in the future. MORE…

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New technology products often take us by surprise. In 1992, for example, we couldn’t possibly have dreamed of how the Internet would transform the world by 1997, only 5 years later. The best innovations are things “you never knew you wanted but cannot live without” kind, inventions that come out of nowhere. YouTube, for example. Or TiVo.

But certain other technology products are so obvious that when they finally emerge many people shrug and wonder “what took it so long?” We knew they were coming, but year after year they never actually materialized.

When they do materialize, we are overjoyed. After years of waiting, for example, we are finally getting MP3 players into cel phones.We are using wireless networks and bluetooth more and more, but we knew we wanted this stuff years ago. The technology consumer will often heap glowing praise on these kinds of new technologies as they emerge, calling them innovative and groundbreaking, when in fact the functionality of the products is merely filling a hole that everyone knew was there.

The Apple iPhone is a perfect example: while the UI is indeed remarkable, almost nothing about it is technologically innovative or new. If you asked me (or just about any of my friends) to describe the perfect cel phone feature set, it would look a lot like an iPhone. In fact, as the owner of a Windows PocketPC phone for nearly 5 years, nothing about the iPhone’s tech specs surprised me. The UI, again, is great and very innovative, but the hardware itself and the basic concept of the device is wholly old news. MORE…

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“Let me tell you about my mother…”

In the movie Blade Runner, the “Voight-Kampff Empathy Test” detects whether or not a test subject is a real human being or an android “replicant”. A machine reads the body’s physical reactions to various psychologically- provocative scenarios (“Capillary dilation of the so-called blush response? Fluctuation of the pupil. Involuntary dilation of the iris…”) and reveals whether or not the test subject’s sense of empathy is consistent with that of a real human being.

There has always been a lot of talk about “empathy” in the information architecture world. Information architects regularly describe empathy as both a critical prerequisite for the job and as something fundamental to the professional practice. But in all my years as a user experience designer and information architect, I was never taught empathy or specifically tried to train myself to be more empathetic. I’ve never taken any kind of Voight-Kampff test to see how empathetic I am.

Practices like user research and deliverables like user personas certainly embody the concept of empathy, but so does the work of countless other professions — artists/illustrators, doctors, marketers, cops, salespeople, journalists, social workers, politicians, even management. Many of them even specifically include empathy training as part of their academic curricula and professional development programs.

Conversely, I’ve met information architects who are very good at what they do but who don’t strike me as particularly empathetic. Pig headedness, self-aggrandizement, insensitivity, and other non-empathetic personality traits haven’t stood in the way of people becoming excellent at many important aspects of IA. How have we come to claim empathy as a faculty we posess and utilize more than people in other professions do?

Defining the Term

Personally, I’ve tried to avoid using the term since IMHO it conjures up a lot of unprofessional connotations: Like a person in a job interview who claims “I like working with people“, a claim to be empathetic can suggest just the opposite: that one needs to make an overt concerted effort to be empathetic to compensate for a more fundamental shortcoming of the faculty. I’m not even sure we agree on what it means, since for most people it seems to have more of an emotional connotation, and emotion is a subject that IAs rarely, if ever, actually discuss.

“Did you ever take that test yourself?”

What do you think? Is it fair of user experience designers or information architects to claim “empathy” as a something that makes us special?

For kicks, here’s a real-world empathy test. I took it myself and scored pretty much in the very middle of the empathy range. It hardly seems very scientifically legit, but give it a shot. I doubt too many IAs would score very highly on this particular measure of empathy.

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Johannes Brahms, clearly pissed off at Avery Fisher Hall. How is it possible that New York’s most dedicated Brahms lovers can excuse Lincoln Center?

A couple of nights ago I went to see a concert of chamber music by Beethoven, Mozart, and Brahms at Lincoln Center’s Avery Fisher Hall, on one of the final nights of the Mostly Mozart festival. (Just for the record, I’m not a big classical music concertgoer and I generally don’t know what I’m talking about, but my wife and brother in law have for years been great about helping me learn and appreciate classical music more and more.)

All of the performances were excellent as far as I could tell, but the final peice, a Brahms sextet, was what all three of us were really looking forward to.

Sadly — and shockingly — the Brahms was utterly unlistenable due to a nearly-constant and totally mysterious high-pitched ringing sound that marred nearly every note from the beginning to the end of the peice. The sound seemed to come from everywhere and nowhere, as if it were simply part of the space itself or coming from the rafters above. It would generally, but not always, coincide with an energetic violin phrase or a loud segment of music. And since the peice was dominated by the violins, the noise was present to some degree for (I would estimate) nearly a third of the peice’s entire duration.

When the noise first started, I glanced around to see what it was (assuming it was someone’s cell phone), and the first thing I noticed was the hearing aid in the ear of the gentleman sitting next to me. But the sound didn’t seem to come from the hearing aid — it was coming from everywhere at once. This wasn’t some subtle easily-ignored sound, either. It sounded like someone’s wristwatch alarm or cell phone was going off every five seconds. Or more like a hundred people’s wristwatches were going off, all very quietly but adding up to something quite substantial.

I wondered if it was just me, something screwed up with my ears. And yet I noticed a similar discomfort in the faces of my wife and brother-in-law sitting next to me. The three of us kept glancing at each other with pained looks every time the noises resumed, in perfect synch. It wasn’t just me. MORE…

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Peter Morville’s well-known “honeycomb” diagram (and accompanying article) illustrates seven qualities or “facets” of user experience design, going beyond just usability into six other areas where the user experience designer’s work is cut out for them. It’s a great diagram — I use it with clients to describe all the things we need to address, and I use it in my classes to help my students see the full scope of the UX designer’s responsibilities.

It occurred to me that a lot of what is included in this diagram is, in fact, entirely subjective in nature. Of these seven facets of UX design, how many of them can actually be measured by objective, empirical, or quantitative means during the design process?

I’m limiting the question to the design process itself, because once a product is released to the market it’s clearly a lot easier to measure its performance than it is to measure it while you are still building it

• Useful: Immeasurable. Sure, focus groups might help us understand what users will find useful, but ultimately even those studies are subjective. Maybe market analysis or customer surveys could approach quasi-quantitative results (i.e., a number of qualitative results can be run through a formula and articificially transformed into quantitative results, such as “21% of customers said they would find an auto-save feature useful”), but I don’t count that as a true measure of the empirical usefulness of a feature.
• Usable: Probably the easiest to measure (such as with clocks and performance counters), but still prone to subjective conclusions and flawed methodologies (as I’ve just written about extensively).
• Desirable: Immeasurable. Again, this can be researched but not truly measured. See “useful” above.
• Findable: Similar to “usable”, this is possible to measure with empirical performance metrics.
• Accessible: Often this is measurable, at the very least legally, according to a series of subjective but expertly-determined standards. There are gray areas, of course, and sometimes the standards are wrong and easily misinterpreted (putting ALT tags on bullet point GIFs for example), but in general I’d say accessibility is measurable.
• Credible: Immeasurable.
• Valuable: Immeasurable.

So it looks like at least 50% of the user experience designer’s job is completely immeasurable during the design process, leaving the designer and his or her colleagues to make their decisions based entirely on their own professional and expert opinions.

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The classic Skinner box experiment.

A comment by Steve Baty on my recent series about design research got me thinking about the fine art of experimental research design:

Where research (in all forms) becomes a waste of time and effort is when the research design and methodology applied invalidate the conclusions _before_ they can be drawn.

One of the things that defines a great scientific thinker is their ability to design and construct meaningful experimental methodologies. Defining the terms and tools of an experiment in such a way as to focus on just the right question while excluding bad data, well, this is where science becomes a high art. Whether it’s physics, medicine, psychology/neurology, human behavior, whatever, the structure of a great experiment is often as interesting, surprising, and elegant as the plot of a great novel — and the insights such experiments reveal are often astonishing.

Sometimes the results of powerful experiments open more questions (often deeper, and more significant questions) than they answer.

I think of things like the Turing Test (measuring the quality of an Artificial Intelligence) or the Double-Slit Experiment (illustrating the quantum nature of light). One of my favorites is a kind of test for autism:

Typically, the child watches two characters in a scene. The first person (A) places some chocolate in a drawer. A leaves the room and B (the second person) moves the chocolate to another drawer. A returns and the observer/child is asked to guess where A believes the chocolate is. Young children (< 3 years) and persons with autism mistakenly think that A will look in the new drawer, whereas older children will correctly claim that A will look in the old hiding place.

Another favorite of mine is the controversial experiment by Benjamin Libet in which it is shown that humans begin an action a full half a second after before their conscious mind makes the decision to act. A shocking conclusion, one that throws our understanding of consciousness and free will for quite a loop. But how in the world can this be measured? Libet’s methodology is ingenius:

Libet asked his experimental subjects to move one hand at an arbitrary moment decided by them, and to report when they made the decision (they timed the decision by noticing the position of a dot circling a clock face). At the same time the electrical activity of their brain was monitored. Now it had already been established by much earlier research that consciously-chosen actions are preceded by a pattern of activity known as a Readiness Potential (or RP). The surprising result was that the reported time of each decision was consistently a short period (some tenths of a second)after the RP appeared.

What are your favorite scientific experiments? I’d love to hear about them.

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(This is Part 5 — the final part. Please read Part 1 , Part 2 , Part 3 , and Part 4 first.)

I would certainly agree that more rigorous methodologies can’t hurt in our field. But at the same time, I think that we need to be a little more honest about the value of some less-rigorous methodologies, techniques that are (and always have been) extremely helpful to the user experience designer. Card sorting, focus groups, guerilla (or gorilla — thanks Keith!) usability testing, and user personas (even the ad hoc kind) can provide invaluable insights and useful tools for a design team, even as they are entirely subjective and even a little touchy-feely in nature.

For example: I’ve been working closely lately with a major branding agency who conducted two weeks of field research into how their client (our client, too) was perceived by their potential audience. The research was well-organized, the participants were carefully selected, the questions were well-crafted, and the results were carefully organized and reported.

What was particularly refreshing to me, as a “customer” of their research results, was that the branding agency was upfront and honest that the final report, despite their care, was “not scientific”. It was research, but it was entirely qualitative and subjective. The final report was comprised of the branding experts’ opinions and interpretations of the data they collected. And it is incredibly useful to the rest of us working on the project because it give us a better foundation upon which to build our creative ideas for the design, the UI, and the business strategies.
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