[Maria:] During our Q and A session at the June Virtual
UX Conference, an attendee asked Jakob Nielsen
if and how artificial intelligence and machine learning
might affect UX research and design.
Here's what Jakob had to say.
[Jakob:] Well, I think that there are two angles to that
and the first angle is that the user interface
will employ more artificial intelligence than it did in the past
and that will also therefore change what
UX people have to do.
And that's all the way from a little bit more,
maybe primitive use of AI for things like face recognition.
We did a study recently in China of how you pay by smile.
"So I got my croissant paid for"
it was one of our test users and they didn't
quite understand how it was doing it.
A lot of mental model confusion.
So even though face recognition
is a great technology, right?
And it's certainly much better, particularly if there's any
virus going around that you don't have to touch terminals
and mess with things, because it's just like
you get recognized and then that's how they know that
you're willing to pay.
But the way it was done had a lot of usability problems
leading back to mainly mental model,
which is one of our key concepts.
And another more kinda maybe important advanced
use of artificial intelligence is in
feature interpretation so that basic computers
ought to work on a "do what I mean" principle,
not "do what I say."
So computers have always been in some sense
ideal in one way of thinking, because they do
as they're told and that's great, right?
But they do exactly what they are told.
And so if you tell them the wrong thing,
then they're also gonna do the wrong thing.
And that's one of the areas where AI can come into place
and have better interpretation of what you really want.
But again, that has a huge human factors component to it
and big task analysis components to it of understanding
the circumstances, but that's one way usability
can be vastly improved if computers can change
from not having that literal interpretation of commands
to having more of understanding interpretation of commands.
Also for more complex fields or complex areas,
it's often not possible to have the computers
just like do it, which in some sense,
productivity wise is the optimal,
because then you don't have to have a person involved,
but there's a lot of things that involve two.
Well, you have to have more human judgment
that the computer can just do the thing.
But what the computer can do is present likely options
to the user and then the user can choose from them.
That can be much more efficient than just having
like, "Oh, here's all possible options" and you have to do
a lot of manual collation manually to get anything to work,
which is kinda how current computers work.
Instead, the computer can kind of shortcut a lot of that.
Not by making a decision, but rather saying,
"Here's the five most likely things that should be done,
which one is actually the one?"
And the person the human can decide on that.
And that's one of them should be one of the options
should probably be none of the above.
And then you've gotta go back to the manual involved
complicated process.
But I think AI can do a lot to really make deeper decisions,
better decisions, but again we have to understand
the task, the domain, and do a lot of those kind of
deeper human factors type of the methods for that to work.
And so that's the entire area of the user interface.
And so it's just, I guess the most kind of bottom line
conclusion there is.
Don't assume just because it's AI, then we don't need any
user interface, design any usability work
any of the UX stuff at all.
And in contrast, we actually needed more because
we need to have a deeper understanding of both the person
and the problem before we can apply AI methods
to either fully or partially solve the problem.
I think partial solve is more likely to be often the case.
And then we may need a little bit of variant methods
but honestly, the methods where we have apply
to this technology, does this apply to any other technology.
But that said, I think there's still gonna be some changes
for UX work as well, because we can use AI in our own work.
And some of these are some of the things
I kinda mentioned like, let's say face recognition,
not just face recognition, like who is this person?
Because if we take somebody in for usability study,
we know where they are but you can do some kind of
like emotion recognition or other ways of tracking
what goes on during the study in a more interesting
and detailed way.
I mean, let's say you can, actually you can not right now,
but that's one of the things I think that AI will hopefully
be able to get us is a better use of lot of biometrics
that currently we don't really use because
it is too confused and messy and misleading,
but that I think is a really future important thing
for us to get better use of research.
I think also more simplistic things like
automatic transcription of a user interview
or usability study session,
or maybe even ways of highlighting or recognizing
key things to look for, I don't necessarily think
we can have a computer just do the user interview.
Maybe it could do some of the questions automatically,
there's sometimes by the way, people answer more truthfully,
when they are doing an interview with a computer
than when they're doing it with a person,
that's been something like experiments in medicine.
So the classic example is like, how many drinks,
how much alcohol do you drink per week, right?
And when the computer asked the question,
people will say they drank more alcohol
than when a human doctor asks the question
'cause they're embarrassed to tell the person I drink
like 20 shots of whiskey a week, but they'll tell
a computer, even though the doctor's gonna look
at the computer's response in the report later,
but people I'm honest sometimes with the computer.
So maybe some types of user interviews could be automated
but obviously many cannot because a lot of this
is like react in the moment and understand
the circumstances, but some could be done
and then you could mass produce it over more people
and you can automatic transcribe it, you can automatically
identify areas of interest.
And again, I don't think perfect AI anytime soon anyway.
So this is gonna be a little bit like what I mentioned
with the user interface that the artificial intelligence
will identify possible things, and then the human
which is the user researcher has to go and look at those
and say, "Yeah, this is not really important,
that one is," and like interpret what it means
which the computer cannot interpret what it really means,
that's so I think that will definitely still be a need for
UX people, but we can do things more efficiently.
Similarly in design, you could have a lot of things
where designers now sit and mess with things
at a very tiny basis can be done more or less automatically
by the computer or the computer can come up with like,
here's like five possible layouts that comply
with all the known graphic design principles
and then the designer can say,
"Yeah, but you know, the principles are right."
But sometimes best design comes from mainly following
the principles but then like violating it
in one particular spot
and then you add at your human creativity,
but you have saved a lot of work because
you already can stop working from something
that AI came up with.
I mean, I think there's gonna be a very large number
of examples like that.
Also, for example, analytics, like just continuing analytics
that just is in real time analyzed by an AI,
which again, you can not have a human sit there
and look at millions of data points every hour,
but a computer can do that.
And then again, it pops up to one of us
like a human UX person that the AI thinks
there's something otherwise going on
and then you gotta ponder that and analyze it
and say "yes, it's right or wrong,
what should be done about it?"
Maybe we can also have automated A/B test
variations generated by an AI as well,
maybe as it was triggered by this real time monitoring
by an AI.
So there's a variety and this keeps going many,
many, many possible other things, right?
And of course the basic, the real main conclusion is that
nobody really knows what will be the truly genius use of AI
in 10 years when it's better.
But now cycling all back, the point is that it's gonna
make us much better, more efficient,
more productive at our work.
Now this backs in the follow-up question,
which says, "Okay, higher productivity that means
that we don't need as many employees so we can
fire half of them, right?"
Actually I don't think so in this case
because I think that the need for UX is so enormously
great in the world that if we can do more work,
that doesn't mean that there needs to be fewer people
doing the same work, it means that the same people
will do more work.
And it also means so actually what normally happens
also is if productivity goes up, that's the only way
that you can increase people's salaries, right?
Because basic rule of economics is that a company cannot pay
an employee more than they produce.
"Cause if you pay people more than they produce,
you're gonna go out of business.
So if you wanna make more money,
they're gonna produce more.
Now, if we think that AI is gonna make you UX people
let's say 10 times more productive,
I don't think this means we're gonna get
10 times higher salary, I think it means that
we will do it too bad, right?
But I think I there will be some more higher salaries
because we will be better, we will have more impact on
the world, but much of that productivity gain is gonna be
spent or used on more UX, right?
So just gonna be more and more, more things,
"cause that's another basic rule of economics.
If something is cheaper people don't buy more of it.
And so what I'm predicting is that UX work will be cheaper
in terms of unit of insight if you wanna call it that,
a unit of great design, which is very hard to measure
in units like that.
But conceptually anyway, we can definitely
talk about it that way.
And so there will be more good UX done because the AI can
take some of that manual work off our plate
and so we can deliver more and that is needed
because the world needs so enormously,
much more UX work than is being done right now.
And so one of the things that's holding smaller companies
back in particular I think is that the current price
of a unit of great design or a unit of great user insight.
And so if we can drive that down by, a big, big factor,
much more UX work will be done.
And so that's the way I think that all that we resolve
that we'll do more, it will be cheaper, we may get
a little higher salaries, but not necessarily super higher,
much higher salaries, but definitely no unemployment
just because our productivity will go up
because we are in a field where there's endless, endless
more need than what's being fulfilled right now.