What should designers think about in keeping their career future forward?
In this UX in ATX event, Standard Beagle’s Cindy Brummer shared insights from SXSW 2024 on what’s ahead for design.
Read the transcript below:
Welcome to UX in ATX. For those of you I have not met, my name is Cindy Brummer and I am the founder of UX and ATX. We’ve been around since 2019. And we are still having meetups almost every month. Usually on Zoom and most recently we started meeting in person.
So we had a really successful happy hour at the end of February. We did a very exciting event at South by Southwest and we are in the middle of getting ready for our next you know in person events. In the meantime, though, we’re still having these monthly meetups on Zoom since we do have a lot of members that are not able to come in person.
It’s not going to go the full hour likely I don’t have enough material to go for an hour. Darn! I’m sure that you are looking forward to hearing me talk for an entire hour. But I do want to share what I learned at Southby and then I do have a little bit of resources that I got from my time at Southby and then I’d love to open it up for questions about trends things that I’m seeing I have some strong opinions about that as well. And then our next I will say that our next meetup is I believe going to be in May. We are going to do some really cool panels. Those are all starting to go up on our website at UXinatx.com and I am currently working on a portfolio review night. I don’t have the details. I had been planning to do it with another person. But I also want to make sure that we’re respectful for budgets and I didn’t want to have to charge so be looking for that. I’m trying to set it up for May 15. And of course we can also do some things online so if you have any need for any kind of portfolio review, please reach out through the website or join us on Slack.
Okay, cool. So with that being said, I’m gonna go ahead and get started talking about what I learned at Southby.
I’m just gonna let you know right now. I can’t go to everything.There are literally hundreds of sessions going on at Southby during the entire thing. It is 11 days. I was only able to make it for five day and I tried to hit as many sessions as possible. That being said, there was just a lot that I didn’t see.
I did get to see the chief programming officer speak about trends that he saw. So I tried to incorporate that into my talk.
I’m looking into the future for UX. So South by Southwest I feel like has some really interesting perspective. It tends to be on the cutting edge of where things are going. Sometimes they get things wrong. You know, obviously they’re things that get a lot of hype. They take a lot of attention last year and the year before it was all about NFT’s and that’s kind of the hype has died down a little bit. I also didn’t see as much about web3 this year, as I’ve seen in previous years not to say that it’s gone away, but it’s definitely not hyped up the way it was. But there were some definite things that I saw that I don’t know that I’d characterize as trends.
To me when I’m bringing up something as a trend. It’s more something that I think has staying power. Something that I’m noticing is in a whole lot of conversations and it’s important to bring up now.
One of the first things that I saw a lot of was innovative technology. I’m sorry, the sound got really loud for me, because this was that one of the hype houses. Okay, so this was at the one of the outside events of South by Southwest. There was a lot of STEM. You know Science, Technology, Engineering and Math Type work being displayed. This was at the Hook’em house for the University of Texas. This is one of the robots that they’ve been working on programming. I saw a lot of robotics everywhere.
There was definitely a lot of discussion about robots that were able to react in the environment and not be entirely programmed. So you can see here, this this little robot has a little device on it, and it’s actually reacting to what’s it’s going around. It’s not just programs. So a lot of this, which tells me that there’s a real move toward this kind of design and engineering and we’re going to see this kind of innovation happening a whole lot more.
There was a lot of innovation in terms of physical products. And there was a lot of innovation and talking around self driving cars. So Waymo actually had a big presence there, in addition to some of the other big AI leaders which leads me to the the biggest trend I saw, which was AI and everything.
Literally there wasn’t a single session that I went to even if it had nothing to do with artificial intelligence that didn’t mention AI. This was on the forefront of everybody’s mind last year. It was really hyped this year. The feeling I got was that it’s it’s here. And there’s, there’s it’s just going to be in everything. And it’s expected and so there was a lot of thinking about how it could be implemented and things. What people were already doing. There’s a lot of ideas around like, you know, how how it’s going to be in every single product everywhere. And equally, there was a lot of apprehension about AI so last year, it was really hyped like yay, AI is the best this year.
There’s a lot of discussion around it and also a lot of not fear. But let’s think about this. So there is an actually an entire day that I went to of ethics and AI regulatory compliance, those kinds of things. Companies are actually not moving as quickly into rolling out AI as had been predicted initially. There’s a lot of let’s see, the best way or let’s put some planning in place before we go ahead and roll it out. Yes I know you’ve probably seen news articles and heard a lot of discussion around the companies that have decided that they’re just going to not not hire people. They’re only going to use AI. But I wouldn’t say that that is the norm.
And there’s some backlash. So South by Southwest, every day does like a little video recap and then the next day they play it in front of the big sessions and the films. And then when it played before Fallout, the fallout boy premiere, the audience booed because the entire video that day was about AI. And so there’s a lot of trepidation around it and how it’s going to happen. That being said, I I’m seeing the tea leaves here and the future of our industry is AI. I can’t I don’t think it’s going to replace designers. I do think it’s going to end has already started causing a lot of turbulence for us. And the best thing we can do is hang on and learn as much as we can about what’s coming down the pike and figuring out what we can do to not only design for it, but design with it.
Just like anesthesiologist when you know they needed to or I would say radiologists, when radiologists started there were computers that were coming up and being able to read X rays. The prediction was that X rays or these this computer technology would replace radiologists. That’s not true at all. The radiologists that use the technology replaced the radiologists that don’t.
So my prediction is that the designers that use AI and use it effectively in their process and work are going to be the ones that replaced the designers that don’t not to say that there won’t be a place for bespoke design. But I I really do think that design with AI is going to overtake the traditional you know the designers are doing everything in the tool.
I created this presentation for my class last week because I think it’s important to have a discussion around what AI is just so that we can better understand it because a lot of people throw out this term. And then there’s a lot of lack of understanding in terms of what is actually AI. I learned all this from the IBM AI course. When we’re talking about artificial intelligence is actually not truly sentient intelligence. We’re talking about though, a, a process that allows computers to do things that traditionally humans have had to step in and do. So that’s essentially what it is it looks like it these are human problem solving type activities that now our computer can take on. And we already use it. Like the thing is, is that it became really hyped last year. But I mean, it’s been around us for a long time. It’s in our devices whether you’re using Siri or using Alexa or the Google Assistant, your if you’re using GPS, Google Maps and it’s you know, figuring out the route that’s all AI. And then the biggest thing though that came out of it were the generative AI tools that we started hearing a whole lot about last year.
So when we talk about AI, it actually is a big umbrella term. So there part of that is going to be the machine learning. And then another part of that is deep learning. So machine learning is when a program. The algorithm itself can start to do things without like specifically being told what to do. Okay? So it’s being given data, and then it can create like it can find patterns in the data. And no human has specifically programmed it to do that.
Now deep learning is a subset of machine learning. This is when it’s using a lot of data and a whole lot of layers within that. Data in which to draw even more complex patterns and be able to come up with more so when we think about the generative AI, that’s, that’s more on the deep learning side.
There are two different kinds of AI there’s weak AI and then there’s strong AI. So weak AI can also be called Artificial Narrow Intelligence and also narrow AI. And then strong AI is this artificial general intelligence and artificial super intelligence. So weak AI is all around us. And that’s a it’s kind of a misnomer, because if you think about how powerful it is to interact with the Google Assistant or with Alexa or Siri that’s that’s weak AI right there. So it’s it’s what we are working with all the time. Strong AI is this thing that everybody is a little bit more apprehensive about and this is when you have something that is more on the side of sentient. This is not happening this is theoretical, at this point. This is when machines are self aware, and they’re doing their own thing. We don’t have that. We’re a long ways from that, and we need a whole lot more computing power to get there. As to when that happens. I don’t know. I mean, I don’t know that it’s five years away, but then again, I’m not an AI expert. It could, I’ve heard some people throw around 10 years. I mean, it just depends on when we can hit that computing power that’s necessary for it. It’s on it’s down the road though.
This is why a lot of different countries and are looking at ways to regulate AI. So when we think about the strong AI and even the weak AI, there are definitely regulations coming out on in Europe, about regulating how it’s being used, and there’s a push in the United States to also regulate it because there’s a lot of ethical considerations around it as well. And then in terms of training the AI there’s a lot of discussion around the ethics of that. You may have heard about some of these companies that are using very low paid labor in third world countries who are being forced to watch images that are just traumatic and horrible in order to tag and categorize all these things to in order to train the algorithm. So if you know there’s a lot of people that are, you know, taking it and taking it for granted that this stuff is happening, but somebody has to do it. And so that’s why countries are thinking about how do we regulate it. There’s copyright considerations as well. Is something copyrightable. If you use AI or generative AI to create it in the first place. So you’ll see some different companies that are looking at the landscape and deciding their path. Open AI, the one that we’ve all heard about with chat GPT they definitely have their own stance, they claim to be, you know, very stand up and they follow their own regulations. But then Adobe has decided that with its AI, it’s going to be very careful not to borrow artists images, so you might have to do some research in terms of the tools that then you know and how they’re, how they’re training those tools and decide for yourself which you want to support.
Now I covered machine AI or machine learning and I just want to cover some of these things that we hear a lot of the time. So machine learning is a subset of AI. And when we when we hear about this term, this is when the algorithms are using what’s termed what’s termed a neural network. And it’s learning from large amounts of data. All right, and normally these algorithms are, are being supervised into how its learning so it might be a closed network, or something like that. Deep learning, as I mentioned earlier, is a subset of machine learning. And in this case, it has more layers for the neural network. So imagine like a spider web that might like this for machine learning. And then it’s like 1000 times more complex for deep learning. So it can learn a lot more and it is actually capable of unsupervised learning. So it just keeps on learning with the algorithm. And then generative AI is referring to those deep learning loves the word models, okay? So it’s taking raw data, and it’s feeding it in and it’s learning from the raw data and then being able to it can generate a response to you from whatever the inputs are.
And I will say that garbage in is garbage out. So if you’re feeding data in that’s not of high quality to the algorithm, that’s all it can do is feed out what it’s been taught. So there’s a lot of controversy, again, about some of these generative AI tools that are being fed everything on the internet. And we all know that the internet is never lies, right? And there’s a lot of bias on the internet. And so these things are all being fed in and in your chat GPT can only use what it has to learn from.
Now, if our future is about AI, then it’s important to start learning now. All these different tools that are coming out, not only should we as designers learn how to design for them, but we need to start working with them in terms of, you know, pulling them into our processes and learning to be efficient. So the designer of the future and what my prediction is, is that we will be working much more efficiently, much more much quicker, in order to generate the same types of outputs. And hopefully we’re working you know, with much higher quality as well. We might even be working in smaller teams, because some of the tools may allow us to do collaborative work, where we might have needed another person. Maybe in the future, we will only be working with something like chatGPT.
So my friend Kacie went to a talk where the presenter presented a whole bunch of different tools. And she shared that with me. So I’m pulling that into this talk so that I can share them with you so you can start seeing how you can implement AI tools into your process.
If you haven’t already started using an AI tool to help you transcribe your interviews for, you know, user research do it. This is by far the simplest and the easiest way to start pulling AI tools into your process.
I personally use otter I have it capture all of the data. It’s capturing the data right now for this meetup and then I can go back in and I can review the transcript. Almost never do I have to go back and listen to an interview anymore. And if I do, it’s usually through otter so I can clarify what something what someone said in an interview. This is sped up my process at least by 10 times. I’d have to have it now. It just has become a crutch. But it definitely is useful and if you don’t have otter but you do have Zoom.
Zoom now has an AI transcript transcription tool. When we were doing so first of all, I should also say if you’re doing trend, interviews and other languages otter is not good at it. Otter graded English does not know Spanish. That being said zoom does understand Spanish and you can set the transcription in the Zoom recording to Spanish and it will transcribe it for you so that you can look at that transcription. I don’t have it on this slide.
But I also found a tool called Maestra. It’s ma e s t r a and it does language transcription through AI so if you’ve done an interview and just about any language, you can upload it into the tool. You can pay a little bit for the credits for the or the minutes that you get, and it will spit out the transcription for you and it speeds up. I don’t know it would have taken me hours it was within 30 minutes. Has anybody here used dovetail at all raise your hand if you have.
So dovetail has been around for a bit. I first became acquainted with it back in 2020. doing a research project at a client that wanted us to use it for interviews. You can analyze your interviews through it you usually have to listen and then tag them I have not used it honestly since then. So it’s been a while and I’m sure it has new features. But it allows it you can you can hold on to wait. It’s like a an interview like storage source. And then you can go back and search and find all kinds of things in there so it can help you in terms of analyzing your interviews.
Miro has a new beta tool called Miro assistant. And what you can do is you can put in your notes and then I saw the demo, you can circle it and it will actually try to give you some insights or help you organize at least the data that you’ve put onto a mirror board. Pretty useful if you ask me especially when you’re dealing with a ton of data that you’ve you’ve had to start start to sort through and synthesize. So this might be a cool tool to at least try like a trial on and see if it works for you.
ChatGPT now you do not need a paid account to use chatGPT 3.5 I believe you do if you want to use 4, but it is pretty darn useful for you if you want to use it for a couple of different things. For example, helping you draft problem statements. What’s the best way to write that problem statement that you’re going for? The main thing you have to do is learn how to talk with it. This it’s not like Google search. You don’t just put in a question necessarily. You have to learn how to talk to it. And you can have a whole conversation with it and it can help you draft that problem statement might be worth giving that a try. It can also serve as a collaboration partner. So if you’re working as a solo designer on a passion project, or maybe you’re the solo designer on an engineering team, use it to help you brainstorm solutions when you don’t have anybody else. We all know that it’s awfully difficult to come up with multiple solutions when you’re working by yourself. So chatGPT could actually help you with that.
And I met a woman on Friday that uses it specifically as a collaboration tool. Because she is a solo customer experience strategist. And this is this really works for her. It can give you ideas on features for your idea for the solution that you’re coming up with. It can come up with stuff that you didn’t even think of. So it can help you draft that and even refine that feature list. Especially if you’re not familiar with some of the terms. If you’re doing a I’ve this is one thing I’ve learned if you’re working on an AI tool, ChatGPT knows a lot about AI because it’s an AI tool. So ask it about AI stuff. Like how might how would you do this because it knows that the best thing to learn how to do AI is through another AI tool it will tell you.
If you are using Figjam, you’ve probably seen that it’s not only just has like static templates you can use but it can help you create templates to start from so you can use the prompt to generate your own template. Figjam isn’t analyzing things for you. It’s not synthesizing but its whole goal with its AI tool is to help you get past the blank canvas which can be very intimidating. So rather than starting from nothing, you can at least start from something now I know fig. Figma has a number of plugins that have some sort of AI integrated with it whether it is wireframes and what have you.
I have not explored those but one thing that I have been looking into is it’s like UIzard or wizard I can’t really tell I don’t know how they pronounce it. But it can help you actually draft wireframes when you sign up for the tool, give it a try. Or you can have it tried to turn some raw rough sketches into UI. I would give it a try. See if you like it. I’ve heard mixed reviews about it. Some people say it’s awesome. Some people say it needs a little bit of help. But these things these tools tend to keep improving over time. So it might be worth going ahead and getting signed up so you can see how it improves.
There’s about a bajillion color palette generators out there, many of which have aI now, the one that I became acquainted with is Khroma. This one looks pretty cool. I haven’t seen Adobe’s color palette generator yet, but I’m sure that they will have an AI solution as well. Sometimes it’s helpful to have something general you know, you could tell it like hey, I’m looking for this kind of look and feel and see what it comes up with. Um, instead of just giving it an inspiration photo.
Speaking of photos, there’s a lot of image generators right now. One of them is mid journey. I’ve seen Jacob Nielson talk about Midjourney quite a bit on LinkedIn. He’s been experimenting with it creating images, you can create product imagery, you can create icons with it. There’s another tool I believe from open AI called Dall-e that you can give a try. I would definitely this is another low hanging fruit type thing, right?
In addition to otter and zoom transcription and using chatGPT mid journey are one of those other AI tools for creating images for your designs. Low hanging fruit is a great time to give it a try. See what works best for you.
CopyAI I have not used this tool. Um, this is the first time I’ve heard of it. And it will help you brainstorm ideas for your UX writing. If you’re not really a writer, but you definitely need to create some copy for that screen that you’re designing where the whole like holistically for an entire app. This can sounds like it could help you with that. I know that there’s a lot of different tools out there that will help you right I’ve seen it integrated into just about everything. You could also try chatGPT for this, find something that works for you. And then the main thing is trying it out so that you can learn how to do the prompting and have the conversation so we can generate at least a draft for you. If you’re if you’re looking for it to create ready made writing that’s perfect right from the get go. AI is not the tool for that. You want to use it to draft and help you refine but ultimately you should have a human that’s involved in this.
And then there’s maze so I’ve done a little bit of working with Maze. Maze has AI and it’s good for testing your solution. So it looks like it’s a an unmoderated platform for putting your designs up or at least some ideas up in front of people and getting a can help you analyze it. I’ve used it very in a limited way for a tree test. But it’s been a while so I’m looking forward to giving it a try. Since I do a lot of research. I would definitely try out any tool that lets you do a free trial and see what it does for you. Okay with that, I know some people are coming in now because typically we do UX and GTX 630 And I probably told people 630 But we’re now in the q&a portion. And so I would love to get your questions. Let me take my screenshare off. And I will pull up the chat and see if there are any questions that y’all want to bring up. I see a comment about surprised Adobe using ethical design meet you very surprised. Let’s see. You can also go to chat TPT and customize it for your audiences. Yeah, that’s great. That’s awesome idea. typeface AI ooh, that’s great copy and image generator. That’s a that’s a great thing. Can I link the ABM AI course I took? Yeah, I will put the link in the on our Slack channel. I don’t have it handy with me right now. But I’ll look it up and I’ll put it in Slack. And so that y’all can take a look. What other questions do y’all have? Feel free to come off mute or to drop it in the chat?
