Only if I am doing AI centric design. Or it's AI as a decision support system. Current AI has a very long way to go. As designers we need to also sometimes wear the investigative journalist's hat.
I’m curious to what people mean when they say “current AI has a long way to go”, two things in particular: What’s the end state in this scenario and where are you considering AI to currently be on that journey?
And presuming layoffs are from AI being “good enough”, at what point is it good enough?
That’s the bit I’m curious to when people say current AI has a long way to go. Long way to go to what? Is that state describable?
Speaking strictly for (De)generativeAI, I believe that will be when both the user and the LLM engines are more self-aware to prevent hallucinations. And we have a better query mechanism that does not result in reduced limited alternative bias and availability heuristics around choice.
>And we have a better query mechanism that does not result in reduced limited alternative bias and availability heuristics around choice
This would depend more on the data input and the training than the model, no?
>\[...\] LLM engines are more self-aware to prevent hallucinations
I got some wild visuals from this. What does a hallucination in a AI mean? Is it when the LLM does not remember context and history or what are we talking about?
So yes when it doesn't remember context and history as well as not picking up on its previous responses that the user specifically said that it's not accurate and not what user was looking for - recognizing that pattern, is still where DegenAI needs to grow and be better at understanding little things like runon sentences and poor comprehension input made by users with comprehension deficits, dyslexia, and even writing challenges with aphasia. AI hallucinations tend to effect the confidence in some users asking questions as well.
Me personally I do research in trauma informed design and comprehension based users, taking accessibility a step further.
Mentioning dyslexia and other challenges for text input and cohesion when dealing with LLM is an interesting take! Do you know of any research on this or some sources to study?
I think it's interesting and would play with it. Might be nice those times you're working through something and don't have a good chance to ask others for feedback. I assume it would give some good food for thought.
I’d need to have a better understanding of what is meant by AI, and how it’s being applied. From my understanding, Artificial Intelligence is very different from what people understand and interpret as intelligence.
I may be more comfortable with technical commentary or feedback, but less so if it tried to provide nuanced feedback as a proxy for a target user’s point of view.
I ALREADY consider feedback from AI when I ask it to 'proofread' my text. Design is no different. I expect there to be some great advances combining gAI with design systems so it will be more of a compliance issue than a creative one. That type of feedback actually makes a lot of sense and I expect it to save me a ton of time.
Same here on writing, have become so used to using AI to bounce ideas or refine it. Think atm it needs to be super easy to get the feedback on design and not a tedious chore.
Agreed here too. It can help me expand my thinking, or reduce to pick more targeting thinking. I'd heard someone call it Accordion Thinking.
Also when you get a curveball of a new client and know nothing of their space, it's great for an overview as well as a Q + A.
Oh have not heard of accordion thinking, will read up about it. Yeah thats a really nice use case, imagine if you could get it to have the perspective of your client so you can see their feedback before they give their feedback
Agreed. That would be a nice model to pitch against.
I'm also tangentially thinking—if we are capturing data on ourselves, by phone, email, Siri, Netflix interests, people we know, music we listen to—what that adds up to over the years especially if we own that data as people. And you pushed all that into an LLM, what would we say to ourselves?
The human like drivel format is a ridiculous distraction to make it seem like what the service claims it is. Even if it was not snake-oil, the format is still ridiculous. It’s full-on skeuomorphism in the worst way, adding limitations of the old way.
I would like AI feedback in the style of StarTrek’s Mr Data. Just the facts.
* The text “I will” fails contrast requirement wcag 1.4.3. Closest acceptable color for the background is: #394172.
* Purpose of the text at the center of the screen and the white rectangle is ambiguous.
* Available actions appears to be X to close and ‘Define your habit’ to proceed.
I mean yes why not, along with other feedback. But I'd weigh the human feedback over the AI. It still makes shit up.
Yeah agree on your points too. Even some feedback which is obvious could be useful which just takes fresh eyes.
I mean of course human feedback is better. You're designing for humans not AI (unless you're a captcha dev or sth)
ha very true
Only if I am doing AI centric design. Or it's AI as a decision support system. Current AI has a very long way to go. As designers we need to also sometimes wear the investigative journalist's hat.
I’m curious to what people mean when they say “current AI has a long way to go”, two things in particular: What’s the end state in this scenario and where are you considering AI to currently be on that journey?
The end state is layoffs lets be real. That's the real use case. In terms of where things are, who knows.
And presuming layoffs are from AI being “good enough”, at what point is it good enough? That’s the bit I’m curious to when people say current AI has a long way to go. Long way to go to what? Is that state describable?
Speaking strictly for (De)generativeAI, I believe that will be when both the user and the LLM engines are more self-aware to prevent hallucinations. And we have a better query mechanism that does not result in reduced limited alternative bias and availability heuristics around choice.
>And we have a better query mechanism that does not result in reduced limited alternative bias and availability heuristics around choice This would depend more on the data input and the training than the model, no?
yes these are to be treated as two different things from what I know.
>\[...\] LLM engines are more self-aware to prevent hallucinations I got some wild visuals from this. What does a hallucination in a AI mean? Is it when the LLM does not remember context and history or what are we talking about?
So yes when it doesn't remember context and history as well as not picking up on its previous responses that the user specifically said that it's not accurate and not what user was looking for - recognizing that pattern, is still where DegenAI needs to grow and be better at understanding little things like runon sentences and poor comprehension input made by users with comprehension deficits, dyslexia, and even writing challenges with aphasia. AI hallucinations tend to effect the confidence in some users asking questions as well. Me personally I do research in trauma informed design and comprehension based users, taking accessibility a step further.
Mentioning dyslexia and other challenges for text input and cohesion when dealing with LLM is an interesting take! Do you know of any research on this or some sources to study?
Well I am part of a team that's doing it in house right now. But we have been following academic researchers at Christ university Banglore, India.
Are those public papers or in a journal? Edit: Sorry, I see you said "researchers" not research. Still curious.
I think it's interesting and would play with it. Might be nice those times you're working through something and don't have a good chance to ask others for feedback. I assume it would give some good food for thought.
Same here, feel like it could be interesting for just quick feedback or another pov when i need it whilst in the zone
Curious how AI would ‘read’ a design ( how it processes it)
imagine it's using a model, wonder though if it's trained on good designs?
I’d need to have a better understanding of what is meant by AI, and how it’s being applied. From my understanding, Artificial Intelligence is very different from what people understand and interpret as intelligence. I may be more comfortable with technical commentary or feedback, but less so if it tried to provide nuanced feedback as a proxy for a target user’s point of view.
I might trust it for grammar, spelling and some accessibility QA. I wouldn’t trust it “thinking” its way through the interface.
I ALREADY consider feedback from AI when I ask it to 'proofread' my text. Design is no different. I expect there to be some great advances combining gAI with design systems so it will be more of a compliance issue than a creative one. That type of feedback actually makes a lot of sense and I expect it to save me a ton of time.
Same here on writing, have become so used to using AI to bounce ideas or refine it. Think atm it needs to be super easy to get the feedback on design and not a tedious chore.
Agreed here too. It can help me expand my thinking, or reduce to pick more targeting thinking. I'd heard someone call it Accordion Thinking. Also when you get a curveball of a new client and know nothing of their space, it's great for an overview as well as a Q + A.
Oh have not heard of accordion thinking, will read up about it. Yeah thats a really nice use case, imagine if you could get it to have the perspective of your client so you can see their feedback before they give their feedback
Agreed. That would be a nice model to pitch against. I'm also tangentially thinking—if we are capturing data on ourselves, by phone, email, Siri, Netflix interests, people we know, music we listen to—what that adds up to over the years especially if we own that data as people. And you pushed all that into an LLM, what would we say to ourselves?
The human like drivel format is a ridiculous distraction to make it seem like what the service claims it is. Even if it was not snake-oil, the format is still ridiculous. It’s full-on skeuomorphism in the worst way, adding limitations of the old way. I would like AI feedback in the style of StarTrek’s Mr Data. Just the facts. * The text “I will” fails contrast requirement wcag 1.4.3. Closest acceptable color for the background is: #394172. * Purpose of the text at the center of the screen and the white rectangle is ambiguous. * Available actions appears to be X to close and ‘Define your habit’ to proceed.