Limitations of AI in Generating Creative Ideas

This is why I’m not worried about AI. I asked ChatGPT to give me a photo idea for a LinkedIn post reviewing Paul Arden’s book “Whatever You Think Think The Opposite.” The only other prompts I gave were that it must involve a picture of me holding the book. It recommended that I take a picture of myself reading the book in a large comfortable chair by a fire. Obvious. It also suggested I take a picture upside in a library. Cliche. So, I opened today's #onebookaweek to a random page. It opened to page 81 with the headline “Look At It This Way.” This is what Steve says: “I used to commission much photography. Consequently, people were keen to show me their work. Ninety-nine percent of the portfolios I saw were of a very high standard. But 98 percent of them contained pictures I had seen before. Obviously, not the same subject or composition, but I had the general impression that I was not seeing anything new. They didn’t have a point of view. If they did, it was that the viewer of their pictures (me) should like their work. Very occasionally, I saw the work of someone who did have a point of view, whose work was like no one else’s. These were often difficult people, almost unemployable because you couldn’t tell them what to do. Sometimes it went wrong. Sometimes it didn’t. When it didn’t go wrong, it more than made up for the times that did.” At that moment, it started to rain. So, I decided to do the opposite of what ChatGPT told me to do. The problem with AI isn’t that it can’t give you plausible answers or suggestions. The problem with AI is that it’s not a problem. It’s not difficult (in the way creative people are difficult) It doesn’t have a unique point of view. If it looks like it does, that’s only because the person entering the prompts does. I would never suggest I take a picture with the book standing in the rain. Or that I take a different type of picture altogether. Creatively speaking, AI is only as good as the creative mind entering the prompts. I can think of lots of ways these tools can be used to fuel creative minds. But until ChatGPT calls my request a dumb… Until it can “Think the opposite” without being prompted to… I cannot trust its ability to offer truly creative solutions. Will AI ever get to that point? I can’t predict the future. But there is one thing I can say: Now that AI can handle all the tactical stuff, Bill Bernbach’s quote about creativity being the last legal unfair advantage a business has over its competition is now more relevant than ever. And there’s still only one pain in the ass sentinel being on this planet capable of it. Until AI annoyingly goes off brief, it’s not being creative. Link to book in comments 👍 to share #obercreative #advertising #marketing #creative #AI #artificialintellegence My services #ghostwriting #copywriting #consulting p.s I’m not anti-AI. I use it all the time.

Some critics of AI have pointed out that it leads to a greater "reversion to the mean" - let's unpack the impact of AI on creativity. 🤖 In an insightful story in TIME (thanks Constantine Moros, MBA, PhD for flaggin!), Ray Nayler argues that AI can discourage creativity by encouraging people to rely on it as a crutch. Yet, the crutch is just that - a crutch: AI is not capable of generating fundamentally new innovation. How many of us have seen AI-generated content on social media, including here on LinkedIn, and it's just so obvious? 🎨 The predictability of choice and essence of creativity The reality is that most of our decisions are highly persistent, i.e. what we decide today is heavily influenced by yesterday. That is good for building predictive AI models, but not for promoting human flourishing, which requires us to branch out - at least in some ways. Creativity is inherently unpredictable, characterized by leaps in logic and unique experiences. AI - at least in its current form - cannot replicate that creativity. Instead, AI often just regurgitates what it has been trained on, leading to a repackaging of existing content and reversion to the mean. The danger lies in this mechanization of innovation, pushing us towards a norm of "good enough" rather than encouraging genuine creativity. 🏭 AI in a historical context Let's recount the history of mechanization. Even with Ford's assembly line, the goal was to achieve scale, which required lower labor intensity and higher capital intensity. (Sadly, many large companies have sought to tell consumers what they should have, rather than learn through dialogue and deliver it.) In this sense, AI can achieve scale, but at what cost? If the end product is average, then is greater scale worth it? That is a huge and important question that we need to grapple with as social scientists on a philosophical level, particularly as there is not enough data to actually make serious empirical progress on it right now. Nevertheless, we can also consider the ways that we use technology to amplify human ingenuity. The goal is not replacement, but augmentation. 🌐 As we reflect on AI's computational advancements over the past year and anniversary of ChatGPT, we must ask whether we can recognize the loss of creativity in the wake of AI and whether that's a price we're willing to pay. AI's true cost might be in mechanizing our tastes and ability to discern quality and originality. We must improve our discernment so that we can use AI as a tool, not a substitute. 🔍 Read more of the story below. #AI #GenerativeAI #Creativity #Innovation https://lnkd.in/ex7uwTiN

GenAI chatbots, despite their advancements, are prone to making mistakes in various ways, stemming from their inherent limitations. Many find chatting with LLMs like ChatGPT offers significant potential in enhancing the speed of delivery and empowering ease-of-use experiences. Many use these tools, without understanding that misinformation and disinformation can arise due to flawed training data or inadequate grounding. These LLMs or foundation models, that are used to create these chat interfaces while extremely useful, lack emotional intelligence, and morality. Recognizing these limitations is essential for designing effective and responsible AI and GenAI chatbot interactions. Let's explore how these limitations manifest in three key areas: Misinformation and Disinformation: Chatting with your LLM interface, otherwise, some call it an AI chatbot can inadvertently propagate misinformation or disinformation due to their reliance on the data they're trained on. If the training data contains biased or incorrect information, the chatbot may unknowingly provide inaccurate responses to users. Additionally, without proper grounding, where prompts are based on high-quality data sets, AI chatbots may struggle to discern between reliable and unreliable sources, leading to further dissemination of false information. For instance, if a chatbot is asked about a controversial topic and lacks access to accurate data to form its response, it might inadvertently spread misinformation. Lack of Emotional Intelligence and Morality: AI chatbots lack emotional intelligence and morality, which can result in insensitive or inappropriate responses. Even with extensive training, they may struggle to understand the nuances of human emotions or ethical considerations. Similarly, in scenarios involving moral dilemmas, AI chatbots may provide responses that overlook ethical considerations, as they lack the ability, or simply cannot perceive right from wrong in a human sense. Limited Understanding and Creativity: Despite advancements in natural language processing, AI chatbots still have a limited understanding of context and may struggle with abstract or complex concepts. This limitation hampers their ability to engage in creative problem-solving or generate innovative responses. Without grounding in diverse and high-quality data sets, AI chatbots may lack the breadth of knowledge necessary to provide nuanced or contextually relevant answers. Consequently, they may provide generic or irrelevant responses, especially in situations that require creativity or critical thinking. When systems like this are pushed to go beyond, or asked to be creative. #genai #AI #chatbots 𝗡𝗼𝘁𝗶𝗰𝗲: The views expressed in this post are my own. The views within any of my posts, or articles are not those of my employer or the employers of any contributing experts. 𝗟𝗶𝗸𝗲 👍 this post? Click 𝘁𝗵𝗲 𝗯𝗲𝗹𝗹 icon 🔔 for more!

So many people are scared AI will take over all creative work. My gut tells me that'll never happen. Here's why... AI is undeniably powerful. It's transforming industries and automating entire workflows. Every day it’s pushing the boundaries of “whoa, that’s already possible?” But when it comes to creativity — AI still falls short. Sure, AI can generate stunning visuals, write compelling copy, and even compose music that tugs at our heartstrings. But it lacks the one thing that makes human creativity truly special: The spark of originality that comes from lived experience. Think about it. Every time new tech emerges, our first thought is “will this replace me?” But what actually happens? It elevates us. It raises the bar for what we can create and achieve. When photography arrived, people thought it would kill painting. Instead, it pushed artists to explore new styles and techniques that captured the essence of human experience in ways a camera never could. When digital music tools became mainstream, people feared it would replace "real" artistry. But it democratized music creation and allowed for an explosion of new genres and sounds that we couldn't have imagined before. The same is true for AI and creativity. Yes, AI can generate an infinite stream of content. But it's content based on patterns. It can't tap into: → human experience → nuance of emotion → quirks of personality As creators, our job isn't to churn out more content than an AI ever could. It's to tell stories that connect us. To express ideas that challenge us. To reflect the world in all its messy, complicated, beautiful humanity. And that's something no machine can ever replace. What do you think? Will AI eventually replace creatives?

Most don't realize the trade-offs they're making when using AI. Since ChatGPT really took flight about a year ago, I've developed an AI-first mindset–looking to integrate it into just about everything that I do. I've invested much energy over the past year, honing my voice. While AI can be extremely helpful in getting folks from 0-1, I've found the opposite depending on the task. A goal of mine when sharing any writing or content is that I want to ensure that my authenticity and creativity really shine. I started to notice that when solely using LLMs to get from 0-1, the originality of my ideas was capped. My ideas felt generic. So, I decided to run an experiment on my workflow. I shifted back to using pen and paper first. After, I read my writing out loud and record it into Otter.ai. Then, use an LLM (Claud, ChatGPT, etc) to synthesize. Since shifting my process, I've turned a corner with my creativity and relationship to AI in my workflow. There's no right way to integrate AI into your workflow. The key is getting clear and intentional about the tradeoffs you're making in the process. ~ ✍️ What's your take on this? ♻️ Reshare if this is helpful. #artificialintelligence #aiworkflow #intentionaltechnology