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Why Content Designers and AI Could Actually Be a Dream Team

Posted on 27 July 202330 November 2024 by Susann Pocha

If you’re a content designer, UX writer, or hold any other role in the field of the ever-evolving world of digital content creation, the prospect of integrating artificial intelligence (AI) into your work process is both exciting and daunting.

Large language models (LLMs), in particular, are passionately debated for how they will not only transform our work but completely disrupt it. The possibilities for editing and generating text are diverse and evolve rapidly. Yet, in the future of content design, human creativity, and AI efficiency are not competitors but rather dynamic teammates. Here are three reasons why content designers should seriously consider pairing up with AI.

1. AI is efficient and effective

AI can significantly improve the efficiency and effectiveness of content design. But only if content creators understand how AI works. The better they understand the functionality and capabilities of the system, the better they will generate useful prompts that transform their ideas in real-time. Also, AI systems are outstanding at mining vast quantities of data and identifying patterns. This can save time or open up completely new perspectives. The once-dreaded blank page can lose its intimidation. Knowing these AI capabilities and how to use them paves the way for a more efficient and effective content-creation process.

2. Humans can decide the focus

AI can free content designers to concentrate on what humans do best: shaping ideas, strategizing, and solving problems with empathy and purpose.

While AI can manage the routine tasks of data analysis, pattern recognition, and interpreting insights, it’s humans who lead the way. It’s humans who provide the perfect briefing for the artificial teammate, ensuring it creates content that is not only accurate but also relevant and ethical. It’s perfectly clear: Crafting a well-thought-out strategy is essential to nourish the AI with precisely tailored prompts and get it reflect on the ideas you’ve been thinking about. This thoughtful application of AI could help generate more targeted and personalized content, resulting in better user engagement. The more focused the thinking of humans, the more valuable the result of the AI.

3. Writing skills become a new benchmark

While AI can create mostly generic content, it still can’t replicate the exceptional writing skills that humans possess–at least not without inhuman efforts to engineer prompts.AI lacks the ability to fully comprehend nuances of language, emotion, and culture that are often essential for compelling content.

AI fails to adapt content to user and business needs. This is where content designers shine, by giving communication a fresh touch that makes it exceptional, if not surprising!

So … what’s next?

To wrap it up: AI’s role is not to replace content designers, but rather to augment their capabilities. For me, it offers a way to automate repetitive tasks so I can focus on strategic thinking, problem-solving, leadership, and maintaining exceptional writing quality. When designing conversational experiences for our customers, my role has shifted. I no longer point out the many constraints within the conversation that the chatbot used to have, but instead, give constraints to the AI to keep the conversation on track and aligned with user and business needs.

It’s incredibly fun and challenging at the same time to put yourself not only in the shoes of the user but also in the shoes of AI. As this process is just emerging, it is up to us content designers to use this service wisely and thus shape the future of our profession.

What ChatGPT and LLMs Mean for How We Build Conversational Interfaces for the Future

Posted on 28 February 202330 November 2024 by Paul Krizsan

Firstly, what are LLMs and ChatGPT? This is not an article about what LLMs (or large language models) and ChatGPT are. If you have been living under a rock and are unfamiliar with these names and terminology then this article written by ChatGPT explaining itself should be a good starting point.

We have been receiving questions from – and participated in many discussions with – our customers and peers about this exciting new tech and wanted to clarify our stance on where we see the opportunities and weaknesses at the current stage, as well as looking forward to a potential hybridized future. The biggest talking point has been the need for conversation design in an increasingly automated and generative world.

From our perspective as experts on conversational interfaces and conversation design we see predominantly two paths that this technology and trend will continue to develop on: the path of consumer-facing applications and the path of the technology as a tool and force multiplier. Neither of which will be eliminating the need for humans behind the wheel, steering the technology, anytime soon.

Hopping on the LLM bandwagon

Broadly speaking, this technology and its implications are spreading at breakneck speed. Many platforms are currently aiming at capitalizing on this goldrush-like state. You may have heard of Microsoft implementing ChatGPT in Bing and Google looking at fusing their proprietary equivalent LaMDa with their own search engine. These search engines follow a trend that companies such as SoundHound have been pursuing for a while, responding to users not in lists of search results, but in concrete answers in the form of natural language.

Other examples of quick wins in this brand new space are bot platforms such as Voiceflow and Cognigy.AI. Here the same purpose of applying LLMs to dynamically generate the system responses or predictable training data for intent training is being used heavily. Some platforms, like Cognigy.AI, are also considering going a step further and looking into the empowerment of conversation designers by allowing the creation of flows and elements through natural language prompts, speeding up the process of setting up new conversations greatly and thus contributing to rapid prototyping capabilities of these low-code platforms. Will these features collate into conversations that are production-ready, about to be rolled out to millions of users, out-of-the-box? Of course not. But they provide a good first framework to expand upon.

Trust in the system and the tech is dwindling

Widely broadcasted anecdotes of tech journalists and influencers, as well as hear-say from colleagues and friends have recently lead to a lot of skepticism when it comes to the current state of the technology. Articles quoting the unsettling feeling, individual erroneous responses and behavioral patterns reinforce negative connotations when it comes to LLMs in todays world. This obviously has a huge negative impact on consumer-facing applications.

Finding an appropriate place for LLMs should not be difficult

Focusing on this new technology as a force multiplies and enablement tool, is therefore the more stable path from our perspective. At least while the technology matures and new, more refreshing experiences for consumer-facing applications improve the publics perception in the mid-term.

On a more immediate and applied note, ChatGPT and LLMs are a great vehicle for innovation and a popular driver for change, but they are tools and will not replace human experts in conversation design. It is a good gap-filler and repetitive tasks but it will not provide the confidence and accuracy of dialogues designed by humans for a while.

The conversation designer is still the agent of change for this new tech

Our workflows in the future could consist of conversation designers laying down the structure of a dialogue, such as the starting point, the goal of the conversation and some checkpoints along the way, with the generative AI or LLM filling the gaps.

In an ideal world we would provide the AI with a purpose and a personality, but no actual dialogue would need to be written by humans. The conversation designer would be focused entirely on the strategic purpose of the interface and the decision on a vector of the personality and tone of voice of the bot.
Paul Krizsan, Director Conversational AI

So while remaining up to date with the current developments of this exciting new technology is vital, we do not share the current ubiquitous sentiment that users are ready for unfettered access to potentially image-harming experiences without having some of the kinks of current LLMs ironed out over the course of 2023.

Are you interested in talking about conversational interfaces, LLMs and how to design for conversations? Talk to us!

“Not everything could also be something.”

Posted on 2 September 2011 by Marco Spies

Only a few weeks ago I read Harry Harrison and Marvin Minsky’s “The Turing Option” from 1992. The sci-fi epic is situated in 2023 and it is striking how naive the renowned writer and the AI authority were with their forecast of technological development and esp. of interaction paradigms. Digital paper, wireless connections, embedded computing, gesture based interactions… all this has happened much earlier than in the book and to a greater extend than described.

However, if you watch this conversation of two chatbots it seems that the future of AI foreseen by Harrison and Minsky, is a long way to go from 2011. Nevertheless, the video actually emphasizes the uneasy feeling that I had when reading the book. Somehow, Sven, the robot in “The turing option” is just too perfectly human. Perhaps we should appreciate, these “cleverbots” are not…

Find an English review of the book here.
I actually read the German version of the book.