Storywise | LinkedIn (original) (raw)
Technology, Information and Internet
Get discovered. Publish stories that sell.
About us
Get discovered. Publish stories that sell.
Industry
Technology, Information and Internet
Company size
2-10 employees
Type
Privately Held
Founded
2023
Employees at Storywise
Updates
- Dive into Jeremy's take on AI's role in storytelling pitfalls. He urges creators to use AI as a compass, not a map, emphasizing the importance of human authenticity.
Risk, credit and entrepreneurship
7mo
Blockbuster movies and binge-worthy series are often criticized for their formulaic plotlines and underdeveloped characters. Many of these productions, accused of favouring profit over depth, rely heavily on AI-driven analysis of user engagement data to shape their content and even to script the dialog. This approach, while profitable, often leads to characters lacking believable personalities and genuine emotional development. Many have speculated that key elements, scenes and character choices from Amazon’s Rings of Power series were scripted by AI. From the egregiously shallow analogy in the opening scene, Galadriel’s illogical decisions throughout, major character inconsistencies within the Harfoot culture, forced and wooden dialogue, the various world building failures and on and on, it is hard to ignore the glaring lack of editorial experience. More recently, True Detective Night Country viewers have complained that the dialogue seems ‘almost human’ at times, and that the character’s choices e.g. Carole Danvers promiscuity, seem unconnected to character development or the plot, but rather an algorithmically calculated beat that should get a rise out of the audience. In both these cases, the lack of authenticity led to a lukewarm reception from audiences and critics alike, demonstrating the pitfalls of over-reliance on AI in creative processes. While AI can provide insights into audience preferences, it cannot replace the human element in storytelling. Audiences may click, like, or watch certain content, but these actions don't fully capture the nuanced emotional responses that define our love for stories. A good story touches the heart, stirs the mind, and stays with us long after we've engaged with it. Lacking lived experiences, AI is only able to mimic reality and, left alone, cannot create real depth beyond the superficiality of a virtual tiktok influencer lip synching and dancing to hordes of adoring teenage followers. Generative AI is, however, developing very fast. The output is increasingly impressive. While not yet able to write a publishable novel without exhaustive prompting and editing (more on this later), several award winning authors, including Rie Kudan, the current winner of Japan’s most prestigious book award, have started admitting to using AI to assist them when writing. Authors might use AI as a tool to understand trends, themes, and general preferences, and even to brainstorm, improve and suggest edits to a manuscript, but the core of storytelling must always come from a place of authenticity. AI can suggest what audiences might like, but it's the author's job to infuse these suggestions with real emotions, experiences, and nuanced understanding. To create believable characters, authors must delve deep into the human psyche; something AI can never do (famous last words?). Rather, think of AI as a compass, not a map; it can point you in the right direction, but the journey and destination should be uniquely yours. - What's next for publishing? Check out our co-founder Jeremy's vision of AI's transformative role. Did we mention he's an amateur author too!?
Risk, credit and entrepreneurship
7mo Edited
The skyscrapers, once pulsing with the glow of activity, now lingered in a fading twilight. And it was all self-inflicted. The silhouettes, a stark reminder of a revolution snuffed out. Sally, hunched over her antiquated desk in the dimming light of her small publishing office, stared at the flickering screen, the blinking cursor a constant reminder of an unfinished task. Every red pulse from the neon lights outside her window felt like a rejection – another contract lost to the East. There, unshackled by regulation, generative AI had turned offices into titans of innovation and efficiency, their tools and processes an irresistible lure for clients worldwide. Sally, once a herald of literary vision, now grappled with an unsettling irony: in trying to protect its intellectual heritage, the West had inadvertently relinquished its future, leaving its creators breathless and silent. That’s me setting the scene for a dystopian AI services war, with a bit of help from generative AI. It’s a war that might just happen. In the slowly evolving world of publishing, it's easy to view AI as a threat rather than an opportunity. One’s first impulse when faced with threats is to crush or banish them, though in this case, many other markets are happily engaging. Unlike US law, Chinese courts recently ruled that creators using AI tools can claim copyright over their creations. To regulate generative AI into ineffectiveness, or to reject it outright, will come at the cost of competitiveness. Consider the story of Kodak, a giant in the photography industry. They hesitated to embrace digital photography, clinging to their traditional film products. This reluctance to adapt led to their downfall, while Fujifilm who embraced digital technology, surged ahead. AI, specifically Large Language Models (LLMs), can be powerful tools for publishing houses and agents. They streamline processes, starting with grammar checks and stylistic improvements. Newer innovations include AI powered story editing guides and CRM assistance throughout the manuscript acquisition process. These allow editors to focus on the core creative aspects of their work. AI isn't here to replace the human touch in publishing; it’s here to enhance it at a time when speed and efficiency means everything. Ignore AI tools at your own peril. - Our co-founder Jeremy Esekow, offers a unique perspective on AI in publishing, drawing lessons from the streaming industry. It’s a roadmap for leveraging AI responsibly and effectively in the literary world.#AIinPublishing #DigitalTransformation #PubTech #DataPrivacy #InnovativePublishing
Risk, credit and entrepreneurship
7mo
It feels like a 100-meter sprint final. Interestingly, as traditional publishers crouch at the AI starting line, I’m struck by the overwhelming indecision among the racers. A couple of publishing houses are rearing to go, eyes trained on the finish line, completely fixated on the starters gun. Others have turned their starting blocks 180 degrees, itching to sprint in the opposite direction. Rather than pitch AI, I felt it more appropriate to write a nuanced post illustrating the opportunities, but also highlighting some pitfalls. And as a template, I’m going to highlight the experiences of content streaming – an industry that has already harnessed the power of AI and made mistakes that literary publishing can avoid. Streaming giants revolutionized content consumption by leveraging AI for personalized recommendations. They kept users engaged, continually discovering new content tailored to their tastes. In their rush to outdo competitors, they often prioritized volume, leading to a dilution of content quality. And they overlooked niche markets in favour of mass appeal. Book publishers might adopt a similar strategy, using AI to analyze reading patterns and preferences, thus offering readers bespoke book suggestions. This not only enhances reader experience but also boosts visibility for lesser-known authors and genres. Book publishers must however focus on curating high-quality, diverse content that resonates with readers, rather than merely cookie cutter style increasing the number of titles. Moreover, AI can streamline the editorial process. From predictive analytics identifying potential bestsellers to AI-driven tools assisting in editing. This integration can significantly reduce time-to-market, ensuring that well written books resonate with current trends and reader demands. Publishers will need to be cognizant of data privacy and ethical AI usage. Some streaming platforms faced backlash for intrusive data practices. A notable example is the 2020 controversy surrounding "The Social Dilemma”. Netflix released this documentary that highlighted the invasive nature of data collection and privacy concerns in the tech industry. Ironically, viewers pointed out that Netflix, much like the social media platforms they were criticizing, collect extensive data on their users. This incident serves as a cautionary tale for book publishing. It highlights the importance of ethical considerations in data usage. And the stakes are even higher for publishers. Many authors are already stressing the copyright theft dangers that AI training models present. Publishers must ensure that author content is protected while enhancing reader experiences. Finally, publishers must avoid the 'echo chamber' effect, where recommendation algorithms create a feedback loop of similar content. Publishers should ensure their AI systems recommend a diverse range of books, encouraging readers to explore new genres and ideas.