Council Post: The Rise of Generative AI and Living Content
Marshall McLuhan once said, “We shape our tools and thereafter our tools shape us”. The concern about technology entering every human space is not novel. With various developments through time such as processors, digital photography, creative software editing suites, music editing software, and computer graphics, the discourse between human creation and technology has continued through time. Humans are capable of leaps of logic that machines are yet to catch up with. Basic computer programming is merely one level above AI. Recent advances and accomplishments in AI are indubitably tied to human intellectual capacity. Although machines are still capable of much more than the human brain, humans differ significantly in terms of application of their knowledge by using logic, reasoning, understanding, learning, and experience. But concerns surrounding man versus machine saga have often lost ground to reality. It is true that a number of advancements in technology have made human involvement redundant in certain aspects of the creative process. However, even as the concern of being replaced is undoubtedly real, it is unlikely to happen that humans would be replaced by machines completely. The article will be talking about how content is going to evolve after the coming of generative AI. At the same time, it will address whether we’d really need writers when we have AI to write for us. Will content evolve or will it get too automated for readers? According to a Reuters source, ChatGPT is the creator or co-author of more than 200 books that are available on Amazon as paperbacks or e-books. The investigation also finds that as Amazon standards do not compel users to acknowledge the usage of AI in their books, the number of books authored by AI may be significantly higher than the number of books actually listed. More than 200 e-books in the Kindle shop on Amazon attributed ChatGPT as the author or co-author during the month of February alone. As more books are published, Amazon has introduced a brand new sub-genre devoted to books about using ChatGPT that are wholly authored by ChatGPT itself. At present, readers do not engage with lengthy content but instead prefer to consume media that is pertinent, succinct and tailored to their interests. This shift towards a more direct approach is something that the consumers are demanding for. Customers want content that caters to their unique needs and interests. Such content may be tailored to the preferences of certain audiences using AI and other cutting-edge technology, thereby giving each user a unique experience. The transition to interactive content is altering how we absorb information as well. Interactive content offers a more dynamic and engrossing way to information distribution, ranging from static images and text to immersive and engaging experiences. Every story should either be relatable or something that manifests a possibility of happening. Long-form Content Merges with Living Content Simultaneously, there is an audience that wants narrative content, which is typically referred to as long-form content. AI can make long-form content by using a technique called natural language generation (NLG). NLG is a subset of artificial intelligence that focuses on generating human-like language from data. Some people will prefer shorter, more precise content that gets straight to the point, while others will appreciate the depth and nuance that long-form content can provide. Additionally, the type of content and the purpose it serves can also impact its reception. For example, people may be more likely to consume long-form content for entertainment or educational purposes while they may prefer shorter, more concise content for news or information that needs to be consumed and understood quickly. It’s also worth noting that the rise of generative AI does not necessarily mean the decline of long-form content. While generative AI may be able to create coherent text, it may not necessarily be able to create engaging, thought-provoking content that resonates with readers. In many cases, long-form content is valued precisely because it provides an opportunity for in-depth exploration of complex topics, which may be difficult for generative AI to replicate. A theory of concept localisation highlights a major challenge in comprehending unfamiliar ideas when they are presented without sufficient context. As human beings, we tend to rely on metaphorical explanations to make sense of complex concepts. We learn best when someone provides us with a metaphor that allows us to understand and contextualise the underlying meaning or connotation of the concept at hand. With the advent of advanced language models, one can take a given concept and translate it into metaphors that are tailored to an individual’s unique background, making it easier for them to understand and absorb the idea. While AI-generated content is yet to perfect this process and may require significant refining by a human editor, it has the potential to greatly speed up the content creation process and help businesses and individuals produce high-quality, engaging content at scale. Rise of Living Content But just when we believed that this is the extent of what technology is capable of, something else comes along. No user can imagine how living content will develop in the future. Living content can be ‘tweaked’ for consumers, in the sense that it can be personalised to meet the needs and interests of individual readers. This can be accomplished through the use of data analytics and machine learning algorithms that analyse a reader’s behaviour and preferences and then curate content that is tailored to their interests. Living content can take many forms, including blogs, news articles, social media updates, and more. The key characteristic of living content is that it is constantly updated so that consumers can return routinely to get the latest information. Mark Twain once said, “There is no such thing as a new idea. It is impossible. We simply take a lot of old ideas and put them into a sort of mental kaleidoscope. We give them a turn and they make new and curious combinations.” Generative AI is trained on existing ideas to present seemingly new content. Conversely, the value of ideas with generative AI gets enhanced through the increased efficiency and scalability of idea generation. With generative AI, it is possible to create a large number of unique and original ideas in a relatively short amount of time, which can be particularly valuable for industries that rely on creative output, such as advertising and marketing. It is however noteworthy that, at present, humans are the only intellectual beings capable of such leaps of logic and epiphanies. Generative AI can also improve the quality and diversity of ideas generated, as it can draw on a vast amount of data and knowledge to create new and innovative ideas. This can help businesses stay ahead of the competition by providing them with unique and valuable insights that would be difficult or time-intensive to obtain through traditional research methodologies. Another way that the value of ideas with generative AI gets better is through the ability to personalise ideas based on individual preferences and needs. With generative AI, it is possible to create content that is tailored to the specific interests and preferences of an individual, which can improve engagement and drive better outcomes. In this era of content, the use of technology, such as AI and data analytics, is becoming increasingly important as it can help content creators personalise their content, improve its quality, and reach their target audience with greater efficacy. AI writing has arrived and is here to stay. Once we overcome the initial need to cling to our conventional methods, we can begin to be more receptive to the tremendous opportunities that these technologies present. Not only do they offer writers the chance to advance from being merely word processors to thought leaders and strategists, they also quicken the pace of content creation significantly. As this technology advances, authors will be able to devote more of their time to deep thought, developing their creative visions and original viewpoints. The majority of those who will profit from this inevitable change in the industry will be writers with original ideas. By expressing these thoughts with impact, clarity, and conciseness, the world of content creation is looking at a renaissance of its own. This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here
In this era of content, the use of technology, such as AI and data analytics, is becoming increasingly important as it can help content creators personalise their content, improve its quality, and reach their target audience with greater efficacy. AI writing has arrived and is here to stay. Once we overcome the initial need to cling to our conventional methods, we can begin to be more receptive to the tremendous opportunities that these technologies present.
In this era of content, the use of technology, such as AI and data analytics, is becoming increasingly important as it can help content creators personalise their content, improve its quality, and reach their target audience with greater efficacy. AI writing has arrived and is here to stay. Once we overcome the initial need to cling to our conventional methods, we can begin to be more receptive to the tremendous opportunities that these technologies present.
["Generative AI"]
["data science", "ChatGPT", "machine learning", "artificial intelligence", "TPU", "AI", "Aim", "analytics", "generative AI", "Generative AI", "R"]
["AI", "artificial intelligence", "machine learning", "data science", "analytics", "generative AI", "ChatGPT", "Aim", "TPU", "R"]
Ashwin is the VP of Data Science and Data Engineering at Digité Inc. He brings with him more than a decade’s experience in leading international data science teams. His focus is on building data science products that can scale for enterprise-level AI applications. Currently he is working to realize the power of XAI in decision sciences and building human-in-the-loop systems to simplify complex business processes for CXO offices.