While versions of AI (artificial intelligence) have been with us for decades in the form of search engines, virtual assistants, and learning applications, it wasn’t until recently that the technology has exploded into mainstream prominence. With the advent of generative AI technology like Open AI’s ChatGPT and DALL-E, Midjourney, and Stable Diffusion have opened up ever-evolving possibilities in the digital landscape. Much has been speculated about how generative AI will affect society, from replacing jobs, unethically stealing from artists, to the fear that it could one day become sentient and, like so many sci-fi films have surmised, target humanity as an enemy. The more probable speculation, however, is that generative AI will continue to transform various industries, including blogs and social media. As early forms of AI have shown to provide personalized user experiences, the new age of generative AI can go even further in terms of dynamic content generation, advanced user engagement strategies, and ethical considerations for a world that is more connected digitally than ever before. The next few years will definitely be an interesting time to see how content is created, curated, and disseminated.
WHAT IS GENERATIVE AI?
To summarize as quickly as possible, generative AI uses a variety of neural networks and data mining techniques to create original data from pre-existing content. While machine learning technology has been in development since the late 2000s, generative AI technology essentially uses a variety of learning techniques to create its own algorithms to solve problems. Much of the technology revolves around pattern recognition and word association, making the technology ideal for creators, code development, gene sequencing, and 3D modelling. As of right now, there are still limitations in scaling computer infrastructure to improve the technology, as this would cost a lot of money and time. Another limitation would be specific to whichever company is developing an AI program of this type, and whether or not they used high-quality, unbiased data to train the model for operation.
Our impressions of the technology remain that it is neutral. How people use the technology, for better or worse, will reflect more about themselves than the technology itself. In terms of social media and blogging, businesses can utiliize generative AI as a powerful tool to create a variety of content quickly. This does not render writers or creators obsolete, as they are required to review, edit, and approve the content. Content creators are needed to ensure that whatever content is created by a generative AI not only suits the brand, but maintains integrity, and reflects accurate information. At this time, generative AI can produce an effective first draft; nothing more.
However, the use cases of this technology can greatly improve personalization as well as the user experience. Utilizing data from user interactions, AI-driven recommendation systems analyze preferences, behaviours, and interests, it is possible to leverage programs like ChatGPT to enhance user experiences, given the correct prompts. With the goal of creating a more engaging platform in mind, generative AI can be an assistant to engage user interactions.
AI’s impact on content creation is profound. Natural Language Processing (NLP) algorithms have led to the emergence of AI-generated articles, blog posts, and social media captions. Although AI content generation remains a topic of debate, it finds practical applications in data-driven reporting, financial analysis, and automating content production for various agencies. The concern that this technology is “stealing” from other creators and/or artists who have had their work posted publicly on the internet but did not give consent for generative AI to access it or be trained on it is a valid one. It is important, then, that creators who are turning to AI-powered tools do so for assistance in ideas, research, and content optimization. Instead of using the tool to generate work and then pass it off as their own, artists can be empowered to craft more relevant and higher-quality content that has a greater ability to resonate with their target audience. They can do this by using generative AI as an assist to improve their work rather than a free essay writer.
In the age of information overload, generative AI is invaluable for monitoring and analyzing the vast amounts of data generated on social media platforms daily. AI-driven social media tools such as Flick and Lately are able to provide optimal scheduling, identify trending hashtags, and provide detailed analytics. This data provides businesses with invaluable insights into customer sentiment, allowing them to tailor their marketing strategies and respond more effectively to customer needs. Sentiment analysis, which is powered by AI and being developed by a number of companies, actually interprets user emotions expressed in social media posts, comments, and interactions. Brands and influencers can leverage this analysis to gauge public sentiment, adapt their messaging, and build stronger relationships with their audience.
For the current or aspiring influencer, generative AI has become an integral part of brand strategies and marketing. Influencers can use AI-technology to analyze their audience demographics, while businesses can use AI-technology like Ambassador or Vivvix to identify suitable influencers based on brand objectives, audience demographics, and content relevance. AI-driven tools analyze vast data sets to determine an influencer’s reach, engagement rate, and authenticity. This ensures that brands collaborate with influencers whose values align with theirs, leading to more authentic and impactful campaigns.
FAKE NEWS & MEDIA BIAS
It’s unfortunate that the more access to information we have, the easier it is for fake news and misinformation blogs and social media posts to have widespread reach. While companies like Ground News are working to combat this by displaying media bias, generative AI has shown a lot of promise having a vital role to combat this problem. Companies like Bipartisan Press have been developing AI models using NLP to determine political and factual accuracy. This type of fact-checking and content verification can help content creators analyze the accuracy of information, identify misleading or false content, and assist in maintaining the credibility of social media platforms and blogs.
On the flip side, however, ethical considerations and AI bias have become focal points of discussion. AI algorithms can inadvertently perpetuate biases present in the data sets used for training. This has been observed in content recommendations, where AI may reinforce echo chambers, limiting exposure to diverse perspectives. Addressing AI bias requires careful data curation, diverse training data, and regular audits of AI systems to ensure fairness and inclusivity. Additionally, transparency in AI algorithms and the responsible use of AI technologies are crucial to maintaining trust among users and preserving the integrity of blogs and social media platforms.
Regardless, generative AI has the potential to usher in a new era for blogs and social media, revolutionizing the way content is created, curated, and consumed. The impact of AI is evident in personalized user experiences, AI-generated content, advanced user engagement strategies, influencer marketing, targeted advertising, combating fake news, and ethical considerations. As generative AI continues to evolve, so too will its influence on the way we interact with, consume, and create content on blogs and social media platforms. Striking a balance between harnessing AI’s potential and addressing its challenges is key to building a more responsible and innovative future for blogs and social media in a connected world.