AI-generated content is coming – faster, better, stronger than expected. At the time of writing this blog post, it includes computer generated texts and images at a very high quality level already. And it is just a question of time passing by, before it also creates convincing video, audio, other content formats and even code (!). But what opportunities and problems does this new trend bring? And should you too let a computer program create your content?
The tools and the market
Right now there are multiple tools on the market, most of them offer free trials to get a first look at their capabilities. If you are interested in AI-generated images, check out my other blog-post to dive deeper into this topic here. For text-based content creation, right now there is no better tool than ChatGPD, where you basically have a conversation with an AI. You can enter a prompt, and get a text-based answer that is very, very convincing to what an actual human may have said. Check it out here: https://openai.com/blog/chatgpt/
Most of these tools are still pretty young, but based on an huge amount of available data to feed into them and the computing power of modern processors and servers, they are making huge development leaps basically every month. And their number and variety is growing. Fun fact, calling them AI is a bit of an exaggeration here. Actually what these tools are based on, is machine learning.
But how does machine learning work?
Machine learning is a method of teaching computers to learn from data, without being explicitly programmed. It involves using algorithms to automatically improve the performance of a system on a specific task through experience. Machine learning algorithms can process large amounts of data and use it to make predictions or take actions based on that data. The goal of machine learning is to allow computers to learn and adapt on their own, rather than being explicitly programmed to perform a specific task. This can be useful for tasks that are too complex for humans to code explicitly, or for tasks that may change over time and require the computer to adapt and learn from new data. So basically, you let a machine-learning algorithm read 1000 pages of Shakespeare, or feed 1000 historical oil-paintings into them, and by analyzing this content/data they are able to recreate new content in the styles or ways of the original content.
Opportunities of AI-generated content
AI-generated content has a number of potential advantages:
- Efficiency: AI systems can generate large amounts of content quickly and accurately, potentially saving time and resources.
- Personalization: AI-generated content can be customized for specific individuals or groups, allowing for a more personalized experience.
- Innovation: AI-generated content can be used to create new ideas or concepts that may not have been possible with human-generated content alone.
- Improved accuracy: AI systems can process large amounts of data and identify patterns or trends that may not be easily visible to humans. This can lead to more accurate predictions or decisions.
- Increased accessibility: AI-generated content can make it easier for people with disabilities or language barriers to access information.
- Cost savings: In some cases, using AI to generate content may be less expensive than using human labor.
However, it is important to consider the potential risks and limitations of using AI-generated content, as well as the ethical implications.
A problematic future of content
AI-generated content has the potential to be dangerous in a number of ways. One potential danger is that it could be used to spread misinformation or propaganda at scale. For example, if an AI system is trained on a dataset of biased or false information, it could generate text or other media that reflects those biases and spreads them to a wider audience. This could have serious consequences, such as leading people to make harmful or dangerous decisions based on misinformation. Another potential danger of AI-generated content is that it could be used to impersonate real people or organizations, potentially leading to confusion or mistrust. For example, an AI system might be able to generate convincing copies of someone’s writing style or speech patterns, making it difficult for people to tell the difference between authentic content and content that was generated by a machine.
Finally, AI-generated content may also raise ethical concerns related to the potential loss of jobs or the manipulation of public opinion. As AI systems become more sophisticated and are able to generate increasingly realistic content, there is a risk that they could be used to automate certain tasks that are currently performed by humans. This could lead to job loss and other economic consequences. Additionally, AI-generated content may be used to manipulate public opinion or to sway political elections, which could have serious implications for democratic societies.
AI as a copyright-problem
If an AI system generates a piece of content, who owns the copyright to that content? Is it the person or organization that created the AI system, or is it the AI system itself? These questions are not yet fully resolved, and the laws surrounding copyright and AI-generated content vary by country.
In some cases, it may be possible to assign copyright to the creator of the AI system, or to the person or organization that owns the AI system. However, this may not always be clear or straightforward. For example, if an AI system generates a novel or a piece of music, it may be difficult to determine who should be credited as the creator.
There are also ethical concerns related to the use of AI-generated content and copyright. For example, if an AI system generates a piece of content that is similar to an existing work, it could be seen as a form of plagiarism. There is also the risk that AI-generated content could be used to exploit or manipulate the work of others, either intentionally or unintentionally.
Overall, the issue of copyright and AI-generated content is complex and still evolving, and it will likely require further discussion and clarification as AI technology continues to advance.
Big ethical concerns included
An even bigger problem than the question of copyrights is the dataset, that is used to teach a machine learning algorithm to create a piece of content. All datasets include mostly copyrighted material, so content (texts, images, code, etc.) that was created by actual humans. Most datasets were created by just scraping off the internet, collecting millions of data entries, and then feeding it to the machine to learn. It is no surprise then, that for example a lot of artists right now ar protesting on social media against these tools. Their styles, their artworks, their life achievements have been included into these datasets, giving users of AI-generators the opportunity to basically mimic their work and sell as their own (see for example the instagram-creator Sarahs Scribbles, which even wrote an article for the NY times about someone who stole their artstyle and used it to create new, original content with it: https://www.instagram.com/p/Cm2G4liv-NL/)
It always takes time until the world adapts to new technologies, no matter how groundbreaking or insignificant they might be. In the case of AI-generated content, there will be the need for regulations around them to prevent abuse as best as possible without ruining the tools.
For your company, AI-generated content can be a real advantage, especially if you are a SME and do not have a lot of ressources for content creation. But always keep in mind, that no new technology comes without it’s complications, and this one here has just started to create trouble.
For us content strategists, all I can say is that we will have touchpoints with these new technologies as well at some point in the future. But as with so many other things – we do not need to get experts in AI-generated content. But we need to be aware of them being out there and not always being used with good intentions.