Raspberry Pi Station

I wanted a dedicated space for tinkering on Raspberry Pi, so I set this up. I bought a Medical Teleconference cart from a government surplus auction for $50, which I repurposed to be a great adjustable standing desk. Plus, it has lots of built-in cable management and a perfect cubby for holding the Pi. Then I lucked out and found an awesome monitor at the thrift store for $30. The rest of the gear I had lying around. Now I have a really convenient place where I can play with Pi, and as a bonus my home lab has a computer. I plan on using this setup to do some experimenting with Machine Learning soon, so stay tuned.

AI Generated Advertising Content

Due to recent progress in the fields of Artificial Intelligence (AI) and Machine Learning, many of the creative tasks within advertising, such as writing ad copy or ad image selection, are increasingly being performed by machine rather than by humans. The rise of AI generated content stands to shake the advertising world, as some professional roles become obsolete. The ways that consumers and brands interact are also rapidly changing as a result. To understand this phenomenon, we must delve into the benefits and pitfalls of AI generated content.

Some advertisers dream of a time when they can enjoy a three-hour work week, utilizing a myriad of AI tools to streamline and automate their workflows to extreme lengths. While this particular scenario isn’t very likely to happen, it’s not hard to understand the desire: This would be quite the leap from the current day-to-day slog that many advertisers find themselves struggling through. In the digital era, marketing departments must churn out dizzying numbers of variations of digital ads for the various social media platforms currently popular, each with slightly different imagery and calls to action. Wouldn’t it be nice to automate this process, and let robots handle the boring bits? Well, that might seem like some manner of science-fiction futurism, but it is actually a possibility today.

AI can be used to completely generate both the advertising copy and the visual imagery for the ad, and when combined with customer profile data, AI can even customize the ad to be more persuasive to that particular viewer. These ads do not exist before the target consumer is ready to view the ad, then in an instant an ad is automatically generated just for that particular viewer. The AI takes into account the viewer’s interests, behaviors, and demographics. The result is a very tailored communication, which will likely be more effective than a traditional one-size-fits-all ad. It also has the benefit of saving the brand a fortune in advertising costs. All the man hours that would have traditionally been spent in crafting the ad, and then creating endless derivatives for every possible platform, was all accomplished without any man hours spent at all (well, besides the initial setup of the AI campaign that is).

Multiple AI technologies can be used in tandem for particularly creative results. Companies like DataGrid and Rosebud.ai have developed AI technology that allows advertisers to utilize completely artificial models that are almost indistinguishable from real, human models. These virtual models can be used as actors in commercials, or as fashion models for brands. You could even showcase fashion products on a generated model that looks identical to the viewer, letting the viewer know how those items would look on them specifically. The possibilities are almost endless. Albert.ai is another AI brand, one that autonomously plans and executes paid search and social media campaigns. Tech company OpenAI (co-founded by Elon Musk) launched the AI tool “GPT-3,” which can write copy so well that it’s hard to tell that the text wasn’t written by an actual human. Using tools like these, brands can save advertising costs, allowing smaller brands the ability to make advertisements that rival the quality of larger brands. They will also be able to experiment with more creative advertising, since the cost to experiment will be much lower than using traditional methods.

However, the technology isn’t all AI generated roses. For example, according to Google’s Search Advocate John Mueller, content automatically generated with AI writing tools is considered spam and against webmaster guidelines. It is possible platforms will begin banning AI generated content in the future, which would certainly dampen the technology’s potential. As of now though, no ban exists for this emerging technology, and platforms like Google are unable to detect if ads were AI generated or human created. Another concern is that AI generation tools might lead to a stall in the advertising job market, as many traditional roles are replaced with AI counterparts. However, it is also possible that freeing advertisers from the more tedious aspects of ad creation will have a positive effect, allowing them to spend more time and resources on more creative pursuits. This could lead to higher quality advertising for consumers, and more high-level positions for prospective advertisers. A more pressing fear is that AI generated content might lead to empty, uncreative, repetitive advertising. This could further crowd an already crowded market, and could erode brand trust with consumers, if the technology is used to generate low-quality content. 

Despite these potential pitfalls though, the future of AI generated content is going to be too lucrative to ignore. Advertisers that learn how to put these new tools to work for them will enjoy an advantage over brands who aren’t able to capitalize on the power of generated content. And as this technology matures, that will only increasingly be the case. Even as it stands now, if some parts of this paper were AI generated using the tools currently available, would you be able to tell?