Artificial intelligence (AI) has made significant progress in the past decade, becoming a well-known presence in everyday life. From Alexa recommending the best restaurants in town for any occasion to security systems sending near real-time alerts for any suspicious movement, and photo editors that can smooth away any imperfection, AI is ever-present and constantly evolving.
Whilst the prime motivation behind developing intelligent systems is to automate routine and time-consuming tasks, newer AI models have found multiple applications in more creative sectors until recently considered exclusive to the human mind. From filmmaking to gaming to the music industry and art, the role of AI as an assistant or solo creator is expanding rapidly. Only time will tell whether machines and humans will coexist as friends or foes.
A particularly controversial tool recently entering the creative sector is generative AI, with both praise and concerns being raised across the board. Generative AI refers to deep-learning models that learn how to create new content (text, images, music, etc.) from the data they are trained on. An already integral component of many online systems, it is the introduction of ChatGPT that has highlighted the untapped potential of this specific AI, especially in streamlining creativity.
ChatGPT can produce text to answer questions and engage in conversations in a very human-like manner. It is capable of writing poems and short stories based on user-generated prompts, editing academic essays and drafting business documents. It's easy to see why such a platform would become immediately popular: it eliminates the scrolling and analysing of Google search results by packaging the information needed in a handful of easy-to-digest lines. Whether writing a school essay or a creative piece, ChatGPT can get the job done in a few seconds rather than hours.
On a more professional level, many creative companies have started integrating these deep-learning models in their workflow, attracted by AI’s capacity to create more content more quickly. And in business, time is money. In 2016, the first AI-generated trailer for the film Morgan was released in collaboration with IBM. The AI model was trained on hundreds of existing trailers from similar flicks to identify and combine the most engaging scenes from Morgan. A task that would once involve at least one human agent and two weeks of work has been executed by an algorithm in less than a day.
There are undeniable positive effects stemming from the application of AI to the creative industries. Again, time is the most coveted one. No need to waste hours fixing a multitude of minute mistakes on a single image, a photographer can now identify and correct them within seconds. A team of marketers can quickly analyse thousands of data points from previous campaigns and identify the main components of the most successful ads to create new content. Or, as in the example above, a small filmmaking team can forego expensive trailer agencies by using AI to patch together scenes from their movie into an engaging promotional video.
The long hours of work averted with the assistance of generative tools allow for more to be done in a smaller timeframe, leading to another benefit of AI: higher income flux and faster turnover. Creative companies and individuals can service more clients at the same time and for lower prices, after reducing their human labour costs.
Finally, generative models open the doors of the creative industry to more aspiring artists than ever. AI fills the gaps where talent or expertise doesn’t reach, with more people than ever capable of expressing their vision through design, music or writing. Furthermore, the UX of many AI platforms has become so sleek and intuitive that most people can easily access their functions, further blurring the line between professional and amateur creative outputs.
Despite the plentiful benefits, there are also negative facets to the rise of AI for creativity. There is a risk that generative models will soon be promoted from creative assistants to creators in their own right. In the future, supervising the outputs of these algorithms may not be necessary, heavily hitting some of the few secure jobs in the industry. It may feel like a distant reality, but the effects of widespread AI use have already reared their heads. Only last year, the uncontrolled use of generative AI in the film industry was one of the issues causing Hollywood screenwriters to launch a 148-day strike. The result was an agreement between the Writers Guild of America and the Alliance of Motion Picture and Television Producers, stating that AI cannot be credited as a writer and cannot undermine a writer’s authority, and requiring studios to disclose if any material is AI-generated.
Another risk of relying on generative models to produce creative material is incurring copyright and intellectual property infringement. There is still no legal consensus on whether AI work is entitled to copyright protection. Currently, the US Copyright Act only grants protection to works generated by human beings, so people employing AI may not hold the rights to their creations. At the same time, creators across multiple sectors raised concerns over their work being used to train generative models without their consent and the outputs of such algorithms being instances of plagiarism. AI-generated images emulating the style of famous photographers or painters have drawn widespread criticism, with many questioning whether any product of generative AI can be considered creative in the first place.
Finally, a less well-known drawback of heavy reliance on AI is its high energy consumption. It is estimated that NVIDIA alone will ship 1.5 million server units by 2027, which would have a higher yearly energy consumption than many small countries. AI may become one of the big polluters of the planet if hardware technology doesn’t evolve in tandem.
Ultimately, there is no definite answer on how best to use generative AI. Both advocates and detractors make sound arguments to support their position, and it is especially difficult to predict the future trajectory of this technology in the creative industry. It may be that some of the outlined concerns can be mitigated by appropriate laws and engineering developments or that the gains outstrip the possible losses. One thing is certain: AI and human creativity remain at odds and inextricably linked, at least in the near future.
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