The Rise of Generative AI: Why Humans Remain at the Core

I have been following the recent strikes by Hollywood creatives, and it has highlighted growing concerns that AI could render human skills and jobs obsolete. These strikes were sparked by the increasing use of AI in the film and television industry, which has led to job losses and concerns about the future of the creative workforce.

While AI can be a powerful tool for generating content, it is not a replacement for human creativity. I firmly believe in technology as an enabler, whether in our day-to-day life or improving operational efficiency at work. We have seen this aspect time and again. e.g., when computers were introduced, people feared they would lose their jobs.

The fact is that AI can only generate content that is based on the data it is trained on, which again is provided by humans. This means that AI is limited by the creativity of the humans who create the data. While generative AI is often seen as a tool that will eventually replace humans, humans will always be at the core of this technology. Here are what I think are three reasons why:

1. Humans are the ones who create the training data. Generative AI models are trained on massive datasets of existing content. This content can be anything from text to images to videos. The quality of the training data is essential to the quality of the generated content. Humans are the ones who select and curate the training data, ensuring that it is accurate and representative of the desired output.
2. Humans are the ones who define the goals of generative AI. Generative AI models can be used to create a wide variety of content. However, the specific content generated is determined by the user’s goals. For example, a user might want to develop creative and original text, or they might want to create realistic and accurate images. Humans are the ones who define these goals, ensuring that the generated content is aligned with the user’s needs.
3. Humans are the ones who interact with the generated content. Once the generated content is created, humans interact with it and fine-tune it. This interaction can be used to improve the quality of the generated content. For example, if a user finds that the generated text needs to be more creative, they can provide feedback to the model. This feedback can train the model to generate more creative text. This back-and-forth feedback only helps the quality of the results generated by the model.

 Generative AI lacks context and judgment. It does not know what scripts or effects would be helpful or appropriate for a particular project. Humans are needed to provide creative direction and discernment. We understand story, character, tone and all the nuances required to develop compelling entertainment. An AI cannot replicate human imagination and wisdom. At best, generative AI can help spark ideas or expedite specific role tasks. But true visionaries and artists are still human. People relate to authentic emotions and live experiences of other people, not to the cold digital calculations of a machine. AI has no cultural heritage, no empathy, no soul. I would only enjoy a film built by Generative AI with human creativity behind it.

 There are understandable fears that generative AI will cause displacement across industries. However, human stewardship can shape these technologies to lift workers rather than push them out. AI is only as wise and ethical as we enable it to be. At the same, it is fundamental that there is a governance framework in place to ensure AI is used responsibly, whether at an organisational level or championed by technology leaders.

Hollywood’s talent plays an invaluable role that machines cannot replicate. As AI progresses, humans must stay at the helm. With visionary leadership and governance, we can steer emerging technologies to expand human potential rather than undermine it.

Having spent some time taking courses on Generative AI (and still a lot more to go), we must stay relevant and start upskilling ourselves on different courses on Generative AI based on our various fields and areas of expertise. On an introductory level, many free courses are available on Generative AI.

• Introduction to Generative AI – 10 Free Courses by Google: This is a set of micro-learning courses that explain what it is, how it works, and how to use Google tools to develop your own Generative AI apps. Each course lasts 45 minutes and includes videos, readings, quizzes and labs.
• Microsoft’s First Generative AI Certificate Is Available for Free: This certificate program launched by Microsoft and LinkedIn provides free coursework for beginners who want to learn how to apply Generative AI to their work. It covers text generation, image synthesis, style transfer, and more.

Suppose you want to learn more about Generative AI beyond Chat GPT, Bard and Bing. In that case, software applications can create new content, such as text, images, audio, video, code, etc., based on existing data or user input. There are many generative AI tools available online for different purposes and domains. Here are some examples of popular Generative AI tools:

• Play.ht: This tool can convert text to voice using natural-sounding AI voices. It can be used for creating podcasts, audiobooks, voice-overs, etc.
• DALL-E: This tool uses a large language model to generate images from text descriptions. It can be used for creating illustrations, logos, icons, etc.
• Synthesia: This tool can create realistic videos from text using AI avatars. It can be used for creating video ads, tutorials, presentations, etc.
• Khroma: This tool can generate colour palettes based on the user’s preferences and inspirations. It can be used for web design, graphic design, branding, etc.

So while advances in generative AI rightly astonish us, we must remember that humanity remains at its core. These tools come from human minds and are designed for human empowerment. With care and ethics, AI and human imagination can positively combine for all. Generative AI should enhance the human spirit, not compete against it.

Disclaimer: The views expressed in my post represent my opinions, not those of my employer.