Let’s compose a new narrative of creativity and innovation with AI.
In a data-driven world, it gets increasingly demanding to find a harmonious blend of human and machine ingenuity to craft powerful data symphonies. The intricate combination, of collaborative intelligence, can augment each other’s complementary strengths.
Row Over Creativity [Human Vs AI]
Controversy over art is nothing new. When an AI-generated artwork took first prize at the Colorado State Fair, it came as a shock, no one saw it coming. For the emerging digital artist contest at the Colorado State Fair, Jason M. Allen’s work Théâtre D’opéra Spatial took first prize for the contest for emerging digital artists.
AI tools like Midjourney, DALLE, and Adobe Photoshop Firefly are making amateurs capable of creating complex artworks just by inserting a few lines of prompt.
The first-ever auctioned, AI-generated picture, “Portrait of Edmond de Belamy,” sells for a whooping amount of $432,500
According to some critics, artificial intelligence tools like Midjourney can create artistic marvels with limited effort, and it’s just imitating human creativity. The underlying argument seems that digital creatives are built by scraping millions of images from the open web (the mathematical systems use style transfer techniques). Creatives that are contributed by genuine artists. AI algorithms are trained to recognize patterns and relationships out of these images, and then train their system to generate new ones in the same style.
Tweak the Model Parameter to Create a Diverse Range of Creative Possibilities
Deep learning technology is a promising artificial intelligence technique that has enabled tremendous possibilities in the creative realm. Deep learning techniques like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), are used to train on large datasets (thousands of paintings and pictures), to learn the underlying patterns and structures. Once trained, these models can generate new digital art and paintings by adjusting their internal parameters or input vectors.
According to Statistics published in Harvard Business Review, GPT-3, for example, was initially trained on 45 terabytes of data and used 175 billion parameters or coefficients to make its predictions. It cost OpenAI a whopping $12 million to run a single training.
Finding the Right Balance Between AI and Human Intelligence
Artificial intelligence has slowly permeated into all aspects of our lives. While AI can process huge volumes of data at quantum quickness, human experience, and intuitions play an important role in solving complex problems that are beyond just analytics skills. Hybrid intelligence can open up several sustainable and inclusive growth possibilities that align with the real-world context.
Enabling unique human skills and encouraging artificial intelligence adoption into the business ecosystem has become crucial in building a symbiosis between humanity and technology. Creating an ecosystem that mutually supports both human creativity and AI will lead to sustainable business growth.
The distinct characteristic of being creative was the key differentiator between humans and machines. With “generative AI” in the picture, it casts doubt on how wide that divide really is!
Tools like Chat GPT are capable of narrating poems. Painting from Midjourneyn winning contest. Does it mean AI is dominating the creative space, or it’s just presenting an impression?
Let’s run a quick test.
Prompt: Write a 4 liner poem around Deep Learning
Neural webs unfurl, knowledge to glean,
Deep learning dreams in layers unseen.
Patterns unfold, a digital sheen,
Wisdom emerging, in algorithms keen.
I would have had a great deal of difficulty expressing deep learning with the distinct concepts in four lines. With Chat GPT, it only took 2-3 seconds. Does this mean AI algorithms can be creatives? I think, it’s difficult to argue, that it isn’t.
There are 3 types of creativity
Combinational Creativity:- Involves novel combinations of familiar ideas, in simple words, it’s all about combining old ideas to come up with something new.
Exploratory Creativity:- This method suggests exploring beyond what you know.
Transformational Creativity:- This method involves novel approaches to creative expression. With this methodology, you intend to push beyond traditional thinking patterns of what is currently known.
Computer models of creativity include examples of all three types. Yet, exploratory creativity seems to be the widely used creative type.
AI has two essential directions symbolic artificial Intelligence and computational intelligence. Symbolic Artificial Intelligence algorithms are designed to solve problems by reasoning about symbols and relationships between symbols. The reasoning follows formalized rules. Computational intelligence is about recreating human-like intelligence in a computing machine.
Competence Connector: Bridging the Skill Gap
As per Salesforce, approximately 75 percent of workers express a sense of inadequacy in acquiring the digital skills essential for the future of the workforce.
One of the top challenges CIO’s face is preparing employees for the skills of tomorrow.
The lack of skilled employees is one of the most significant challenges global organizations face today. Businesses are turning towards cognitive technologies to automate day-to-day tasks. Integrating AI Technologies into workplaces and increasing employee productivity, optimizing resource allocation, and reducing cost.
By harnessing the power of artificial intelligence (AI), we can unlock transformative solutions that bridge skill gaps across diverse fields, revolutionizing training, upskilling, and reskilling individuals worldwide.
Organizations that prioritize leveraging AI technologies to retain and upskill their employees will witness a significant leap in improving their overall efficiency.
Creative Catalysts: Unleashing Divergent Thinking
Divergent thinking involves generating multiple novel ideas to open-ended problems. Artificial intelligence tools like Midjourney enable employees with the ability to make connections between remote concepts and inspire them to generate ideas from them. Text-to-image algorithms can combine contextual resemblance to create novel product designs. AI can easily bring your creative thoughts into a visual canvas with minimal effort.
Eg: A prompt like Heart shaped wooden chain, will give 100’s of inspiration that would help the craftsmen to build something novel.
Insert a simple prompt and the tools pop open a plethora of options you could take inspiration from. Just imagine the wide applicability of AI-created images in the animation industry. However, in the creative industry, it may seem like an opportunity, but there exist few open-ended questions. Is AI’s creativity limited to retrieving combinations that exist in their databases? What happens when we challenge AI to discover solutions that have never been previously identified?
AI to Personalize Content
Be it a global brand or not, content personalization is crucial in delivery. Businesses can make use of AI models to automatically generate localized versions of their content. For brands with a global footprint, AI translation has become critical in personalizing messages. AI-generated creative content is showing impressive results across a broad spectrum of industries.
While AI-powered translation tools provide speed, consistency, and scalability, for culturally dense or nuanced subjects, human intervention remains essential.
According to a study by Common Sense Advisory, 76% of people prefer to purchase products if they have info about them in their native language.
To win customers you need to have an exceptional personalization strategy. With more and more cognitive systems taking over automation, personalized content delivery at scale is something businesses should look into. AI tools with personalization capabilities can help create content that are more likely to appeal to their target audience. Placing the right content, at the right time, to the right person can go a long way in establishing an emotional connection. AI techniques like sentimental analysis can significantly improve customer experience and influence the company’s bottom line. When it comes to engaging and connecting with the mass audience, the significance of personalization cannot be overlooked.
Minds in Motion: Mastering Creativity Through Chess
There are certain striking arguments like, What good are the tools if we begin to rely so much that we no longer can think bigger? Chess may be an exception.
When computer-simulated chess games were introduced they posed a threat. Can humans outsmart the mathematical system? But in reality, the contrary happened. The broad acceptance of computer simulations chess helped players to explore creative ways to beat the algorithm and find a better version of themselves. A recent study conducted by Assistant Professor of Entrepreneurship Henning Piezunka at INSEAD found that people who had access to computerized chess simulation games proved to be more competitive than people who had limited access to computerized chess simulation games.
To Conclude
Human creativity is the original source and machine creativity is an emulation of human creativity. After all, without the original source, machines won’t have enough data to train themselves to create anything more than a “random lexical mixture”. With the current pace at which AI initiatives are driven, as time goes on, AI could become more prevalent and more capable of leading creative initiatives.
