Human Creativity is complex. Can AI match that?
The link between semantic diversity and novelty appears more robust in human-generated solutions, indicating variances in the creation or perception of innovation between humans and AI, according to Harvard Business School’s report, “The Crowdless Future? How Generative AI is Shaping the Future of Human Crowdsourcing”.
Crowdsourcing offers unparalleled diversity of output by tapping into a wide range of skills and perspectives, enriching the quality of solutions with economic efficiency and agile responsiveness. This research sheds light on the capabilities and constraints of both human and AI-based crowdsourcing in tackling intricate organizational challenges, laying the foundation for a potential collaborative approach between humans and AI for problem-solving.
Contextual Understanding
Creativity often arises from a deep, nuanced understanding of context, including social, cultural, historical, and emotional facets. Humans have the ability to synthesize these disparate pieces of information to create something new and meaningful. AI, although increasingly sophisticated, struggles to grasp the complete context in the way humans do.
Emotional Intelligence
Human creativity often incorporates emotional depth, evoking feelings, and responses from an audience. The act of creation can itself be a deeply emotional process, influenced by the user’s own experiences, moods, and perceptions. AI lacks emotional intelligence and the capacity to experience emotions, which are often essential elements of truly groundbreaking creative works.
Ethical and Moral Dimensions
Human creativity frequently engages with ethical, moral, and social issues, often challenging norms and provoking thought. While AI can analyze data and generate outputs based on algorithms, it doesn’t possess an innate understanding of ethical and moral implications, which can be critical to creative processes.
Adaptability and Learning
Creativity often involves adapting to new situations, learning from failures, and iterating on previous ideas—all characteristics deeply embedded in human cognition and social interaction. AI models can learn from data but aren’t capable of the same kind of experiential learning and adaptation that humans are.
Self-Awareness
Humans are aware of their own existence, limitations, and potential, which can lead to introspective creativity. Current forms of AI lack self-awareness, preventing them from accessing this rich vein of creative potential.
Technological Constraints
AI operates based on algorithms and computational power. Even advanced machine learning models like GANs (Generative Adversarial Networks) are limited by the data they’re trained on and the algorithms that power them.
Future Possibilities
Advancements in AI research might narrow the creativity gap between machines and humans. However, whether AI can ever truly replicate the complexity of human creativity is still an open question, intertwined with our understanding of consciousness, emotion, and the human experience itself.
AI can and does aid the creative process and can even produce outputs that humans might consider creative, the notion that it could ever match the depth, breadth, and complexity of human creativity remains speculative at best.
Jan Iverson is Head of Studio at FS Studio and an award-winning product leader with over 20-years of extensive experience in digital media and marketing, with a specialization in the design and development of AR, VR and 3D activations: mobile apps, games, LBE, sales tools, digital twins; with XR cross-platform content development, and a track record of success in leading award-winning digital creative teams. Virtually Human is her bi-weekly series.
