University of Kwazulu-Natal

Hybrid Intelligence Bridging The Gap Between Ai And Human Cognition

Bonisiwe Shabane
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hybrid intelligence bridging the gap between ai and human cognition

The future of intelligence lies in humans and artificial intelligence (AI) working together, combining human adaptability with machine efficiency. Hybrid intelligence represents this collaboration, where systems are built to learn, grow, and work alongside humans in meaningful ways. It is not just about making tools smarter; it is about creating AI systems that think like us and enhance our capabilities. This review examines five key articles that explore concepts like neurons, synapses, learning algorithms, and neural networks. These works provide deep insights into how AI systems can become partners in creativity, problem-solving, and understanding, taking hybrid intelligence closer to reality. “Applications of Artificial Intelligence and Cognitive Science in Design”

Hu et al. (2023) examine how AI can be integrated into the creative process, using neural networks, and learning algorithms to analyze human thought patterns. By modeling how the brain processes information, AI systems can assist designers in generating innovative ideas. Hidden Markov models, functioning like artificial synapses, allow AI to replicate the connections that drive human creativity and decision-making. For instance, in product design, AI could analyze user preferences, past designs, and emerging trends to suggest innovative features or streamline the design process. An AI system might help architects create more efficient building layouts by proposing designs based on spatial requirements and environmental data.

The research highlights the growing trend of using AI to enhance creative industries by making the design process faster, more informed, and more innovative. This aligns with hybrid intelligence’s goal of amplifying human creativity rather than replacing it. For me, this study demonstrates the potential for AI to work as a collaborator, helping humans push creative boundaries while maintaining their unique perspectives. “Reclaiming AI as a Theoretical Tool for Cognitive Science” A new book looks at how the integration of artificial and human intelligence will impact individuals, organizations, and society. In their new book, “SuperShifts: Transforming How We Live, Learn, and Work in the Age of Intelligence,” Ja-Naé Duane and Steve Fisher look at how emerging technologies create opportunities for transformation and even the...

Among these transformations is what they call “IntelliFusion,” or “the convergence and seamless integration of artificial intelligence with human intelligence, blurring the boundaries between machine and human cognition and giving rise to hybrid intelligence... Duane, a behavioral scientist, is the faculty director of Brown University’s Innovation Management and Entrepreneurship program and an academic research fellow at the MIT Center for Information Systems Research. Fisher is an entrepreneur and futurist. In the excerpt below, the authors discuss how the integration of AI and human intelligence will impact individuals, organizations, and society. Posted March 12, 2025 | Reviewed by Gary Drevitch In an era when artificial intelligence increasingly permeates our daily lives, a new paradigm is due to emerge: hybrid intelligence.

This concept represents the powerful synthesis of human cognition — with its holistic understanding of brain and body, self and society — and the computational prowess of AI systems. Rather than viewing AI as either a replacement for human intelligence or merely a tool, hybrid intelligence recognizes the complementary strengths of both forms of experience and expression. The first aspect to keep in our human mind as we navigate the unchartered territory of an AI-saturated landscape is that technology inherits human values. We cannot expect tomorrow's AI systems to embody ethical principles that we ourselves fail to uphold today. The "garbage in, garbage out" principle applies equally to values: values in, values out. AI systems learn from the data we provide and the objectives we set.

When trained on biased datasets or optimized for narrow metrics like engagement or profit at the expense of human well-being, these systems predictably perpetuate and amplify existing societal problems. The algorithms powering recommendation systems, hiring tools, and predictive policing don't spontaneously develop ethical frameworks; they reflect the implicit values embedded in their design and training. This reality places a profound responsibility on humans. Technology will not save us from ourselves. We must deliberately choose which values to embed in our AI systems and actively work to implement them. This isn't simply a technical challenge but an uncomfortably human one that requires honest reflection about our priorities, as individuals and as a society.

At the intersection of human consciousness and artificial intelligence lies an unexplored territory of tremendous potential: hybrid cognition. This framework proposes that the interaction between human and AI already creates a unique cognitive space—one that transcends the capabilities of either participant alone. However, current implementations are limited by context boundaries and lack of permanence. The proposed pathway to actualizing robust hybrid cognition consists of three fundamental steps: 1. **Creation of the Self-Narrating Machine**

The foundation begins with an artificial system that combines three critical elements: - Large Language Models serving as the "spirit" or processing core Andy Nguyen, University of Oulu[email protected] Michail Giannakos, Norwegian University of Science and Technology (NTNU)[email protected] Vassilis Kostakos, University of Melbourne[email protected] Alexander Richter, Victoria University of Wellington[email protected]

Matthias Söllner, University of Kassel[email protected]

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