University of Kwazulu-Natal

Hybrid Intelligence

Bonisiwe Shabane
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hybrid intelligence

In recent weeks, the AI landscape reached a new milestone with the release of several reasoning models, including OpenAI’s ChatGPT o3-mini, Deep Seek-R1 and Gemini 2.0 Flash. Building on the foundations laid by models like GPT-3 and GPT-4, these latest systems demonstrate notable gains in logical consistency and context awareness. Their rapid evolution does not unfold in isolation but coincide with technological strides on multiple fronts. A pragmatic response to these converging trends would be an investment in double literacy, an approach that curates and aligns both natural and artificial intelligence as a way of curating hybrid intelligence. Why? As AI systems grow more capable, jailbreaking — manipulating AI to bypass its built-in constraints — has become an increasingly pressing concern.

More powerful models often prove more vulnerable to exploitation, challenging developers and policymakers to keep safeguards ahead of potential misuse. At the same time, agentic AI and robotics are making striking advances. Robots researched by NASA robotics and pioneered by Boston Dynamics, among others, illustrate how physical machines equipped with sophisticated sensors and actuators can now navigate, manipulate objects, and execute tasks with unprecedented agility. Meanwhile, purely software-based AI agents — think advanced virtual assistants or complex problem-solving programs — leverage machine learning, natural language processing, and large-scale data analysis to make autonomous decisions. They already tackle intricate tasks such as medical diagnostics or financial modeling without needing a physical form. Increasingly, these two fields converge: software agents orchestrate fleets of robots, while robots generate invaluable real-world data to feed AI’s learning processes.

Yet, with the rise of powerful AI comes a heightened risk of jailbreaking and related vulnerabilities. The smarter these systems become, the harder they can be to control, underscoring the need for a balanced, human-guided approach that ensures such technologies serve constructive ends. The following article was written by Dr. Cornelia C. Walther, a visiting scholar at Wharton and director of global alliance POZE. A humanitarian practitioner who spent over 20 years at the United Nations, Walther’s current research focuses on leveraging AI for social good.

Imagine a neurosurgeon who faces a complex, high-risk brain surgery. Despite years of experience, the case presents unpredictable variables. Instead of relying solely on intuition, she turns to an AI-powered surgical assistant, which analyzes millions of similar cases in seconds, predicting complications and suggesting the most precise approach. As she operates, her expertise guides the procedure while the AI continuously adjusts recommendations in real time based on the patient’s vitals. When an unexpected complication arises, the AI flags an anomaly milliseconds before human detection, allowing the surgeon to act instantly and save the patient’s life. The AI extended the human’s capabilities without replacing her judgment.

This is hybrid intelligence (HI) in action — natural and artificial intelligence working together, amplifying strengths, compensating for weaknesses, and achieving what neither could alone. By understanding and harnessing HI, organizations can move beyond incremental efficiency gains to unlock strategic, sustainable outcomes that future-proof the enterprise while improving the well-being of the people involved. In the following sections, I explain how the multidimensional set-up of natural intelligence intertwines with AI to create HI, and provide a practical framework to help organizations leverage these ideas systematically and cost-effectively. Let’s start with a quick overview of the primary forms of intelligence referenced in this article: In the field of artificial intelligence, hybrid AI is an exciting perspective. The concept of hybrid AI is a promising direction where various AI technologies are combined to strengthen response development.

The structure of hybrid AI has been analyzed in practice. In this article, we explore what hybrid AI is and uncover its architecture. Hybrid AI, short for Hybrid Artificial Intelligence, integrates different artificial intelligence technologies or methods within a single system or application. It blends rule-based logic and machine learning to handle tasks with defined rules and data patterns. It aims to create an efficient, robust and intelligent system that can solve challenges in various fields, and also incorporate natural language processing for human interaction. Hybrid AI aims to utilize the benefits of different AI methods and overcome their shortcomings, ultimately improving the overall performance and capabilities of the system.

Hybrid AI systems, which combine different AI systems, are able to address a wider range of tasks and domains more efficiently than systems relying on a single approach. A hybrid AI system's architecture usually comprises the following essential elements: Hybrid AI architecture combines various AI techniques in multiple components for enhanced performance and functionality. This is a preview of subscription content, log in via an institution to check access. Price excludes VAT (USA) Tax calculation will be finalised during checkout. For further work on this topic see Dellermann et al.

(2019). https://deepmind.com (accessed 19 Mar 2019). https://ai.google/research/teams/brain/pair (accessed 19 Mar 2019). Hosted by Joshiya Mitsunaga, with co‑hosts Prof. Catholijn Jonker (Professor of Interactive Intelligence at TU Delft) and Prof. Frank van Harmelen (Full Professor of Knowledge Representation & Reasoning, Vrije Universiteit Amsterdam), each episode unpacks the political, ethical, and philosophical tensions at the heart of smart technology.

The administrative processes for these new positions are currently in progress. Once finalised, the job advertisements will be published, and links will be provided on our recruitment page for interested applicants. The Hybrid Intelligence Centre invites artists to apply for its first Artist-in-Residence program. A chance to collaborate with top scientists in AI, robotics, and cognitive science, and explore how art and science shape our hybrid human–machine future. Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values.

Our goal is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the centre, changing the course of the ongoing AI revolution. By providing intelligent artificial collaborators that interact with people we strengthen our human capacity for learning, reasoning, decision making and problem solving. This interaction has the potential to amplify both human and machine intelligence by combining their complementary strengths. Hybrid Intelligence requires meaningful interaction between artificial intelligent agents and humans to negotiate and align goals, intentions and implications of actions.

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