University of Kwazulu-Natal

Why Hybrid Intelligence Is Our Best Bet To Thrive Now

Bonisiwe Shabane
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why hybrid intelligence is our best bet to thrive now

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: 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 recent AIBC Sigma event, Dr. Angelo Dalli, a distinguished AI thought leader and the scientific director of CSAI, presented an eye-opening keynote on the transformative future of artificial intelligence. His talk highlighted “Hybrid Intelligence,” a game-changing approach where AI moves from mere automation to becoming an essential partner in human decision-making. Dr. Dalli’s insights emphasize that AI’s next frontier isn’t about replacing human intuition but enhancing it to achieve high-impact results. In this article, we’ll explore the principles of Hybrid Intelligence, its benefits in real-world applications, and its potential to reshape industries from finance to online gaming.

Hybrid Intelligence represents a major evolution in applied AI, taking it beyond traditional data processing and automation. Unlike conventional AI, which primarily crunches numbers and identifies patterns, Hybrid Intelligence involves AI systems that can reason, adapt, and collaborate with human intuition. This new form of AI isn’t just an advanced tool but a strategic partner that aligns with human decision-making processes. By uniting machine accuracy with human insight, Hybrid Intelligence in AI redefines how technology integrates into complex, real-world environments. In Dr. Dalli’s words, it’s about “amplifying human potential” through an AI system that understands context, builds transparency, and aligns with ethical standards.

Applied AI: Real-World Context and Relevance Artificial intelligence has come a long way, moving beyond automation to a new frontier where machines and humans collaborate. This concept, known as hybrid intelligence, emphasizes the strengths of both parties—machines with their speed, scale, and analytical capacity, and humans with their empathy, creativity, and ethical judgment. The result is not competition but cooperation, where humans and AI work hand in hand to solve problems that neither could tackle alone. Hybrid intelligence refers to the fusion of human cognitive abilities and machine intelligence. Unlike traditional AI, which often aims to automate tasks entirely, hybrid intelligence is built on partnership.

It seeks to augment human decision-making by combining contextual knowledge and ethical reasoning with AI’s computational efficiency and predictive power. In essence, hybrid intelligence acknowledges that while machines can crunch numbers faster, only humans can interpret meaning, apply moral frameworks, and innovate in unpredictable scenarios. The complexity of modern challenges—climate change, global health crises, financial instability, and cybersecurity threats—requires both computational power and human wisdom. AI models can scan terabytes of data in seconds, but they cannot fully grasp the nuance of cultural, ethical, or emotional factors. Humans, meanwhile, excel at creative problem-solving and contextual judgment but struggle with large-scale analysis. Hybrid intelligence merges these strengths, leading to decisions that are not only data-driven but also contextually sound and socially responsible.

EY helps clients create long-term value for all stakeholders. Enabled by data and technology, our services and solutions provide trust through assurance and help clients transform, grow and operate. Discover how EY insights and services are helping to reframe the future of your industry. How digital twin technology powers the future at Xcel Energy How Bristol Myers Squibb overhauled working capital to fund its future How St James’s Hospital's journey to cloud transformed cancer care

In the fast-evolving world of artificial intelligence, we’ve seen some pretty exciting developments over the last few years. From self-driving cars to AI that can generate human-like text, the possibilities seem endless. But there’s one key advancement that’s quietly making waves and poised to change the landscape: Hybrid AI. You might be wondering, what exactly is hybrid AI? Let’s break it down. At its core, hybrid AI is about combining the strengths of two major AI approaches: symbolic AI and machine learning.

It’s like the perfect fusion of brains and brawn—each bringing its unique talents to the table to tackle problems in smarter, more efficient ways. To understand hybrid AI, we first need to understand the two building blocks. Now, hybrid AI takes the best of both approaches. It combines the reasoning and logical thinking of symbolic AI with the pattern recognition and learning abilities of machine learning. Think of it like having a team member who’s both great at following the rules and capable of creative problem-solving—this is the magic of hybrid AI. Pure machine learning is undeniably powerful, but it has its limits.

Imagine an AI system designed to help doctors diagnose illnesses. A machine learning model might be excellent at spotting trends in patient data—like recognizing the symptoms of pneumonia from chest X-rays. However, it might struggle with reasoning through medical guidelines or understanding a patient’s complex medical history without massive amounts of data.

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