Why Hybrid Intelligence Is the Future of Data Science

An increasing amount of research suggests that humanity has a new best friend: intelligent machines. Human-in-the-loop (HITL) computing is poised to offer stronger intelligence than artificial intelligence (AI), or humans could deliver without the complementary strengths of the other.

Machines and AI specialize in logic and computation speed that are far beyond the capabilities of the human mind. Instead, humans contribute creativity and dynamic thinking that integrates data with reality, and different areas of knowledge with one another for meaningful context. Together, hybrid intelligent systems can achieve accuracy and reliability through different strategies and sources of information. The result is a fascinating new field called “hybrid intelligence” or “collaborative intelligence.”

Cutting-edge business school programs like the Southern Utah University (SUU) Master of Business Administration (MBA) – Business Analytics online program integrate this new learning so that graduates can lead their organizations in its application.

Hybrid Intelligence Has Many Applications

The present and future of hybrid intelligence encompasses much more than just what you might expect. Beyond business, science and medicine, hybrid intelligence can produce textured, layered works of art. Combining human and machine intelligence can take all creative pursuits in new directions. Anna Ridler has applied it in installation art. Scott Eaton has broken new ground in drawings and sculpture. Musicians have created their own hybrid collaboration assistants to compose new music, and writers and performance artists are working at the vanguard of this fascinating new phenomenon.

Maximizing the socio-technical ensemble of both human and machine intelligence in business takes imagination. Humanity will have to think beyond current paradigms regarding the nature of work, how to bundle tasks into a “job” and extract value from business assets. Business leaders need to think about designing systems of human-computer collaboration so that different types of “thinkers” (including humans with complementary aptitudes) can work together.

Some early applications of hybrid intelligence are now being tested and used. Chatbots are taking over customer service duties with human beings operating dashboards that contribute to many conversations, rather than each human engaging 1 to 1 with a customer. In medicine, physician assistants are showing signs of being able to outperform AI/ML or human doctor capacities alone. In hiring, lending, insurance underwriting and public sector casework, applications are being developed and used to improve decision-making.

Recent Research Offers Powerful Support for Hybrid Intelligence

Researchers from the University of California – Irvine conducted an image classification experiment in 2022. Humans and computer algorithms competed to identify distorted pictures of animals and everyday items. Often, when the computer had high confidence, the human had low confidence in accurately assessing the image, but when assessments from both were combined, the hybrid model showed a higher percentage of confidence and correct responses than either human or machine alone.

According to co-author of the study and professor of cognitive sciences Mark Steyvers, “We show through empirical demonstrations as well as theoretical analyses that humans can improve the predictions of AI even when human accuracy is somewhat below [that of] the AI — and vice versa. And this accuracy is higher than combining predictions from two individuals or two AI algorithms.”

A 2021 research paper on a design science research project to study hybrid intelligence also provided similar conclusions. In a project with a Swedish manufacturer, an ML algorithm was designed with principles useful for HITL computing. While machine learning algorithms can be limited by bias, failure to understand context and precision deficiencies and fail to adapt to environments and self-adjust, adding human intelligence to the equation with effective communication makes ML and AI more effective in a variety of applications. AI and ML are instruments best guided by humans using several principles detailed in the report. Application developers should make it easy for humans to access and manipulate the AI in the application’s (or robot’s) behavior.

Why Professionals Should Be Well-Versed in Hybrid Intelligence

The shortcomings of human cognition, predictions and decision-making and those of AI are offset when man and machine converge, each lending their greatest aptitudes in collaboration. Though we are at the beginning of a revolution, many experts expect this to unfold quickly. As a result, we should see high employer demand for the skills necessary to contribute in HITL computing and hybrid intelligence projects over the next few years. For prospective business school students, that makes choosing a cutting-edge program vital for opening career opportunities in this fascinating new field.

Learn more about Southern Utah University’s Master of Business Administration – Business Analytics online program.

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