The Emergence of Human-Centric AI Engineering: A Broadened Perspective on Artificial Intelligence

 Introduction

Tech experts, academics, journalists, and venture capitalists all have a collective fascination with the term "artificial intelligence" (AI). Although AI holds up the possibility of revolution, the general public frequently misunderstands the notion, and even researchers may find it difficult to fully comprehend its ramifications. Instead of pursuing human-imitative AI, this article emphasizes the necessity for human-centric AI engineering by focusing on Intelligence Augmentation (IA) and Intelligent Infrastructure (II).'\

I. How AI Is Misunderstood

The False Connotations of AI

AI that resembles humans: both allure and terror.

The requirement for a better comprehension of the AI landscape.

A Personal View: The Prenatal Testing Conundrum

The identification of weaknesses in a data- and statistics-based medical system.

The significance of a medical system operating on a global scale with little human supervision.

II. IA and II's advancement

Enhancing intelligence (IA)

Improving human creativity and intelligence using data and computation.

Examples of IA applications include language translation and search engines.

Infrastructure with intelligence (II)

Creating a network of physical objects, data, and computing to support human life.

Issues with managing distributed knowledge, interactions at the cloud edge, and long-tail phenomena.

III. Changing the Focus of AI

Human-Imitating AI and Beyond

The limits of human intelligence and the demand for specialized reasoning.

Overcoming AI's overconfidence and refocusing on important AI issues.

The Value of Classical AI Issues

Tackling issues with uncertainty representation, causality inference, and natural language processing.

Pursuing long-term objectives and building models that are computationally tractable.

IV. Engineering Human-Centric AI

A New Engineering Discipline is Being Born

Acknowledging the value of human-centered AI engineering.

Acknowledging the demand for a more comprehensive multidisciplinary strategy.

Coordination and a Range of Voices

The complimentary roles of business and academics in the development of AI.

AI discourse that incorporates social sciences, humanities, and ethics.

V. Creating a Future That Is Human-Centric

Intelligent Infrastructure's Potential

Establishing an environment with AI that is beneficial to human life.

Weighing the potential of AI against societal, moral, and legal standards.

The Future Obstacles

Focusing on data and learning when developing trustworthy and efficient AI systems.

Solving actual IA and II issues rather than relying exclusively on AI that mimics human behavior.

Conclusion

The AI revolution offers a chance to develop a human-centric engineering field that stimulates creativity and improves human capabilities. We can get over the constraints of human-imitative AI and concentrate on pressing AI issues by widening our vision to encompass IA and II. A future that is focused on people and in which AI coexists with human intelligence will be shaped by industrial and academic collaboration as well as by the inclusion of various voices from the social sciences and humanities. Let's be cautious and responsible as we negotiate the challenges ahead in our search for a more positive and inclusive AI-driven future.