Argumentative Essay on Artificial Intelligence: Will It Surpass Human Intelligence?

Introduction

AI stands as one of today’s most debated topics, yet a shared understanding of the distinctions and parallels between human and artificial intelligence remains elusive. Conversations on critical themes, including trustworthiness, explainability, and ethics, often reflect implicit anthropocentric and anthropomorphic perspectives. Notably, the aspiration for human-like intelligence persists as the gold standard for Artificial Intelligence. Currently, we grapple with key inquiries: 1) How can we harness and effectively collaborate with these systems? When is it safe to entrust AI with decisions, and when is human judgment indispensable?; 2) What strategies enable us to leverage the unique strengths of both human and artificial intelligence?; 3) How can AI systems be deployed to effectively complement and compensate for the inherent limitations of human cognition (and vice versa)? This paper delves into these questions, emphasizing that the prospect of AI surpassing human intelligence soon is implausible.

Advancements in AI

Recent strides in information technology and AI suggest the potential for increased coordination and integration between humans and technology. Consequently, significant attention has focused on the development of Human-Aware AI, aiming for AI that functions as a “team member,” adapting to the cognitive capacities and limitations of human team members. Metaphors like “mate,” “partner,” “alter ego,” “Intelligent Collaborator,” “buddy,” and “mutual understanding” underscore a high degree of collaboration, similarity, and equality in “hybrid teams.” When human-aware AI partners emulate “human collaborators,” they must possess the ability to sense, understand, and respond to various complex human behavioral qualities, including attention, motivation, emotion, creativity, planning, or argumentation. Hence, these “AI partners” or “team mates” need to be endowed with human-like (or humanoid) cognitive abilities to facilitate mutual understanding and collaboration (Korteling et al., 2021).

Constraints of AI

Despite advancements, AI agents, for the foreseeable future, are likely to remain unconscious machines or specialized devices supporting humans in specific complex tasks. As digital machines with a fundamentally different operating system (digital vs. biological), AI agents exhibit distinct cognitive qualities compared to biological creatures such as humans and other animals. In general, digital reasoning and problem-solving agents only superficially resemble their biological counterparts. Recognizing this, it becomes crucial for human professionals collaborating with advanced AI systems (e.g., in military or policy-making teams) to develop a proper mental model regarding the differing cognitive capacities of AI systems in comparison to human cognition. This issue gains significance as AI systems advance and are deployed with increased autonomy. Consequently, this paper seeks to offer clarity and insight into the fundamental characteristics, differences, and idiosyncrasies of human/biological and artificial/digital intelligences. The final section introduces a global framework for constructing educational content on “Intelligence Awareness,” applicable to developing education and training programs for individuals who will use or collaborate with advanced AI systems in the near and distant future (Korteling et al., 2021).

The Future and AGI

In computer science, Artificial General Intelligence (AGI) refers to an intelligent system with extensive knowledge and cognitive computing capabilities, possessing comprehensive understanding across various domains. According to Cai (2016), AGI, seen as a kind of holy grail, represents the pursuit of an intelligent system capable of navigating unstructured, dynamic scenarios autonomously, minimizing the need for constant human oversight.

This paper contends that, for most applications, vigorously pursuing or anticipating systems with “human-like” AGI or abilities may not be practical or necessary. Insisting on adherence to the criteria of human intelligence for new forms of general intelligence inorganic to humans may be misleading. The possession of general intelligence by humans doesn’t dictate that artificial forms must mimic human qualities. The paper explores how we conceptualize (natural and artificial) intelligence in light of the likely potentials and imminent challenges of AI in the short- and mid-term future. It encourages contemplation as we navigate a dynamic AI landscape with an unpredictable future (Cai, 2016).

Conclusion

In conclusion, given the rapid evolution of AI technology and applications, there is a need for a more flexible conceptualization of intelligence that recognizes its diverse forms and combinations. A refined understanding of intelligence should encompass the fundamental characteristics, possibilities, and limitations of various cognitive system properties, both biological and artificial, without succumbing to anthropocentric or anthropomorphic misconceptions. This “Intelligence Awareness” is crucial for navigating the numerous possibilities and challenges presented by machine intelligence, especially in determining when to deploy AI in specific tasks and contexts.

To address this, the development of educational curricula is recommended, emphasizing new, targeted, and easily adaptable training formats and learning environments for human-AI systems. Future efforts should concentrate on creating training tools, methods, and content that are flexible and adaptive, capable of keeping pace with the dynamic changes in the AI field and meeting the diverse needs of different target groups and learning objectives.

References

Cai, S. (2016). Artificial Intelligence and Human Intelligence. Journal of Peking University (Philosophy and Social Sciences), 4. 

Korteling, J., van de Boer-Visschedijk, G. C., Blankendaal, R. A. M., Boonekamp, R. C., & Eikelboom, A. R. (2021). Human- versus artificial intelligence. Front Artif Intell. doi: 10.3389/frai.2021.622364.