Abstract
Artificial intelligence (AI) is a rapidly growing technological phenomenon that all industries wish to exploit to benefit from efficiency gains and cost reductions. At the macrolevel, AI appears to be capable of replacing humans by undertaking intelligent tasks that were once limited to the human mind. However, another school of thought suggests that instead of being a replacement for the human mind, AI can be used for intelligence augmentation (IA). Accordingly, our research seeks to address these different views, their implications, and potential risks in an age of increased artificial awareness. We show that the ultimate goal of humankind is to achieve IA through the exploitation of AI. Moreover, we articulate the urgent need for ethical frameworks that define how AI should be used to trigger the next level of IA.
Highlights
The term ‘intelligence’ has no standard definition and, Legg and Hutter present70 definitions covering a broad range of views [1]
John McCarthy of Dartmouth University brought together leading mathematicians and scientists for an extended brainstorming session on artificial intelligence [24,25]. They concluded with a suggestion: “We propose that a 2-month, 10-man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College . . . the study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”
If we apply artificial intelligence to the human mind, it is reasonable to posit that a self-learning algorithm might, in combination with a human brain, be able to create a feedback loop
Summary
The term ‘intelligence’ has no standard definition and, Legg and Hutter present. Jensen subscribed to Carl Bereiter’s definition of intelligence [2]; “what you use when you don’t know what to do” whilst Colom et al relied on Snyderman and Rothman’s understanding of crucial factors for intelligence defining it as “a general mental ability for reasoning, problem-solving, and learning” [3,4] In his definition of intelligence, Gottfredson touched upon several factors including the importance of learning quickly and learning from experience [5]. The concept of IA suggests a solution that lies “halfway between the entirely human and entirely automated capabilities” [21], thereby taking the form of tools that can help improve the efficiency of human intelligence [22] In this regard, the two primary approaches of AI and IA compete with each other, as the focus shifts between them following important developments. We contribute to academic research by discussing both AI and IA simultaneously, investigating their applications in detail, and evaluating their transformative contributions to future developments in AI and IA
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