Exploring the differences between human and machine intelligence: towards technological singularity

Abstract

Many recent advancements in automation and other technologies can now be attributed to the use of Artificial Intelligence (AI), which has recently experienced significant advancements in capability and performance. ☐ Artificial Intelligence and related Machine Learning (ML) technologies are constantly evolving. While these advancements and their increasing incorporation into our daily lives are certainly to be marveled at, the use of this technology, like all technology advancements has both positive and negative effects. Creating accurate image classifiers has significant value for the medical researcher trying to differentiate benign from malignant cells, but other uses can have horrific outcomes such as in the case of ill-conceived aircraft flight control systems or the reduction in privacy brought about by facial recognition systems. ☐ The roots of our research began as an exploration of the use of AI in the cybersecurity domain specifically aimed at identifying a viable fourth factor for Multi-factor Authentication (MFA). What started as something you might call a "reverse Turing test" became an examination of about a dozen things that a human might be able to do versus what a machine might be able to do. This was followed by several focused investigations of the use of this technology (called cyberpsychology) to enhance conventional cybersecurity use cases (e.g. authentication). ☐ These insights into the currently perceived differences between human and artificial intelligence led to a second line of research to better explore more futuristic possibilities. Possibilities, not those as seen from a science fiction standpoint, but those we can use to better understand what hard science contributions have been or need to be made to better understand these differences. Key foundational studies are made in these areas to better define the problem area itself, the nature of the hard science contributions, and how machine intelligence can be classified and measured. And last, the need to better understanding where the ever-changing boundary is between human and artificial intelligence, and if the location of that boundary can be estimated over time.