Artificial intelligence technology is being used in more and more applications, and it is expected to be used in more and more
tasks to automate as much as possible. To prepare for this future, we must understand the capabilities and limits of the technology.
Capability limitations, transparency/ethics issues, lack of sustainability, and limited availability and access are stopping AI from
being applied to even more applications. In order to identify whether availability/costs is the most significant factor holding AI back
from widespread adoption and whether AI as a service is the solution to these factors, qualitative research was conducted.
Four AI experts at The University of Maryland Baltimore County were interviewed. The interviews shed light on capability limitations,
transparency/ethics issues, and provided insight on the drawbacks of AI as a service. The interviewees noted AI has a lack of
understanding of causality, deficiencies in planning, decision making, emotion, creativity, collaboration, and the lack of the ability to
carry over experience from one task to another. They also explained that AI also has a black box issue, which means the researchers
themselves do not completely understand why the AI makes a decision, which can lead to biases. And while AI as a service will have a great impact on
the adoption of AI, AI as a service still requires experts and a lot of resources to customize and apply. And for many applications, AI as a
Service will not suffice and many might not want to share their data. These results indicate that AI must be further developed, the issues of
ethics and transparency, sustainability, and reliability must be further researched and addressed.
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