The Growing Impact of Artificial Intelligence and AI Assessment Frameworks
The dawn of the 21st century brought with it a profound shift in technology. As we explore the digital era, the reality of Artificial Intelligence (AI) is becoming more prominent[1]. The idea of automated systems that emulate human cognition and shape human activities, brings to mind a technologically advanced dystopian future[2]. The expanding influence of AI prompts the need for an efficient AI assessment framework[3], enabling us to properly evaluate its impact.
Creating a Harmonious AI Assessment Framework
An AI assessment framework is like a symphony, with every note symbolizing an evauative standard that comes together to create a harmonious melody. This framework intertwines these notes, offering a method to assess the complexity, effectiveness, and ethical grounding of AI systems[4]. A vital component within this AI assessment framework is understanding the complex nature of an AI system – the ‘perplexity’ characteristic.
Unraveling ‘Perplexity’ and ‘Burstiness’ within AI Systems
‘Perplexity’ presents an interesting contradiction. It dissects the complexity of AI decision-making and also measures its predictability or unpredictability. ‘Burstiness’, another key metric, is considered essential for creating AI models that better mimic human-like understanding[6].
Developing an All-Inclusive AI Assessment Framework
Given the perplexing and bursty nature of AI, a well-suited AI assessment framework should reflect these considerations[7]. The framework should also incorporate elements like transparency, reliability, and accuracy, while ensuring fairness and eliminating biases[8]. An AI assessment framework is a crucial asset for AI research, providing valuable insights into the effectiveness, legality, and ethics of AI applications within important societal areas like healthcare, education, and judiciary[9].
Moving Towards a Future Enhanced by AI and AI Assessment Frameworks
Whilst gaining deeper insights into AI may seem like a never-ending journey[10], the adoption of evaluative strategies, which enhance transparency, reliability, fairness and bias-control, can certainly facilitate progress[11]. The implementation of a structure like the AI assessment framework, that integrates these evaluative measures, equips us with the knowledge to understand and navigate the exciting yet challenging arena of AI, thereby preparing us for the ever-evolving digital landscape[12].
