In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Algorithmic Discrimination, Governance, Pseudo AI. Why are these terms vital in the AI landscape? And what do they mean?
If you’re unfamiliar with the term algorithmic discrimination, it’s when bias in data used to train the algorithm can result in unfair decisions and results. When using algorithms to make decisions, especially ones that impact humans such as loan decisions, it’s important to keep a human in the loop to oversee the results. If you don’t there can be dangerous consequences.
The concept of Pseudo AI delves into the deceptive portrayal of AI capabilities. It refers to systems that claim to be AI-driven but lack true intelligence. It’s when a company or product claims the use of AI for a given task, but is actually using humans to perform those tasks, without properly disclosing the use of humans to perform those tasks. This can also be dangerous and deceitful.
Governance in AI refers to the framework and regulations required to ensure trustworthy and ethical AI development and deployment. It’s the processes and structures for supervision and control of a given system or organization. Specifically in AI, governance refers to policies, procedures, record keeping, auditing, controls, measures, guidelines, practices, tools, and systems that ensure proper and compliant functioning of systems according to organizational needs.
Join us in this episode as we unpack the significance of these terms. We also explore real-world implications and examples of algorithmic discrimination and pseudo AI. We also discuss the necessity of ethical considerations and governance in shaping AI’s future.
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