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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?
Algorithmic discrimination
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.
Pseudo AI
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
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.
Show Notes:
- FREE Intro to CPMAI mini course
- CPMAI Training and Certification
- A Step-by-Step Approach to Running AI and Machine Learning Projects
- AI Glossary
- Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer
- Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU
- Glossary Series: Perceptron
- Glossary Series: Hidden Layer, Deep Learning
- Glossary Series: Loss Function, Cost Function & Gradient Descent
- Glossary Series: Backpropagation, Learning Rate, Optimizer
- Glossary Series: Feed-Forward Neural Network
- AI Glossary Series – Machine Learning, Algorithm, Model
- AI Glossary Series – Model Tuning and Hyperparameter
- AI Glossary Series: Overfitting, Underfitting, Bias, Variance, Bias/Variance Tradeoff
- AI Glossary Series: Operationalization
