What people often think AI is

Beyond the Hype: The Nuanced Reality of AI 🤖

What people often think AI is:
• Data: A static entity that AI can automatically turn into insights.  
• AI: A magic wand that can do anything.
• Value: The automatic result of applying AI to data.

What AI actually involves:
• Data: A dynamic process of selecting, sourcing, and synthesizing diverse data.
• AI: A complex process involving data engineering, feature engineering, scaling, modeling, and deployment. 
• Value: An ongoing process of extracting insights, monitoring performance, and iteratively improving models.

Key Constraints:
• Legal: AI systems must be developed and used within legal and regulatory constraints.
• Ethical/Transparency: AI must be used fairly, transparently, and ethically.
• Historical Bias: Models can inherit bias if trained on biased data. 
• Security: AI systems must be secured from threats and breaches

.