Key Concepts from ACCT 331: Introduction to Applied Artificial Intelligence

These flashcards cover the key topics and concepts discussed in the ACCT 331 introductory lecture on applied artificial intelligence, focusing on the business implications of AI, the role of business translators, and the end-to-end machine learning workflow.

What represents the next leap in financial services according to the lecture?

Agentic AI, which goes beyond task automation to systems that can reason, plan, and act with autonomy.

Why are many organizations failing to achieve a measurable impact from Generative AI?

Due to a narrow focus and dramatic conclusions that create a misleading narrative of widespread AI failure.

What primary role does a business translator play in the intersection of business and data science?

They work closely with both business and data science teams to ensure project goals align with business needs.

What are the typical stages in the end-to-end machine learning workflow?

Data collection, data cleaning and feature engineering, model training, evaluation, and deployment.

What is the 'Deployment Paradox' mentioned in the lecture?

Some decisions' value is hard to estimate before deployment.

What does feature engineering improve?

The performance of the model by selecting the right features and preparing them appropriately.

How is exploratory data analysis (EDA) utilized in data science?

To analyze and investigate data sets and summarize their main characteristics, discovering patterns, and spotting anomalies.

What is a significant challenge faced by organizations in deploying AI solutions according to the lecture notes?

Executive alignment and managerial approval are often major blockers to successful deployment.

What does the MLOps workflow involve?

It involves data collection, experimentation, evaluation throughout a multi-staged deployment process, and ongoing monitoring.

Why is it important to plan deployment before coding begins in machine learning projects?

To ensure that the deployment, business metrics, and change management plan are designed ahead of time, reducing failure risks.