You Can’t Manually Review Every AI #shorts #AI
AI governance is becoming critical as organizations deploy more intelligent systems across their operations. With predictions of over a billion AI agents entering the workforce in the coming years, traditional governance approaches simply cannot keep pace. How do you ensure your AI systems are using data responsibly without slowing down innovation? What happens when an AI agent makes decisions that were never explicitly programmed? And how do you build governance processes that scale alongside rapidly expanding AI adoption while maintaining trust with customers and regulators?
Blake Brannon is Chief Innovation Officer at OneTrust, where he leads product vision and strategic direction for the company’s AI-ready governance platform. He has been with OneTrust since 2017, previously serving as Chief Technology Officer, and has played a key role in scaling the platform to support privacy, data governance, risk, and responsible AI initiatives for large enterprises. Blake is based in Atlanta and holds an academic background from the Georgia Institute of Technology, with early research experience in network systems and wireless communications.
In the episode, Richie and Blake explore AI governance disasters, the importance of consent and data use, the rise of AI agents, the challenges of scaling governance processes, the need for continuous observability, the role of governance committees, strategies for effective AI governance in organizations, and much more.
Find DataFramed on DataCamp https://www.datacamp.com/podcast
and on your preferred podcast streaming platform:
Apple Podcasts:
https://podcasts.apple.com/us/podcast/dataframed/id1336150688
Spotify:
https://open.spotify.com/show/02yJXEJAJiQ0Vm2AO9Xj6X?si=d08431f59edc4ccd
Links Mentioned in the Show:
OneTrust - https://www.onetrust.com/
AI-Native Course: Intro to AI for Work - https://www.datacamp.com/courses/introduction-to-ai-for-work
Related Episode: From City Sewers to Sovereign AI with Russ Wilcox, CEO at Ar
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Playlist
Uploads from DataCamp · DataCamp · 0 of 60
← Previous
Next →
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
SQL Server Tutorial: Date manipulation
DataCamp
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
R Tutorial: Adding aesthetics to represent a variable
DataCamp
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
Python Tutorial: Preparation for modeling
DataCamp
Python Tutorial: Machine Learning modeling steps
DataCamp
R Tutorial: The prior model
DataCamp
R Tutorial: Data & the likelihood
DataCamp
R Tutorial: The posterior model
DataCamp
R Tutorial: An Introduction to plotly
DataCamp
R Tutorial: Plotting a single variable
DataCamp
R Tutorial: Bivariate graphics
DataCamp
Python Tutorial: Customer Segmentation in Python
DataCamp
Python Tutorial: Time cohorts
DataCamp
Python Tutorial: Calculate cohort metrics
DataCamp
Python Tutorial: Cohort analysis visualization
DataCamp
R Tutorial: Building Dashboards with flexdashboard
DataCamp
R Tutorial: Anatomy of a flexdashboard
DataCamp
R Tutorial: Layout basics
DataCamp
R Tutorial: Advanced layouts
DataCamp
Python Tutorial: Time Series Analysis in Python
DataCamp
Python Tutorial: Correlation of Two Time Series
DataCamp
Python Tutorial: Simple Linear Regressions
DataCamp
Python Tutorial: Autocorrelation
DataCamp
R Tutorial: The gapminder dataset
DataCamp
R Tutorial: The filter verb
DataCamp
R Tutorial: The arrange verb
DataCamp
R Tutorial: The mutate verb
DataCamp
R Tutorial: What is cluster analysis?
DataCamp
R Tutorial: Distance between two observations
DataCamp
R Tutorial: The importance of scale
DataCamp
R Tutorial: Measuring distance for categorical data
DataCamp
Python Tutorial: Plotting multiple graphs
DataCamp
Python Tutorial: Customizing axes
DataCamp
Python Tutorial: Legends, annotations, & styles
DataCamp
Python Tutorial: Introduction to iterators
DataCamp
Python Tutorial: Playing with iterators
DataCamp
Python Tutorial: Using iterators to load large files into memory
DataCamp
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
SQL Tutorial: Tables: At the core of every database
DataCamp
SQL Tutorial: Update your database as the structure changes
DataCamp
Python Tutorial: Classification-Tree Learning
DataCamp
Python Tutorial: Decision-Tree for Classification
DataCamp
Python Tutorial: Decision-Tree for Regression
DataCamp
Python Tutorial: Census Subject Tables
DataCamp
Python Tutorial: Census Geography
DataCamp
Python Tutorial: Using the Census API
DataCamp
R Tutorial: A/B Testing in R
DataCamp
R Tutorial: Baseline Conversion Rates
DataCamp
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
R Tutorial: Introduction to qualitative data
DataCamp
R Tutorial: Understanding your qualitative variables
DataCamp
R Tutorial: Making Better Plots
DataCamp
SQL Tutorial: OLTP and OLAP
DataCamp
SQL Tutorial: Storing data
DataCamp
SQL Tutorial: Database design
DataCamp
Python Tutorial: Introduction to spaCy
DataCamp
Python Tutorial: Statistical Models
DataCamp
Python Tutorial: Rule-based Matching
DataCamp
More on: AI Alignment Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
The ABCs of reading medical research and review papers these days
Medium · LLM
#1 DevLog Meta-research: I Got Tired of Tab Chaos While Reading Research Papers.
Dev.to AI
How to Set Up a Karpathy-Style Wiki for Your Research Field
Medium · AI
The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap
ArXiv cs.AI
🎓
Tutor Explanation
DeepCamp AI