AI Governance

AI Governance is the set of processes, policies, and tools that bring together diverse stakeholders across data science, engineering, compliance, legal, and business teams to ensure that AI systems are built, deployed, used, and managed to maximize benefits and prevent harm. AI Governance allows organizations to align their AI systems with business, legal, and ethical requirements throughout every stage of the ML lifecycle. (For a more thorough definition, please refer to our blog post: What Is AI Governance?)

All Terms

J

K

N

O

Q

U

V

W

X

Y

Z

1

A

2

B

3

C

4

D

5

E

6

F

7

G

8

H

9

I

12

L

13

M

16

P

18

R

19

S

20

T

E

A

A

A

A

A

AI Risk Management

A

R

A

Governance Artifact

G

Artificial Intelligence

A

Artificial General Intelligence

A

A

A

Autonomous System

A

A

Auditing or Audibility of AI Systems

A

Credo AI Audit Trail

C

A

Bias (Social vs. Statistical):

B

Conversational AI

C

Conformity Assessment

C

D

E

E

F

Foundational Model

F

General-purpose AI (GPAI)

G

Generative AI or genAI

G

H

Human-Centered Design

H

Human-in-the-loop

H

Human-on-the-loop

H

Impact Assessment

I

I

Interpretability

I

L

Machine Learning

M

M

Multi-Stakeholder Collaboration

M

P

Credo AI Policy Center

C

Credo AI Policy Pack

C

P

Programmatic RAI Assessments

P

R

Responsible AI License

R

A

R

Rulemaking Process

R

S

Social-technical Systems

S

S

Technical Evidence

T

T

Transparency Report

T

T

A

Project Failure Rate

P

Project Rejection Stage

P

Sunk Project Cost

S

B

Compliance Risk

C

T

AI GRC Project Rejection Rate

A

Transformative AI (TAI)

T