'Nutrition labels' for models encourage transparency and
surface potential bias and model drift, while supporting open
source models
LAS
VEGAS, April 17, 2024 /PRNewswire/ -- SAS
INNOVATE -- Data and AI leader SAS is launching new
trustworthy AI products and services to improve AI governance and
support model trust and transparency. Model cards and new AI
Governance Advisory services will help organizations navigate the
turbulent AI landscape, mitigating risk and helping them pursue AI
goals more confidently. SAS has also published a Trustworthy AI
Life Cycle Workflow, mapped to the National Institute of Standards
and Technology (NIST) AI Risk Management Framework.
Model cards are like "nutrition labels" for
AI models.
"Our customers are enthusiastic about the potential of AI but
remain cautious about when and how to use it," said Reggie Townsend, Vice President, SAS Data Ethics
Practice. "They're asking good questions about responsible and
ethical AI. Our goal is to give them the tools and guidance, based
on decades of experience, to integrate AI in ways that boost
profitability while reducing unintended harm."
Model cards: Trustworthy AI's 'nutrition
labels'
It can be difficult to take something as complex and
sophisticated as an AI model and convert it into something easily
digestible for everyone involved in the AI life cycle. And as new
rules and regulations are passed around the world, the ability to
understand and share with regulators how a model is performing will
be crucial. Model cards, an upcoming feature in SAS®
Viya®, will serve stakeholders across the AI life cycle.
From developers to board directors, all stakeholders will find
value in a curated tool that supports proprietary and open source
models.
Releasing mid-2024, model cards are best described as "nutrition
labels" for AI models. The SAS approach is to autogenerate model
cards for registered models with content directly from SAS
products, removing the burden from individual users to create them.
Additionally, because SAS Viya already has an existing architecture
for managing open source, model cards will also be available for
open source models, starting with Python models.
Model cards will highlight indicators like accuracy, fairness
and model drift, which is the decay of model performance as
conditions change. They include governance details like when the
model was last modified, who contributed to it, and who is
responsible for the model, allowing organizations to address
abnormal model performance internally. The model usage section
addresses intended use, out-of-scope use cases, and limitations,
which will be key factors as transparency and model auditing likely
become regulated business operations. Model cards were showcased
earlier this year at SAS Insight, a conference for analysts.
"SAS is taking a thoughtful approach to how it helps customers
embrace AI, focusing on the practical realities and challenges of
deploying AI in real industry settings," said Eric Gao, Research Director at analyst firm IDC.
"Model cards will be valuable for monitoring AI projects and
promoting transparency."
New AI governance group led by ethical AI
veteran
With the proliferation of AI, SAS customers have become
increasingly concerned with how to use their data in ways that are
both productive and safe. To help them on their data and AI
journeys, SAS is launching AI Governance Advisory, a value-added
service for current customers.
Beginning with a short meeting, SAS AI Governance Advisory will
help customers think through what AI governance means in the
context of their organizations. SAS has piloted this service, and
customers have noted several benefits:
- Increased productivity from trusted and distributed decision
making.
- Improved trust from better accountability in data
usage.
- The ability to win and keep top talent who demand responsible
innovation practices.
- Increased competitive advantage and market agility from being
"forward compliant."
- Greater brand value for confronting the potential impacts to
society and the environment.
PZU Insurance of Poland is one
of the largest financial institutions in central and eastern
Europe. A longtime SAS customer,
PZU deploys AI in areas such as claims, sales, fraud
detection and customer care.
"Our AI governance conversations with SAS helped us consider
potential unseen factors that could cause problems for customers
and our business," said Marek
Wilczewski, Managing Director of Information, Data and
Analytics Management (Chief Data Officer/Chief Analytics Officer)
at PZU. "We better understand the importance of having more
perspectives as we embark on AI projects."
Industry veteran and ethical AI expert Steven Tiell has been hired as SAS Global Head
of AI Governance. Tiell, who led Accenture's global data ethics and
responsible innovation practice, is also the former Vice President
of AI Strategy at DataStax.
Building on emerging government standards
Last year, the US National Institute of Standards and Technology
(NIST) launched an AI Risk Management Framework. It has become a
valuable tool for organizations to design and manage trustworthy
and responsible AI in the absence of official regulations.
SAS has created a Trustworthy AI Life Cycle workflow, which
makes NIST's recommendations easier to adopt for organizations by
specifying individual roles and expectations, gathering required
documentation, outlining factors for consideration, and leveraging
automation to ease adoption. Organizations end up with a production
model with documentation showing that they did due diligence to
help ensure that the model is fair, and their processes do not
cause harm.
The workflow allows organizations to document their
considerations of AI systems' impacts on human lives. It includes
steps to ensure that the training data is representative of the
impacted population and that the model predictions and performance
are similar across protected classes. These steps help ensure that
the model is not causing disparate impact or harm to specific
groups. Furthermore, users can ensure that a model remains accurate
over time by creating human-in-the-loop tasks to act when
additional attention is needed.
The SAS Trustworthy AI Life Cycle workflow can be downloaded
from the SAS Model Manager Resources Github and will soon be
available through the NIST AI Resource Center.
Today's announcement was made at SAS Innovate, the data and AI
experience for business leaders, technical users and SAS Partners.
Keep up with the latest news from SAS by following @SASsoftwareNews
on X/Twitter.
About SAS
SAS is a global leader in data and AI. With
SAS software and industry-specific solutions, organizations
transform data into trusted decisions. SAS gives you THE POWER TO
KNOW®.
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reserved.
Editorial Contact:
Trent
Smith
trent.smith@sas.com
919-531-4726
sas.com/news
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