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How SAS drives technology innovation ethically & responsibly

Responsible Innovation

As the market leader with the most trusted AI and analytics platform, SAS is committed to working with customers, partners and academia to increase the awareness of, and need for, AI that is ethical, equitable and sustainable.


Our Core Principles

Access to quality data, at the optimal time, interpreted with compassion, is essential to ethical and human‐centered innovation.

Technology does not exist in a vacuum. It affects us all in unexpected ways. Ethical dilemmas can present tensions that should be navigated in the most productive and least harmful ways. Managing challenges in a trustworthy manner requires an unwavering set of principles rooted in proven, effective strategies.

Human Centricity

Promote human well-being, human agency and equity.

Inclusivity

Ensure accessibility and include diverse perspectives and experiences.

Accountability

Proactively identify and mitigate adverse impacts.

Transparency

Openly communicate intended use, risks and how decisions are made.

Robustness

Operate reliably and safely, while managing potential risks throughout a life cycle.

Privacy & Security

Protect the use and application of an individual's data.

Our Approach

Responsible innovation requires us to ask not only "could we," but also "should we?"

From ideation through development and deployment, our principles are reflected in our people, our processes and our products. With a collaborative governance approach called the QUAD, we focus on Oversight, Platform, Controls and Culture to anticipate, mitigate and avoid unintentional harm, particularly for the most vulnerable.

Oversight

Ensures that internal and external AI-enabled technologies and processes adhere to data ethics principles. Advises leadership on sales, consulting, product development and procurement opportunities involving AI.

Platform

Absorbs and interprets expectations and demand, then develops AI technologies that align with market viability, SAS portfolio synergy, regulatory compliance and data ethics principles.

Controls

Monitors, audits and seeks compliance with data ethics principles. Provides organizational checks and balances to identify mitigation needs before AI-related technologies and services are made public.

Culture

Cultivates an ecosystem of creators, contributors and consumers of AI for knowledge sharing, collaboration and the normalization of behaviors and practices aligned with data ethics principles.

The SAS approach to using GenAI responsibly

A particularly hot subfield of artificial intelligence – GenAI – has garnered significant attention across industries and geographies due to its considerable promise and possible risks. Many companies, including SAS, are now exploring guidelines for appropriate employee use of GenAI technologies.

Decisions about using this technology should be deliberative, thoughtful, and include perspectives from the highest levels of an organization. With that mindset, and with input from SAS Legal, SAS’s Artificial Intelligence Oversight Committee, and SAS’ Executive Leadership Team, SAS has established a formal and comprehensive generative AI policy to govern employees’ use of GenAI for business purposes

The GenAI policy includes requirements such as:

Every GenAI use case must involve meaningful, substantive human review of any generated content, including for accuracy, unintended bias and other quality issues.

SAS employees must take care to protect IP belonging to SAS or third parties and must protect confidential information whether belonging to SAS, customers, vendors or other business partners.

The use of GenAI must be disclosed in appropriate circumstances, for example, to recipients of content generated by AI if necessary to avoid misleading them.

All uses of GenAI must respect the privacy rights of our employees, partners and customers.

This policy ensures that SAS' use of GenAI aligns with our organizational values and principles of responsible innovation. Customers who look to SAS as a trusted technology partner can also trust SAS to use GenAI tools responsibly. Our GenAI policy helps SAS employees across the company understand the concerns customers may raise when evaluating technology for adoption, which will lead to better products that our customers want to use and stronger customer relationships based on mutual trust.

The SAS approach to the EU AI Act

Read our statement on the EU AI Act, how we're working with our customers and how SAS is committed to trustworthy AI use and development.

Trustworthy AI: Explore how SAS promotes human ingenuity

Training

SAS Training on Trustworthy AI

Product

SAS® Viya® Platform

Solution

AI for every industry

Our vision is a world where data empowers people to thrive. We pursue that vision through trustworthy and responsible innovation." Reggie Townsend Vice President of Data Ethics Practice SAS
Our vision is a world where data empowers people to thrive. We pursue that vision through trustworthy and responsible innovation." Reggie Townsend Vice President of Data Ethics Practice SAS

SAS Data Ethics Practice

Our Data Ethics Practice is a guiding hand for our responsible innovation efforts, ensuring our platform, processes and services keep the focus on people, with an “ethical by design” approach throughout product development and market strategy. The Data Ethics Practice is led by Reggie Townsend who also is a member of the National Artificial Intelligence Advisory Committee that advises the U.S. President and the National AI Initiative Office on a range of issues related to the development and use of AI.

Resources to keep the AI conversations going

Blog

Trustworthy AI blog

Data for Good

Data for Good stories

Customer stories

All customer stories

Blog

5 ethical questions to consider before making AI-driven decisions

Ebook

A comprehensive approach to trustworthy AI governance

Blog

Understanding AI governance

Data for Good

Bringing together humans and AI to detect deforestation

Analyst event

SAS Inside Intelligence 2023 Conference


SAS Viya helps a biopharmaceutical group collaborate on data, streamline processes and deliver trial results to regulators faster.