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In celebration of Women’s History Month, the Salesforce Women’s Network hosted its inaugural Women in AI Day event on March 26th, 2024 in the Salesforce Tower in San Francisco. The event was a gathering of Salesforce women leading the work on ethical and responsible AI at Salesforce.

We have established a set of five guidelines that build upon our Trusted AI Principles to provide more detailed guidance for the responsible development and implementation of GenAI.

It is not enough to deliver only the technological capabilities of AI – we also have an important responsibility to ensure that AI is safe and inclusive for all. These are our commitments to building AI responsibly.

We summarize insights from our FAccT 2022 CRAFT workshop that focused on Concepts of Fairness & Transparency, Applied RAI Practices, Organizational Approaches to RAI & Cultural Change, and Public Policy & Regulation.

December 21, 2021 The leading AI research conference, NeurIPS 2021, has recently wrapped up, spanning seven very full days, 2,344 accepted papers, eight invited talks, ten tutorials, and nearly 70 workshops. Though there was diverse and innovative thought leadership on display, I found myself drawn to the particular topics

August 5, 2021 In June 2021, four of us from the Salesforce AI Ethics and Conversational Design teams collaborated with the Montreal AI Ethics Institute [https://montrealethics.ai/] (MAIEI) to facilitate a workshop on the responsible creation and implementation of chatbots and conversational assistants. Connor Wright [https://www.linkedin.com/

February 2020 Summary from FAccT 2020 CRAFT Session > AI Ethics practitioners in industry look to researchers for insights on how to best identify and mitigate harmful bias in their organization’s AI solutions and create more fair or equitable outcomes. However, it can be a challenge to apply those

At Salesforce, we take seriously our mission to create and deliver AI technology that is responsible, accountable, transparent, empowering, and inclusive. These principles ensure that our AI is safe, ethical, and engenders trust.

Learn about the ethical implications of voice for business and how to make them an operational and strategic priority now—before you’re too far down the path.

Published: May 30, 2019 With the advent of low-code developer tools, people of varying skill levels and backgrounds — not just those with PhDs — are not only able to leverage the benefits of artificial intelligence (AI), but also build intelligent systems. As access to AI widens and the depth of its

You may be the first person in your company focusing on the need to create or implement ethical AI. If so, I’d like to share some lessons learned that could help you in your work.

This post is for those responsible for implementing AI systems but do not have a background in data science, statistics, or probability. The intention is to create an approachable introduction to the key concepts to identify potential bias (error) in their training data.

What kind of world do we want for ourselves, those we love, and future society? How do we are organizations, employees, customers, and members of society ensure that technology is in service of society and not the other way around?

In this article, I will focus on mechanisms for removing exclusion from your data and algorithms. Of all the interventions or actions we can take, the advancements here have the highest rate of change.

This is part one of a two-part series about how to build ethics into AI. Part one focuses on cultivating an ethical culture in your company and team, as well as being transparent within your company and externally.