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Salesforce Debuts AI Ethics Model: How Ethical Practices Further Responsible Artificial Intelligence

Salesforce is in the business of building human-centered solutions. When it comes to AI, that means making issues of accessibility and ethics central to the design and implementation process. And the company isn’t alone. Ethical AI practices — formal strategies for addressing ethical questions in AI development and implementation — are a growing area of focus for responsible leaders in the tech industry. 

Salesforce’s Ethical AI team, led by Kathy Baxter and Yoav Schlesinger, has released a new report on how these practices start, mature, and expand.

Driving the news: Research shows that ethics is more than just the latest buzzword. A staggering 90% of consumers believe that companies have a responsibility to improve the state of the world. 

The catch? Those same consumers don’t typically trust AI technology. 

Ethical AI practice lays the groundwork for sustainable relationships between the people who make or use AI and the users impacted by their work. 

What’s the impact: The new model developed by the Salesforce Ethical AI team examines several critical stages required to establish effective strategies that safeguard and encourage consumers: 

  • Stage 1: Ad hoc. Individual advocates generate small-scale strategies and work to earn buy-in. 
  • Stage 2: Organized and repeatable. Formal teams and resources coalesce efforts into an executable strategic vision. 
  • Stage 3: Managed and sustainable. These new teams develop the measures and mentality to make the practice viable long-term. 
  • Stage 4: Optimized and innovative. The practice pushes forward with a holistic vision and dedicated support to bake ethics into the organization at all levels. 

The Salesforce perspective: Salesforce’s maturity model — a descriptive analysis of how practices start and develop over time — leverages insight from top technology companies and emerging success stories in the field. It also leans heavily on Salesforce’s experience as a leader in ethical AI practice. 

A key take-away is that these crucial teams and resources start with individual employees and leaders who have identified the value of ethics to technology companies. For Salesforce, one of those advocates was Kathy Baxter, whose vision for more ethical AI led to a team dedicated to leading the industry in practical solutions and in-depth understanding.

Today, the AI ethics team not only develops its own strategy, but adds to the wider momentum behind a better, more responsible tech industry. 

Zoom out: With AI growing rapidly across industries, understanding how the practices that develop and implement the technology come together is invaluable. 

The work behind this new model shows that ethical AI practices take time and commitment. From developing unique, personalized principles to going beyond a basic ethics review, robust practices involve a strategic progression of resources. Knowing what to do, in what order, and why empowers advocates to build beyond the basics and center ethics as a keystone of responsible, value-adding innovation. 

More information: Check out the full AI Ethics Maturity Model to learn more about the stages of practice development and why they matter to businesses. 


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