Create an Ethics Committee to Keep Your AI Initiative in Check
Contemporary sensitivities to bias are growing, and this will only increase with the proliferation and ubiquity of Artificial Intelligence (AI). Organizations using AI are starting to recognize the role that strong, organization-wide values must play in fostering responsible innovation. Many companies are now building Data & AI Ethics Committees, to not only maintain an organization’s values-based intentions, but to increase transparency into how they use AI. The idea is not simply to address human bias, statistical bias, and fairness, but also to increase organizational maturity concerning how AI-based products and services impact stakeholders, including civil societies. An ethics committee can provide an institutional feedback loop for how AIs are performing in the real world, giving valuable insights to designers, engineers, and executive teams. Establishing this level of ethical governance is critical to helping executives mitigate risks as they incorporate AI into their products and services.
WITF-FM, a public radio, television, and online news broadcaster in central Pennsylvania, includes the following statement above select online news coverage: “WITF strives to provide nuanced perspectives from the most authoritative sources. We are on the lookout for biases or assumptions in our own work, and we invite you to point out any we may have missed.”
It’s not uncommon for news organizations to invite comments and feedback from their audience; in fact, most encourage it. But WITF has gone above and beyond a general invitation for engagement. This statement highlights the potential for bias in their own reporting — and their attempt to avoid it.
Contemporary sensitivities to bias are growing, and this will only increase with the proliferation and ubiquity of Artificial Intelligence (AI). Most of today’s AI systems are built via machine learning, a technique that requires any one of thousands of potential algorithms to “learn” patterns from extremely large stockpiles of data. This should produce a model that is predictive of future real-world scenarios, but bias skews the accuracy of these models. Organizations using AI are starting to recognize the role that strong, organization-wide values must play in fostering responsible innovation, and like WITF, many leaders are going above and beyond. For example, Marc Benioff, founder and co-CEO of Salesforce, vocally advocates for companies to take responsibility for their contributions to society. Those values are highly aligned with Salesforce’s company culture, which prioritized the creation of two first-of-their-kind roles: Chief Equality Officer (Tony Prophet) and a Chief Ethical and Humane Use Officer (Paula Goldman), to elevate the responsibility for protecting these organizational values to the C-suite.
With a strong commitment across the organization, businesses can align, distribute, and scale values-led decision-making, which builds tremendous trust with both internal and external stakeholders. This is the bedrock of a responsible organization.
But maintaining an organization’s values across products and services — particularly as organizations start to use AI to help make or inform decisions — will require strong internal governance. Consider a situation where AI technology is perceived as unfair or malfunctioning. Can the creator be held accountable? Is there recourse for consumers in the form of an accountable engineer, an internal governance board, or even external governance? To use the Salesforce example again, the company is governing itself via a stakeholder-rich ethics committee that oversees ethics-related decisions at the organization.
Every organization can create a strong internal governance framework to address how they design and implement AI. In collaboration with the Ethics Institute at Northeastern University, Accenture has released a report on Building Data & AI Ethics Committees, which can serve as a manual.
