BCG GAMMA Responsible AI

Deliver Powerful Business Results with Responsible AI

When done right, responsible AI isn’t simply a framework to mitigate risk. It’s a way to deliver transformative business impact. BCG works with companies to make responsible AI a reality.

As artificial intelligence plays a more central role in business and society, so does the need for ensuring its responsible use. The financial and reputational risks of AI failures are real, but they can be managed if organizations take the right steps.

Our philosophy is twofold: first, responsible AI should not be viewed strictly as a defensive maneuver—but also as a source of value. Second, the principles of responsible AI offer an important starting point, but they must be translated into action.

The Business Case for Responsible AI

Companies do not need to choose between protecting customers with responsible AI and boosting the bottom line. Companies can both realize the transformative power of AI and amplify its benefits by developing AI in a responsible manner. Time and again, BCG research has shown that companies with a strong sense of purpose and a focus on total societal impact outperform their peers. Incorporating an organization’s authentic purpose and AI ethics into the core of AI will:

  • Boost the bottom line. Companies that embrace responsible AI—and publicize that fact—build trust, improve customer loyalty, and ultimately enhance revenues. Lack of trust, on the other hand, carries a high financial cost.
  • Differentiate the brand. Customers are increasingly choosing to do business with companies whose demonstrated values align with their own. Organizations with a strong sense of purpose are more than twice as likely to generate above-average shareholder returns, whereas AI without integrity will fail brands every time.
  • Improve recruiting and retention. Responsible AI attracts the elite digital talent critical to the success of firms around the world. In the UK, one in six AI workers has quit his or her job rather than help to develop potentially harmful products; that’s more than three times the rate for the tech sector as a whole. A well-constructed responsible AI program empowers workers to innovate freely within the bounds of AI ethics.

How BCG Helps Companies Bridge the Responsible AI Gap

Companies that recognize the need for responsible AI usually begin by developing principles to guide their actions. But they sometimes struggle to move from high-level principles to tangible changes in the way they build AI solutions. We call this the responsible AI gap. Companies must bridge this gap if they want to unlock the true potential of responsible AI, and they can do so by taking BCG’s six simple steps.

How We Work with Clients

When we work with clients to implement the six steps of responsible AI, our perspective is informed by the following beliefs:

Don’t just philosophize, operationalize. Many companies have developed responsible AI principles, but very few have changed how they operate. Bridging the gap between principles and actions is our focus.

Play offense, not defense. When companies focus strictly on risk mitigation, they miss the upside potential of responsible AI. Our holistic approach helps companies understand how to realize the sources of value from AI ethics.

Look at systems, not algorithms. Most frameworks around artificial intelligence and business ethics focus exclusively on algorithms, but problems can arise anywhere in the AI value chain—from data collection through decision making. Algorithms and data constitute only 30% of AI; the remaining 70% comprises business processes. Ignoring that 70% means ignoring a significant source of concerns about responsible AI. Our approach considers the entire AI system, end to end.

Start from a position of strength. We use our proprietary Responsible AI Organizational Maturity Assessment to help companies evaluate their organizations and analyze their readiness for responsible AI. We provide a heat map of strengths and weaknesses in such key areas as data and privacy, fairness and equity, and social impact.


Tools to Enable Responsible AI

As part of our broader commitment to responsible AI, BCG has developed a set of tools that help companies achieve their business goals and preemptively address the repercussions that AI can have on individuals and society. Companies can use these free tools to ensure their AI programs are, in fact, responsible.

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CodeCarbon

AI can benefit society in many ways. But given the amount of energy that’s needed to support AI’s computing requirements, these benefits can come at a high environmental price. CodeCarbon is a lightweight software package that can be seamlessly integrated into a company’s Python code base. The software estimates the amount of carbon dioxide that will be produced by the cloud computing resources needed to execute the code. It then shows developers how they can lessen emissions by optimizing their code or by hosting their cloud infrastructure in regions that use renewable energy.

GAMMA FACET

GAMMA FACET

Many business users treat AI as a technology black box that produces positive business results—but does so in “mysterious” ways. FACET, which BCG designed around the leading Python package scikit-learn, helps human operators understand advanced machine learning models. Now able to “open the box,” data scientists and business users can make decisions that save money, maximize yield, retain customers—and ensure that the end result is, indeed, responsible. FACET can be applied to a broad range of use cases, from improving patient outcomes to optimizing complex supply chains.

Learn More About Responsible AI

Responsible AI Builds Trust in Government

Responsible AI Builds Trust in Government

To earn the public’s support, government use of advanced analytics must include stakeholder input, proper controls, regular reviews, and contingency plans for lapses.

Tracking Your Responsible AI Journey

Key performance indicators help organizations guide their AI projects to successful, responsible, and meaningful results. Here are five KPI categories to keep your eye on.

How to Use AI Responsibly

In this panel discussion, BCG GAMMA’s chief AI ethics officer, Steve Mills, explores the challenges that companies are facing when it comes to responsible AI and reveals tangible strategies on how to overcome them.

Data Bias in AI and its Root Causes

Inherent errors can greatly compromise the validity of the data used in artificial intelligence programs. Understanding how and where such distortions arise can help reduce them significantly.

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