PwC's Responsible AI

AI you can trust

AI is bringing limitless potential to push us forward as a society — but with great potential comes great risks.

Responsible AI (RAI) is the only way to mitigate AI risks. Now is the time to evaluate your existing practices or create new ones to responsibly and ethically build technology and use data, and be prepared for future regulation. The payoff for early adopters is an edge that competitors may never be able to overtake.

When you use AI to support business-critical decisions based on sensitive data, you need to be sure that you understand what AI is doing, and why. Is it making accurate, bias-aware decisions? Is it violating anyone’s privacy? Can you govern and monitor this powerful technology? Globally, organisations recognise the need for Responsible AI but are at different stages of the journey.

Potential AI Risks

A variety of factors can impact AI risks, changing over time, stakeholders, sectors, use cases, and technology. Below are the six major risk categories for application of AI technology.

Performance

AI algorithms that ingest real-world data and preferences as inputs may run a risk of learning and imitating possible biases and prejudices.

Performance risks include:

Risk of errors
Risk of bias and discrimination
Risk of opaqueness and lack of interpretability
Risk of performance instability

Enterprise

AI solutions are designed with specific objectives in mind which may compete with overarching organisational and societal values within which they operate. Communities often have long informally agreed to a core set of values for society to operate against. There is a movement to identify sets of values and thereby the ethics to help drive AI systems, but there remains disagreement about what those ethics may mean in practice and how they should be governed. Thus, the above risk categories are also inherently ethical risks as well.

Enterprise risks include:

Risk to reputation
Risk to financial performance
Legal and compliance risks
Risk of discrimination
Risk of values misalignment

Our recommendations: Overcoming risks with Responsible AI

As organisations start to adopt AI, they need to be aware of certain barriers that may complicate technology implementation. Being aware of emerging AI regulation to govern the use of AI is only one part of the equation in mitigating risks. They will also need to look inwards and challenge any siloes in their approach to AI and data governance, and assess if their workforce has the necessary skills critical to AI adoption.

Here are 3 steps organisations can take to build greater trust in AI.

Take a multi-disciplinary approach to governance

To govern the use of AI, ensure that all stakeholders are involved. This means the team tasked with overseeing governance should comprise representatives from various areas of the business, including leadership, procurement, compliance, human resources, technology and data experts, and process owners from different functions.

If there is an existing governance structure in place, you may extend it by adopting a three lines of defence risk management model.

Build up your AI risk confidence

Ensure that you have the right AI policies, standards, controls, tests and monitoring for all risk aspects of AI.

Having a common AI playbook may serve as a ‘how to’ guide for approaching new AI initiatives to build trust in this technology. It may be helpful to guide how you collaborate and discuss risks based on your goals, while identifying the level of rigour required to address risks based on their severity.

Act to maintain performance

Keep the momentum going as you familiarise yourself with AI and learn how to manage the risks. Observing good governance and risk management may not necessarily slow you down in this regard. The right level of explainability, for example, will depend on each AI model’s level of risk and required accuracy levels, allowing for quicker progress in some areas than others.

Download the full report (PDF)

PwC’s Responsible AI Toolkit

Your stakeholders, including board members, customers, and regulators, will have many questions about your organisation's use of AI and data, from how it’s developed to how it’s governed. You not only need to be ready to provide the answers, you must also demonstrate ongoing governance and regulatory compliance.

Our Responsible AI Toolkit is a suite of customisable frameworks, tools and processes designed to help you harness the power of AI in an ethical and responsible manner - from strategy through execution. With the Responsible AI toolkit, we’ll tailor our solutions to address your organisation’s unique business requirements and AI maturity.