AI ethics & governance
Design and deploy Responsible AI solutions that are ethical, transparent, and trustworthy.
AI brings unprecedented opportunities to businesses, but also incredible responsibility. Its direct impact on people’s lives has raised considerable questions around AI ethics, data governance, trust and legality. In fact, Accenture’s 2022 Tech Vision research found that only 35% of global consumers trust how AI is being implemented by organizations. And 77% think organizations must be held accountable for their misuse of AI.
The pressure is on. As organizations start scaling up their use of AI to capture business benefits, they need to be mindful of new and pending regulation and the steps they must take to make sure their organizations are compliant. That’s where Responsible AI comes in.
So, what is Responsible AI?
Responsible AI is the practice of designing, developing, and deploying AI with good intention to empower employees and businesses, and fairly impact customers and society—allowing companies to engender trust and scale AI with confidence.
With Responsible AI, you can shape key objectives and establish your governance strategy, creating systems that enable AI and your business to flourish.
Build responsibility into your AI to ensure that the algorithms – and underlying data – are as unbiased and representative as possible.
To build trust among employees and customers, develop explainable AI that is transparent across processes and functions.
Empower individuals in your business to raise doubts or concerns with AI systems and effectively govern technology, without stifling innovation.
Leverage a privacy and security-first approach to ensure personal and/or sensitive data is never used unethically.
By creating an ethical underpinning for AI, you can mitigate risk and establish systems that benefit your shareholders, employees and society at large.
Responsible AI practices can be applied to any industry or function. Take Human Resources (HR) as an example. When done correctly, AI systems can allow organizations to make more ethical, effective and efficient talent decisions by eliminating potential sources of bias. Explore more in our interactive report.View now
Define and articulate a Responsible AI mission and principles, while establishing a transparent, governance structure across the organization that builds confidence and trust in AI technologies.
Strengthen compliance with current laws and regulations while monitoring future ones, develop policies to mitigate risk and operationalize those policies through a risk management framework with regular reporting and monitoring.
Develop tools and techniques to support principles such as fairness, explainability, robustness, traceability and privacy, and build them into the AI systems and platforms that are used.
Empower leadership to elevate Responsible AI as a critical business imperative and require training to provide all employees with a clear understanding of Responsible AI principles and criteria for success.
The Algorithmic Assessment is a technical evaluation that helps identify and address potential risks and unintended consequences of AI systems across your business, to engender trust and build supportive systems around AI decision making.
Use cases are first prioritized to ensure you are evaluating and remediating those that have the highest risk and impact.
Once priorities are defined, they are evaluated through our Algorithmic Assessment, involving a series of qualitative and quantitative checks to support various stages of AI development. The assessment consists of four key steps:
What is ethical AI?
Responsible AI enables the design, development and deployment of ethical AI systems and solutions. Ethical AI acts as intended, fosters moral values and enables human accountability and understanding. Organizations may expand or customize their ethical AI requirements, but fundamental criteria include soundness, fairness, transparency, accountability, robustness, privacy and sustainability.
What are concerns involving AI ethics?
AI—if built without the right algorithmic considerations, if trained on data that has inherent bias in it, or if left ungoverned—has the potential to perpetuate unintended consequences and not perform the task it was designed and intended to perform. All of which puts customer privacy and safety at risk, and weakens trust in the technology (and the company using it) in the process. Any company that has an intention of scaling AI needs to think about the ethical implications of using AI to make decisions that will impact not just the business, but its employees and customers.
What are the key principles of responsible AI?
The key principles of Responsible AI are:
What are steps to ensure AI is ethical?
Organizations should use the four pillars of Responsible AI to apply AI ethically and responsibly: