Responsible Generative AI


Adopting complex and new technologies like generative AI should always be balanced against value gained and risks taken. We help you set up a framework to use generative AI in a way that’s trustworthy, safe and compliant.

When generative AI entered the public consciousness – thanks to high-profile tools such as ChatGPT – a flurry of interest and huge enthusiasm sparked countless ideas for business applications. From code development to client-facing chatbots, the potential is significant. But the technology also comes with an expanded set of risks – to businesses and society alike.

To navigate this situation, your business needs a systematic approach that enables you to harvest the business benefits of generative AI while also managing the risks of this new technology. Careful consideration of how you use generative AI will also ensure that you continue to comply with existing and upcoming regulations as well as stakeholder expectations.

Generative AI entails risks such as:

  • Intellectual property infringements on copyrighted, trademarked, patented, or otherwise legally protected materials if such material is used for training the underlying models without appropriate consent of the owners
  • Privacy violations if users input information that later ends up in model outputs in a form that makes individuals identifiable
  • Inaccurate output (“hallucinations”) that sounds extremely convincing and therefore can only be detected easily by an expert in the respective field

Since this is such a new technology, there may also be some inherent risks involved which are yet to emerge.
We promote a broad, human-centered, pragmatic, outcomes-focused and ethical approach to the use of generative AI based on the following principles:

  • Fairness: The AI design identifies and addresses inherent biases arising from the development team composition, data and training methods. The AI system is designed considering the needs of all impacted stakeholders and promotes a positive societal impact.
  • Resilience: The data used by the generative AI system components and the algorithm itself is secured from unauthorized access, corruption and/or adversarial attack.
  • Explainability: The generative AI’s training methods and decision criteria can be understood, are documented and are readily available for human operator challenge and validation.
  • Transparency: When interacting with generative AI, an end-user is given appropriate notification and an opportunity to select their level of interaction. User consent is obtained, as required for data captured and used.
  • Performance: The generative AI’s outcomes are aligned with stakeholder expectations and perform at a desired level of precision and consistency.

We assess your framework against the applicable regulation, set up suitable governance, processes and policies and look into the technical implementation. We leverage the right blend of technical, regulatory and risk management capabilities to stay focused on your desired business outcomes while getting to grips with the potential downsides of this new technology.

Ask us for support in:

  • Defining your risk appetite in pursuing the value of generative AI
  • Identifying and prioritizing the risks that your specific applications create
  • Setting up a framework to manage and monitor these risks

Partnering with you, it is our goal is to ensure you can answer the following questions with confidence:

  1. Which generative AI is used in your company, where and for which applications?
  2. Which risks arise from the use of generative AI in your company, and how are they managed?
  3. Which regulations are relevant for the use of generative AI in your company, and are you compliant with them?

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