AI Governance

The purpose of our AI Governance Advisory service is to bridge this gap of mistrust between high-level management and AI-based systems by advising organizations in the following areas/directions:
  • Creating reliable AI models that produce consistent results (be it decisions, recommendations, insights):    
  • What can be the proper AI-technology for the problem at hand,
  • What shall be the proper KPIs for evaluating an AI-based system’s performance and ensure its controllability,
  • What needs to be in place organizationally for ensuring the Accountability of a given AI-based system
  • How to avoid biases that may affect the results produced by an AI-based system:
  • What are the standards for testing AI-based systems for bias,
  • How they can be interpreted
  • How to explain the decisions made by AI instead of a black box situation:
  • What are the suitable mechanisms for explaining the decisions of an AI-based system
  • How they can be implemented and at what stage
  • How to ensure AI-based systems are safe and secure:
  • What are the proper tests for ensuring the Robustness of an AI-based system?
Our teams of advisors at code4thought are subscribing to the idea that we need humans in the loop to ensure AI-based systems are as bias-free as possible. And those humans must have deep experience in auditing software systems via ML tooling and be guided by humans deeply experienced in the process.
Thus, we are ready to help and advise as to what are the best-practices for setting up the proper processes and infrastructure that will ensure your AI-based systems are Responsible, Reliable and can be Trusted.
During an advisory project, our teams follow a structured approach which helps our clients to govern an AI-based system in order to ensure its proper implementation, timely deployment and trustworthy operation.
Fact-based analysis
By using a set of proven and industry-accepted questionnaires our team collects data and information while optimising the time spent from our clients’ participants. By following a predefined and structured methodology we ensure we answer adequately all questions from our clients by bringing all facts to the table.
ISO 29119-11 Frame of Reference
By using the guidelines of the ISO 29119-11 standard for testing AI-based systems, our team provides actionable recommendations and insights on what is the state of practice for testing a system from the Bias, Explainability and Robustness perspectives.
Advise relevant in each stage of an AI-system’s lifecycle
Our advisory on AI Governance is relevant and applicable from the early stages of an AI-system’s inception to its final deployment in Production and helps both the manufacturers as well as the operators of an AI system.
Insights from a single data instance to boardroom
We create insights for both the people who design and implement AI-based systems, as well as the ones who are accountable for their operation and governance. We address the respective needs in all levels of an organization, from the engineers and all the way up to the C-suite.
Independent, objective advisory, so no strings attached with software vendors or big tech companies
Our team provides actionable advice and recommendations that are independent, impartial and objective. We have no stake in the outcome and focus only on the facts.
Pragmatic and actionable suggestions for improvements, so no theoretical or out of context advice
Our guidance and recommendations are practical, pragmatic and can help you to improve (at least) the controllability of your AI System. That means you can start implementing them right away with our guidance.
Diversity in our expertise
Our teams have been analyzing and testing AI-based systems from a diverse set of business (i.e. health-care, retail, high-tech) as well as technology (i.e. deep learning, rule based, decision trees) domains. All this expertise can help us understand your context ensuring that our advice fits to your needs.