Avoiding the Bermuda Triangle of AI, Governance and Ethics

• Corporate governance is having to deal with AI explanability – if you can’t explain what the AI does, then who is accountable for it?
• AI is programmed to be constructive and plausible – so it will always pretend to understand what you’ve done and try to improve it. But what if, what you’ve already given it is ok?
• The objectives of the AI don’t always align with your business.
• The smarter the AI gets, the further it might get from the objectives.
• The AI is simply using training data, it’s not a human mind.
• It can do complex things but it doesn’t teach anyone anything.

What is AI?

• The simulation of human intelligence.
• It offers a huge business opportunity
• Large language models have been the biggest breakthrough in AI and have now been adopted by many – it is largely taking training data and applying it to a new task.
• LLMs are getting faster, cheaper, and more efficient.
• AI does its best things when given free rein but this brings the biggest risk.
• AI is fantastic at analysing large data sets but the key is to bring in human controls at the right time and level.

Challenges in AI governance?

Speed & complexity: there’s a lot of change in AI

• The growth of the model is fast and makes it difficult to keep up.

Ethics: AI repeats our biases

• The AI will do what it’s programmed to do, but is it effective?
• As it gets faster it gets harder to pick these biases up.
• AI and sample bias – we take the data available to us and we use this as training. But is the data biased?
• We don’t tend to question the output from AI in the same way that we question humans.
• Control: AI is unpredictable. AI is trying to make massive predictions but it can get it wrong. This can affect corporate reputation.

Profit and safety

• We need to set a goal to make it profitable to be safe.
• As a board of directors, there are different things to think about like strategy, competitiveness, capital allocation, AI risks, and technology competency.
• The board should have competencies in AI but also in ethics, and not necessarily as a combined thing. 

Principles of AI governance

• Critical success factors for AI in business include:
  • Strategy: what will AI enable you to do that you couldn’t do before?
  • Implementation.
  • Data quality: data needs to be accurate, and relevant.
  • Skills and expertise: you need data scientists and AI specialists.
• Fundamental principles of AI governance:

• Transparency and explainability.
• Ethical and responsible use.
• Accountability including liability management.
• Privacy and data protection.
• Safety, security and reliability.
• Human centrism and oversight.

Five challenges and possible solutions for boards:

• Speed & complexity: Implement agile governance structure.
• Ethical implications: Engage diverse stakeholders for an AI-specific framework.
• Control: Establish clear accountability for AI-driven decisions.
• Profit vs safety: Align incentives with both corporate and ethical initiatives.
• Knowledge requirements: Enhance board education; recruit specialist advisors.

As AI technologies become integral to operational landscapes, the imperative for clear, effective governance has never been more critical.

Join us for this webinar where you’ll discover the strategic frameworks and best practices for integrating AI within your organisation’s governance structures.

Key insights you’ll gain:

• Strategic implementation frameworks: Actionable strategies for the seamless integration of AI into your organisation.
• Risk management in the AI era: The complexities of managing risk and ensuring compliance when AI is part of your decision-making fabric.
• Cultivating an ethical AI culture: Foster a culture that embraces the responsible use of AI.

Clark Boyd is CEO and founder of AI marketing simulations company Novela. He is also a digital strategy consultant, author, and trainer. Over the last 12 years, he has devised and implemented international strategies for brands including American Express, Adidas, and General Motors.

Today, Clark works with business schools at the University of Cambridge, Imperial College London, and Columbia University to design and deliver their executive-education courses on data analytics and digital marketing. He is also a faculty professor of entrepreneurship and management at Hult International Business School.

Clark is a certified Google trainer and runs Google workshops across Europe and the Middle East. He has delivered keynote speeches on AI at leadership events in Latin America, Europe, and the US