Ethical Risks and Principles of AI: A C-Suite Exploration

Featuring insights from industry experts, discover the ethical risks and principles of AI from a C-suite perspective. 

AI is changing the game for industries, creating vast opportunities and generating significant ethical, safety, and accountability challenges. As businesses increasingly adopt AI, the question of who is responsible for its governance and ethical deployment becomes crucial.

Who better to offer insights into this topic than our very own HotTopics c-suite community of executive thought leaders and technologists? In some of the recent instalments of our flagship event series, the Studio, we gathered audiences of executive technology leaders at Abbey Road Studios to sit in front of a live panel debating the evolving role of the c-suite in AI accountability. With input from industry leaders from companies including Thoughtworks, Barilla and the London Business School, the panellists explored key insights on ethical AI governance, the allocation of responsibilities and the potential risks and opportunities AI presents for society.

Ethical risks and principles of AI: overview

• AI and accountability
• The ethical risks and principles of AI deployment 
• Defining roles in AI governance
• Navigating AI opportunities and challenges
• Balancing innovation and AI ethics

AI and accountability

The general consensus around the roundtable panel “CIO, CTO or CAIO: Who is Responsible for AI?” was that AI’s implementation necessitates shared accountability across the executive team.

No longer confined to the remit of IT or technology departments, AI impacts all corners of an organisation. Thoughtworks’ CTO, Rachel Laycock, emphasised the need for a cultural shift toward an AI-first mindset, where every executive, regardless of their role, is accountable for its ethical use. “It is a shared accountability,” Laycock said. AI is a strategic imperative that influences decisions at the highest levels of leadership.

As businesses adopt AI at scale, panellists emphasised the role of key executives like the Chief AI Officer (CAIO), a relatively new title designed to manage AI integration across business functions. Laycock pointed out that this role bridges traditional CIO, CTO, and CDO responsibilities, ensuring that AI is integrated without creating silos. At Shell, for instance, AI has been elevated to an executive-level priority, with the CEO driving AI discussions and investments, as noted by Allan Cockriel, CIO and Group CISO.

The ethical risks and principles of AI deployment

AI promises transformative potential, it comes with a significant set of ethical risks—most notably, issues related to data bias, privacy concerns and misinformation. 

“There’s a laundry list of challenges.” Rachel Laycock highlighted the challenge of ensuring data integrity and preventing bias. AI systems often reflect the biases present in their training data, as evidenced by a cautionary tale shared by Sara Mubasshir, Head of Change at London Business School. She drew attention to the oximeter readings during the COVID-19 pandemic, which misread results for people of colour due to biassed data inputs.

These challenges underscore the importance of AI literacy and ethical training across all levels of an organisation. As Mubasshir pointed out, “we need to start talking about AI literacy” to bridge the gap between innovation and ethical deployment. The failure to understand these ethical ramifications can lead to harmful outcomes, from biassed decision-making systems to the breaching of privacy rights.

“My personal opinion is that private data is just as important to society as private property,” according to one panellist in the “No Data, No AI?” Food for Thought discussion. When considering the ethics and accountability of using AI, technology leaders need to emphasise the need to safeguard their data.

Defining roles in AI governance

The allocation of AI responsibilities within an organisation varies depending on industry needs and AI maturity levels. 

Amitabh Apte, Chief Digital and Business Technology Officer at Barilla, highlighted the company’s cross-functional AI board, a governance structure designed to manage AI initiatives across different departments. Apte stressed that AI is for everyone in the organisation, not just a single department or a centralised team. This democratised approach to AI governance ensures that all stakeholders are involved, fostering a culture of shared responsibility.

However, this raises a critical question: Who holds ultimate accountability for AI governance? Allan Cockriel noted that while the IT function manages technical aspects, the executive team governs strategy. This distributed approach allows companies to balance innovation with risk management. Barilla’s model reinforces this need for guardrails—a framework that ensures AI is developed and deployed ethically, without snuffing out innovation.

Navigating AI opportunities and challenges

AI’s rapid development, fuelled by advancements in generative AI and tools like OpenAI’s ChatGPT, has generated both excitement and concern. 

While AI offers opportunities to augment human productivity and drive business value, it also raises fears of job displacement and ethical misuse. In the roundtable debate “AI and the Future of Society” Allan Cockriel emphasised that organisations must help employees navigate these changes, equipping them with the skills and tools to coexist with AI, rather than fear it.

The tension between innovation and governance is evident in heavily regulated industries like finance and energy. Panellists acknowledged that AI governance frameworks need to evolve alongside the technology, ensuring that companies maintain compliance with emerging regulations while fostering innovation. This links back to Rachel Laycock’s remarks on the difficulty of getting AI systems from experimentation to production due to these regulatory hurdles, particularly in light of data privacy and ethical concerns.

Balancing innovation and AI ethics

The broader societal implications of AI were also a focal point of the discussion. 

Que Tran, CIO at DP World, echoed concerns about public scepticism toward AI, noting that people often fear new technologies due to uncertainty. This fear can be exacerbated by misinformation and the "hallucination" phenomenon in AI models, where systems generate incorrect or misleading information.

Despite these concerns, many panellists argued that AI will complement, rather than replace, human roles. Stuart Birrell, Chief Data Officer at EasyJet, likened the current AI revolution to the rise of the World Wide Web, where initial concerns eventually gave way to widespread acceptance and integration.

Looking for further reading on this topic? Check out the following roundtable discussions on AI and more in our c-suite insights section:

CIO, CTO or CAIO: Who is Responsible for AI? Who is responsible for AI in today's rapidly-evolving landscape? Expert panellists discussed accountability and responsibility for scaling AI initiatives in the C-suite.

AI and the Future of Society: From workforce training to tackling bias, ethics and new regulations, technology leaders must find the delicate balance between embracing AI's benefits and addressing genuine concerns.

Food for thought: no data, no AI? Not so fast: the truth is far more nuanced for the technology C-suite. Here’s why.