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How to formulate an ethical approach to AI

3 mins read
  • As regulators catch up, organisations must be proactive in developing their own controls
  • Governance frameworks should allow for innovation, while putting protections in place
  • Aligning policies with corporate values and addressing stakeholders’ concerns are vital
  • Consider creating an AI oversight board and investing in ethics and compliance training 
  • AI must be tempered by human emotional intelligence

Ty Francis CBE, Chief Advisory Officer of LRN

If the hype is to be believed, we are now at a pivotal moment for the adoption of artificial intelligence into everyday (and business) life. The release of ChatGPT late last year which garnered 100 million users within months suggests that generative AI (i.e. AI capable of creating sophisticated written content, images etc) is poised to revolutionise ways of working and transform what it means to be creative in ways that we do not yet fully understand. 

From an organisational standpoint, there are as many threats as opportunities, both in the sense of commercial competitiveness and in terms of how it impacts how entities are run. Ethical questions will need to be addressed, and suitable governance frameworks put into place to ensure that the use of AI is controlled in such a way that allows innovation to flourish, whilst also providing the necessary protections.

There’s clearly an urgent need for appropriate regulation and compliance controls. However, as we’ve seen in the past with the birth of the internet itself and later, with the emergence of social media, when new technologies have the power to change the world, the world (and certainly regulators) have to play catch up. While organisations wait for appropriate rules to be developed on a national and international scale, they will need to take the initiative for themselves.

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Grasp the governance mettle

That means proactively developing internal frameworks – and soon. This should include defining how generative AI fits within an organisation’s own ethical values (and complies with any relevant existing standards), designing clear governance guardrails, developing monitoring systems to ensure compliance from the outset and on an ongoing basis, and setting out clear responsibilities, underpinned by accountability.  

Your people need to know how AI will be used in the workplace and for what purposes. They must be told what they are and are not allowed to use it for. Where its use is permitted, what parameters there are around its use? Who is responsible if anything goes wrong, and equally, how can they communicate what is going right so that the organisation can learn from it to mitigate risk and seize opportunities? 

They will also want to understand what this means for their jobs and for corporate culture (both internally and externally-facing), what safeguards will be put in place around issues like the potential for bias and discrimination in AI processes or how security and data privacy will be managed. Other stakeholders such as shareholders will doubtless want to have a handle on this as well.

Therefore, it’s vital to develop a set of governing principles setting out the use of – and controls around – AI. This should be backed up with policy documents that are clear and accessible to all to explain what the organisation’s position on AI should look like on the ground and how compliance will be embedded from the top down. 

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Take a co-ordinated approach

For many organisations, it makes sense to establish an AI ethics governing body or board, tasked with developing best practice, guiding behaviours and implementing oversight, which has the full backing of the senior leadership team. Its role should include giving the green or red light to specific projects on a case-by-case basis in line with company policy, measuring compliance and making sure the company is ahead of (or at least aware of) new developments in this fast-moving arena. 

Given the intricacies of AI, and the huge potential for ethical ‘grey areas’ it throws up, this is a very tall order, requiring constant, co-ordinated (human) vigilance, for which on-going, expert support in terms of guidance and advice, will be needed.

AI ethics and compliance training is key throughout the organisation too, to educate staff on how policies on AI use align with corporate values and ethos, and how to evaluate and manage AI projects in line with company policy, considering all the potential impacts (both positive and negative) as a vital part of the process. Since those impacts may well reverberate far beyond the company’s walls, it’s vital to think about the wider societal context of any new AI initiative planned. Whatever the rules (or lack of) governing the use of AI for commercial ends, the reputational risk of getting it wrong is already very real.

Until fully fit-for-purpose regulatory frameworks around the use of AI – and generative AI in particular – are ready, organisations must take it upon themselves to harness its power with due care and attention. Embracing it unfettered is likely to be a risky strategy, but so too is ignoring it altogether. 

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An open-minded, yet guarded and co-ordinated approach is a sensible one: making sure no one is free to ‘go rogue’ with this technology; thinking through the unintended consequences that might arise in its use; and considering a wide range of stakeholders who might be impacted. It’s essential that human (emotional) intelligence overlays artificial intelligence to create robust, ethical systems that satisfy business interests – but not at the expense of society at large.


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