Non-tech leaders are now the key champion for AI ethics

Ethical AI – which ensures that the AI initiatives of the organization is fair and do not in any way cause harm to people – has been ideally seen as a tech issue until now, with CIO/CISOs being the chief custodians of AI ethics. Time is now changing as organizations are realising that the broader implications of ethical AI for businesses. This view gets echoed in a recent IBM survey, in which 80% of respondents pointed to a non-technical executive as the primary advocates for AI ethics.  

An earlier report on the topic was published by IBM in 2018 that pointed to only 15% non-technical executive as the primary advocates for AI ethics practices.   

According to the study, more CEOs (79%) are now prepared to build ethical practices into their AI projects – up from 20% in 2018 -- and more than half of responding organizations have publicly endorsed common principles of AI ethics. For example, chief executives have started to recognise the need to identify the potential for bias in an AI project and understand the importance of transparently articulating it to the right stakeholders.  

However, challenges remain, as despite a strong imperative for advancing trustworthy AI, less than a quarter of organizations have acted on their AI ethics initiatives. Hence there remains a gap between leaders’ intention and meaningful actions.  

According to the report, 68% of organizations acknowledge diversity is important to mitigating bias in AI, but respondents indicated their AI teams are: 5.5 times less inclusive of women, 4 times less inclusive of LGBT+ individuals and 1.7 times less racially inclusive.  

The silver lining is that the report showed that business executives are now seen as the driving force in AI ethics, with CEOs (28%), board members (10%), General Counsels (10%), Privacy Officers (8%), and Risk & Compliance Officers (6%) are viewed as being most accountable for AI ethics by those surveyed. 

While 66% of respondents cite the CEO or other C-level executive as having a strong influence on their organization’s ethics strategy, more than half cite board directives (58%) and the shareholder community (53%).  

At the same time, 75% of respondents believe ethics is a source of competitive differentiation, and more than 67% of respondents that view AI and AI ethics as important indicate their organizations outperform their peers in sustainability, social responsibility, and diversity and inclusion. 

Several companies in fact have started making strides, as more than half of respondents say their organizations have taken steps to embed AI ethics into their existing approach to business ethics. More than 45% of respondents say their organizations have created AI-specific ethics mechanisms, such as an AI project risk assessment framework and auditing/review process.   

“As many companies today use AI algorithms across their business, they potentially face increasing internal and external demands to design these algorithms to be fair, secured and trustworthy; yet, there has been little progress across the industry in embedding AI ethics into their practices,” said Jesus Mantas, Global Managing Partner, IBM Consulting.   

“Our study findings demonstrate that building trustworthy AI is a business imperative and a societal expectation, not just a compliance issue. As such, companies can implement a governance model and embed ethical principles across the full AI life cycle,” he said. 

To sum up, while ethical principles embedded in AI solutions is an urgent need for organizations; the progress is still very slow. The study suggests that those organizations who implement a broad AI ethics strategy interwoven throughout business units may have a competitive advantage moving forward.   

Of the key recommendations, the researchers noted, was that companies should take a cross-functional, collaborative approach involving its key stakeholders in the AI ethics process, including C-Suite executives, designers, behavioural scientists, data scientists, and AI engineers – with each having a distinct role to play in the trustworthy AI journey.