Joe McKendrick
zdnet.com
Originally posted 27 Dec 24
Many organizations are either delaying or pulling the plug on generative AI due to concerns about its ethics and safety. This is prompting calls to move AI out of technology departments and involve more non-technical business stakeholders in AI design and management.
More than half (56%) of businesses are delaying major investments in generative AI until there is clarity on AI standards and regulations, according to a recent survey from the IBM Institute for Business Value. At least 72% say they are willing to forgo generative AI benefits due to ethical concerns.
More challenging than technology issues
Many of the technical issues associated with artificial intelligence have been resolved, but the hard work surrounding AI ethics is now coming to the forefront. This is proving even more challenging than addressing technology issues.
The challenge for development teams at this stage is "to recognize that creating ethical AI is not strictly a technical problem but a socio-technical problem," said Phaedra Boinodiris, global leader for trustworthy AI at IBM Consulting, in a recent podcast. This means extending AI oversight beyond IT and data management teams across organizations.
Here are some thoughts:
Many organizations are delaying or halting investments in generative AI due to ethical and safety concerns, prompting calls to involve non-technical stakeholders in AI design and management. A recent IBM survey found that 56% of businesses are postponing major AI investments until regulatory clarity emerges, with 72% willing to forgo AI benefits due to ethical worries. While technical challenges have largely been resolved, ethical concerns are proving more complex, requiring a socio-technical approach. Phaedra Boinodiris of IBM Consulting emphasizes that ethical AI development demands multidisciplinary teams, including experts in linguistics, philosophy, and diverse life experiences, to address questions like unintended effects and data appropriateness.
Business leaders increasingly see AI ethics as a competitive advantage, with 75% viewing it as a differentiator and 54% considering it strategically vital. Consumers and employees also value ethical AI. An effective AI ethics framework can yield three types of ROI: economic (e.g., cost savings), capabilities (e.g., long-term innovation), and reputational (e.g., improved brand perception). However, many executives lack awareness of these impacts, highlighting the need for ongoing education to align AI ethics with broader organizational goals.
