FROM PILLAR TO POST question , with findings from the general public highlighting that 51 % believed the information they received from GenAI was incorrect , and 40 % believed the information was out of date . Businesses also reported issues with GenAI generating infringements on copyright or intellectual property rights ( 47 %), as well as receiving unexpected or unintended outputs ( 37 %).
However , the biggest issue impacting trust in GenAI from businesses ( 65 %) and the public ( 72 %) is ‘ AI hallucinations ’ – when GenAI produces incorrect predictions or nonsensical outputs . For businesses , this is where applying Generative AI to the right use cases , with the right technology and guardrails is needed to alleviate concerns . Almost half of consumers ( 43 %) also call for AI to be regulated .
Concerns remain about the ethical use and risks of GenAI
Alongside concerns about the accuracy and trustworthiness of GenAI outputs , business leaders and consumer respondents also have strong and similar views on where GenAI should never be used .
Over half ( 53 %) of the general public say they don ’ t want GenAI to be used for ethics / decisionmaking , while 45 % of business respondents cited critical decision-making . Where they slightly differ is on specific no-go use cases , with consumers citing politics ( 51 %) and businesses highlighting recruitment and termination ( 45 %) as where GenAI has no place in decision-making .
The research somewhat validates these concerns . Any AI-driven system is only as good as the data it ’ s trained on , however , the data highlights worrying shortfalls within organisations . Only 34 % of leaders said that their business ensures that data used to train GenAI is diverse and not biased . Additionally , only 26 % say they have ethical guidelines in place and 57 % say they have data privacy and security policies for GenAI use .
This lack of focus on data integrity exposes organisations to risks , with 60 % of business leaders stating that ethics is their top GenAI risk category , followed by data ( 56 %). This shows a need for greater governance to build trust and mitigate risk in how employees use GenAI in the workplace .
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