While making an address at the 2023 Digital Ethics Summit, the UK’s information commissioner John Edwards warned that 2024 will be a critical juncture where public trust in AI could be eroded. 

In his speech, Edwards emphasised the importance of tech developers prioritising privacy, and embedding these considerations into every product. However, he warns that the effort being put in by lawful developers is being undermined by bad actors. 

“We know there are bad actors out there who aren’t respecting people’s information and who are using AI to gain an unfair advantage over their competitors,” said Edwards.

“Our message to those organisations is clear – non-compliance with data protection will not be profitable.”

“Persistent misuse of customers’ information, or misuse of AI in these situations, in order to gain a commercial advantage will be punished.”

During his keynote address, Edwards articulated the potential consequences of a loss of trust in AI, saying if people don’t trust AI, then they’re less likely to use it, resulting in reduced benefits and less growth or innovation in society as a whole.

In light of this, Edwards asserted that the ICO would ensure that the benefits of AI would not compromise individual privacy. 

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“Privacy and AI go hand in hand – there is no either / or here. You cannot expect to utilise AI in your products or services without considering privacy, data protection and how you will safeguard people’s rights,” he continued.

“There are no excuses for not ensuring that people’s personal information is protected if you are using AI systems, products or services.”

The call for increased trust in AI can be best illustrated in Stanford university’s AI Transparency Index, which shows that even the highest ranking AI programmes have a score between 40-60%, short of the 80% Stanford says should be commonplace. 

Regarding privacy, and other downstream impacts, some companies such as OpenAI, Google, and Anthropic did score well in usage policy, but that was out-shadowed by lower than acceptable labour and data scores.