Is Trust The Next Big Divide in AI?

Racepoint Global

Written by: Nana Rodaki – Client Manager, Racepoint Global London

As a technology enthusiast who devours as much news and analysis of the latest tech trends as I can possibly fit in the day, I often feel that I’m listening into the conversations of others. Having the opportunity to discuss first-hand the key challenges and considerations that businesses face puts things into perspective.

Walking the floor at this year’s AI Tech World and Connected World Summit was a revelation. Business leaders at established enterprises, start-up executives as well as representatives of non-profit organisations alike were asking a key question: ‘How can I get technologies like Artificial Intelligence (AI) and Machine Learning (ML) to work for me?’ Drawing on these conversations, it seems that most industries (from manufacturing to retail, healthcare, insurance and beyond) are already sold on the benefits that these technologies can bring and the real question has shifted to deployment across different use cases and the best way to achieve these benefits.

But through conversations with companies within the Connected Living space, I soon realised that there was a big discrepancy. Consumers still had ‘trust issues’ with AI and particularly with voice assistants. Are we then in the midst of a divide between how businesses and consumers see tech evolution?

Is technology smart enough for business but too ‘curious’ for consumers?

Advancements in technology always come with new promises and in the business world these take the form of all sorts of efficiencies. When thinking about deploying AI and ML, what organisations are looking for is actionable insights that can help them address challenges and gain real business value.

AI and ML bring the gifts of real-time, full IT visibility and prediction. Sets of algorithms and data analytics models can for instance, identify micro-anomalies and patterns that could potentially pose security or other threats (i.e. downtime) in their nascent stage, giving organisations the chance to respond before they develop into actual threats. For the more consumer-facing businesses, AI-powered customer engagement platforms can predict customer queries before they start. For example, if an item is reported as faulty, businesses can act proactively and offer customers who purchased it a replacement or refund, doing wonders for their brand reputation and customer loyalty.

But if the business world is getting more and more on board with these technologies and turning its attention to deploying them in the most beneficial way, why do consumers feel differently?

A recent study by Accenture UK revealed that although 67% of UK voice assistant users use them daily, more than one in five UK adults admitted they leave the room or lower their voice to make sure their device cannot spy on them. The voice assistants’ great level of responsiveness seems to be at the same time a key advantage and disadvantage and consumers still don’t feel they can trust that AI will respect their privacy. These fears appear to be justified when the media report on Alexa’s crossed wires or accusations of smart TVs snooping

Where do we go from here?

It is fair to say that the business and consumer AI use cases are at a different stage in their deployment cycle with businesses being far more ready to adopt and deploy the technology. However, for the AI space to take off, the consumer trust issue needs to be addressed. The next frontier in AI is to incorporate consumer feedback into product design and development and provide the safeguards that will allow the market to take off.

In addition, the communications teams need to focus on reinforcing the facts and reassuring consumers by debunking the fearmongering myths that stick in the mind long after the headlines have faded.

Is this going to be enough for consumers to look at the small speaker in the room differently? It remains to be seen but I certainly look forward to seeing how this conversation will evolve and the progress – if any – that will be made before next year’s AI Tech World and Connected World Summit.