Why should anyone trust AI?

5Oct - by aiuniverse - 0 - In AI-ONE

Source: ciodive.com

The pandemic has changed the world, accelerating the pace of digital transformation and forcing businesses to find new efficiencies — not only in cost cutting but in decision making.

That’s why business leaders love AI, because it can help them make better and faster decisions by providing quicker and more accurate insights. It can tell them what customers really want — and what they want right now.

There is a problem though: Consumers don’t love AI. In one recent study, only 25% said they would trust an AI decision more than one made by a human, and less than 30% were comfortable with businesses using AI to interact with them.

Consumers are skeptical about AI because they don’t understand it. Many are scared by what they read and hear and not all their fears are misplaced. 

Unintentional built-in bias leads algorithms to make decisions, like credit denials, that unfairly discriminate against some minority consumers. It’s also probable that jobs will be lost to AI. What industry does to mitigate both of these problems will be key to maintaining consumer trust. 

Many business leaders attempt to impress customers merely by devising an “AI strategy” or building an “AI system” — and trumpeting it loudly. But customers are put off by this approach. 

What consumers value is the convenience, speed and choice delivered by AI working behind the scenes when they’re doing things like shopping or seeking health advice. 

They’re impressed by better products and services, greater convenience and better value for money, all of which AI delivers. The disconnect means business leaders need to think about their AI efforts differently, and spend more time educating consumers on how AI benefits them.

Not to be denied: AI is doing great things

Few shoppers realize the overnight arrival of their online purchases depends on AI algorithms getting items packed and shipped expeditiously. How many grasp that AI enables a customer service agent or chatbot to make quick-fire responses to their queries and requests? Few probably understand AI is locating the nearby Lyft driver within seconds of a tap on a smartphone.

The workings of AI are mostly unseen in the financial industry, where they very much benefit both institutions and customers. Take fraud detection. Some earlier protections were simple, blunt instruments. 

Sure, they stopped fraudulent transactions, but they also blocked many legitimate ones (“false positives”), often resulting in terrible customer experiences. Today, AI-based platforms pinpoint fraud faster and better, reducing false positives by more than half. That equals more legitimate transactions and fewer unhappy customers.

Within organizations, AI is eliminating repetitive tasks and enabling creativity. Business leaders should be asking, how much drudgery can AI push out of the system so my employees can do more creative work?

Diversity and discretion

What lessons can business leaders draw from all this? One is to tackle the bias issue — the danger that flawed algorithms make decisions unfairly, disadvantaging consumers. 

The first step is to understand that the bias isn’t in the AI but in the data, whether it’s data used initially to train the algorithm or data entered to generate insights. The best way to minimize bias is through diversity — finding and using the widest possible range of datasets. Not just quantity but variety. 

In human interaction, we fight bias by talking to people with different perspectives, by working with people that challenge and question the status quo. The same approach needs to be taken to the data we use to inform our algorithms.

Different groups of business stakeholders need different talking points when it comes to AI. Analysts and investors may be impressed with tales of tech capabilities, but customers just want to hear about better services or products, and that their data is being strongly protected and ethically used. 

We’re more likely to build trust by flat out saying, “We’re not going to compromise your data.” 

Business leaders need to understand AI’s limitations. AI is a tool, not a product, a strategy or a business model. Powerful it may be, but AI is only assisting us in doing the things we’ve always strived to be: smarter, faster, more efficient and, hopefully, more trustworthy

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