Want to get more from AI? Build trust in your machines

Paul Blase, PwC

Did you know that the self-driving car market could reach $87 billion by 2030¹? How many of us are ready to sit in the passenger seat of a speeding, driverless taxi? Despite not trusting my fellow humans as drivers all the time, I’m not sure I’m ready. It would require complete trust in the artificial intelligence manning the wheel and controlling the brakes.

We are at an inflection point as AI proliferates across virtually every industry. Yet, according to PwC’s Global Data and Analytics Survey 2016: Big Decisions™, only 39% of companies are highly data-driven. Most executives still favor minds over machines—relying on gut intuition rather than data-driven insights from wiry-brained co-workers.  

I’ve been thinking a lot about this topic as I prepare for my talk at AI World. Trust, not technology, is the biggest barrier to getting more from AI. If you want to disrupt, rather than be disrupted, building trust in your machines to harness their potential is vital. Here are some guiding principles that can help:

Overcome the Terminator myth: The C-suite should lead the charge in adapting their organizational cultures to be open-minded in working with, and trusting, machines. It’s not easy, given perceptions of worker displacement by automated antagonists, or of rogue Terminators taking over the world. Yet, organizational cultures receptive to blending human judgement and intuition with AI and deep learning can achieve extraordinary results.

Treat machines as allies, not servants: Those who get the most out of AI avoid treating their machines like statistical subordinates. Rather, they create a culture that treats intelligent machines as analytical allies who can help solve complex business problems. Open-minded executives know where they want to go, and work hard to guide—and teach—machines to help them get there. It’s a two-sided journey. As machines digest vast quantities of data, they become more intelligent—and in turn advise executives. When trust is part of the equation, both humans and machines become smarter and augment each other.

Nurture humans to communicate data insights: Human decisions are inevitably underscored by a degree of bias. Regardless of whether it’s an individual or a group, bias frequently influences executive decisions about what data to accept, and what to ignore—a precarious position. Businesses with the right human-machine dynamic can leverage AI to create a systematic approach to decision-making and help circumvent bias. Nurturing human skills is essential to empower data champions to instill confidence in data insights, even when they go against an executive’s gut. 

Foster the human spirit of inquiry: Building trust in machines doesn’t replace the need for the human spirit of inquiry. Quite the contrary. Ongoing collaboration with machines should be guided by business objectives and a vision of what the business wants to do ultimately, that it can’t do now. Identifying the right questions to ask comes only through open discussion, experimentation and a willingness to fail. Far from being excluded from analysis and problem framing, top executives should guide the exploration, and data scientists should design experiments to prove leadership’s hypotheses.

While I’m not quite ready to ride in a driverless car, I might be able to take the leap if a human driver was on hand to assume control if needed. As my trust builds, in the not too distant future, perhaps I’ll be comfortably working in the back seat, as invisible forces safely deliver me to my destination.

Let me know how you are adapting your culture to get more out of AI. If you will attend AI World, I hope to see you there. 

1. Lux Research

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