How can we ensure that AI in everything from lending to household goods is designed to be fair, transparent, and human centric? The Responsible AI movement is tackling those questions by proposing a framework that can help organizations foster AI with principles. Today, three tech questions make it clear that the movement’s work is addressing issues critical to our lives now:

1) Why do I feel like I’m being watched?

When you add the proliferation of camera-ready devices and exponential progress in AI, you get computers that are visual learners. From facial recognition payments to tracking babies as they sleep, the possible applications of machine learning are widespread. But while troves of visual data are being turned into compelling insights, there remains a challenge of how AI can collect visual data responsibly.

Computers still need to get better at reading human emotions and behaviors. But organizations will need to decide sooner when a visual input warrants a computer response; it’s important that machines learn to respond in a way that puts people at ease. What’s more, firms will need to decide what kind of data should be extracted: when gathering data look for visual information that’s useful and whose collection doesn’t ruffle feathers, or laws. 

2) AI knows you better than you do

AI may soon know our preferences better than ourselves. Smarter algorithms are propelling chatbots, voice, and messaging platforms to drive today’s retail discoveries. But guess what’s left out? Branding. Audience-targeting algorithms lessen the impact branding efforts, endorsements or PR campaigns. And because brick-and-mortar stores aren’t as ubiquitous as they have been in the past, AI recommendations sit between logistics operations and customers.

Brands will need to tread past these gatekeepers carefully—crossing the moat of e-commerce platforms without losing customer trust is key. It’s easy to worry that your intelligent assistant has too much power—including the power to manipulate and embarrass. And with AI looking to connect at home, in the car, or anywhere you take your location-tracking phone, the possibility for fatigue is real. Further, when AI can be gamed or hacked to limit choice, a shared set of best practices that addresses authenticity and manipulation is critical. 

3) Your new algorithmic coworker

Worries about the rise of the robots don’t totally capture AI’s role in the future of the workplace. Yes, jobs will be lost, but new jobs will take their place, and better ways of working will emerge when AI is paired with humans—not competing against them.

Responsible AI principles will be crucial for machine and human coexistence at the office, however. We’ll need to consider the specific types of job training and counseling programs that help people adapt. What’s more, guiding AI toward collaborative projects—all the while considering its needs as “another type of user”—will require designing machines to ask the right questions and reduce ambiguity. Algorithmic transparency is particularly important to this endeavor. AI bias reflects the same biases that humans have—so it’s critical that a diverse array of people, data and machines work to keep biases in check.

As these trends show, it’s essential we make sure AI is socially accountable. And with AI’s rapid incorporation in so many aspects of our lives, now is the time to be addressing how it is working and how it isn’t.

Not tomorrow. Today.

Join the conversation about Responsible AI with Accenture at MWC 2018.

This article was produced on behalf of Accenture by Quartz Creative and not by the Quartz editorial staff.

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