AI is becoming increasingly complex. It is not easily explained and can be confusing or even daunting to most people outside of those who work in the field. It wouldn’t be an exaggeration to suggest that for many people, their only exposure to the technology is the sometimes apocalyptic way in which AI is depicted in pop culture or the negative news stories that latch on to AI projects gone bad.

But as consumers assess whether to embrace the idea that more advanced AI-enabled products and services will become intertwined in their lives, pop-culture’s impact certainly cannot be ignored as it shapes how people will adopt the technology and trust the developers behind it.

“There is some public perception on AI, which is driven either by headlines of where AI has gone wrong, in some sense, and by science fiction films over the years,” says David Foster, Head of Lyft Bikes and Scooters. “And none of that probably leads to a sense of calm and happiness with AI taking increasingly broad roles in the world around us.”

The industry has taken steps to better inform and educate consumers. People understand that AI is doing useful things like helping them take better pictures on their phones, streamlining more relevant content to their social feeds, cleaning their home with a robotic vacuum, or helping them find artists they may like on their media player.

However, an Ipsos study taken in the UK found that 53 percent respondents would not feel comfortable with AI making decisions which affect them.
A study by the Center for the Governance of AI at the University of Oxford found that 22 percent of Americans thought that technology will be “on balance bad,” while 12 percent think that it would be “extremely bad,” leading to the potential human extinction.

Adds Foster: “We have to be a little bit careful about pushing the words AI for AI’s sake, and instead to focus on the benefits that we’re actually bringing to consumers and to the public that are enabled by AI, but are not there purely as a means to serve the technology of AI.”

By inviting end-users into the process of AIX design, we can better gauge the job to be done in terms of educating them about a product or service’s value and to understand how pop culture and news media are helping or hurting the technology’s adoption.

Who can forget the HAPIFork, the “smart” fork that monitors how quickly and how much you eat, that took the 2013 Consumer Electronics Show by storm? Of course, utensils are not the only thing apparently thinking for you – the number of products deemed “smart” or “intelligent” range from watches, health apps, home systems, bikes, toys and cars.

Each product promises to revolutionize the way we live in big and small ways, but have we hit peak AI hype? Some in the AI industry seem to think so, and that this will have consequences for the technology’s further adoption and development.

“Marketing that’s focused on texts and specs is going to fail,” says Jeff Poggi Co-CEO of the McIntosh Group. “And if we keep the marketing focused on the engineers that are developing the technologies, it’s going to be a very difficult rollout. We’ve got to think about this in the terms of consumer benefits. “We’ve got to start with the idea of how is this going to impact the emotions and the experience of the consumer and give them realistic examples of how that’s going to impact their lives. Show them the truth. Tell them how it is going to benefit them and what the experience is going to be. That’s the way we need to do it, and it has to be done enough in an authentic way.”

Many of existing products have relatively simple tasks which they perform quite well such as monitoring and automatically adjusting room temperature based on your schedule and comfort, or capturing physical activity levels and caloric intake to advise on diet and exercise.

But we are now moving into a realm where the industry is promising self-driving cars, refrigerators that monitor your food supply and diet and then order groceries for you, and robots that will take care of your household chores.

The issue is that these tasks require a tremendous amount of data and an AI system that can effectively process this information to provide real value. The challenge is to ensure we’re setting expectations about what these products can actually do right now.

This is an issue, and one the industry has faced in the past. “AI Winter” refers to a setback in the development of AI as a result of a lack of enthusiasm among consumers and investors. Typically, this begins when the AI community itself begins to see its own limitations. This pessimistic outlook is then picked up on by a number of outside influencers, including the media, which creates a negative feedback loop. This has already occurred in the 1970s and 1980s.

It could be argued that this time, given the significant advances in technology across all facets of our lives, the backlash will come from consumers who simply expect more. Indeed, consumers are constantly flooded with endless promises of how technology will make their world a better place.

This has resulted in people trusting their devices more than they should – like letting their car self-drive exceptionally long distances, along busy highways only to end up in a fatal crash. The car isn’t yet “smart” enough to handle all the variables thrown its way. While this is an extreme example, it’s these types of instances where expectations do not align with reality and serve as a wake-up call to the industry.

“In the companies that I’ve started, I’ve always told our engineering teams that what you’re going to deliver to the final customer is going to be really disappointing,”says Rodney Brooks, the Panasonic Professor of Robotics (emeritus) at MIT. “It’s not going to be at the cutting edge because we can’t afford to have our products grow up out there with a real user. So we’re going to be really careful with what we put out there and what we deliver. And we’re not going to be going as fast as science fiction movies expect us to be. It’s just the reality in order to provide something that people can feel comfortable with.”

One step in helping people move from a general distrust in AI towards acceptance lies in helping them understand how it all works. The more we talk about AI and see the incremental benefits it can have on society; the more willing people will be to accept it into their lives.

We need to foster technology literacy, help the general public understand how AI actually works, help them understand their rights as consumers, and how best to collaborate with AI to help bridge the gap from sci-fi to reality. Further, companies, governments and academics need to create and openly promote a framework that protects consumers from privacy and security threats, as well as define our “data rights” in a way that is accessible to consumers to make them feel empowered and safe.

“Technology literacy is not only important for the people who are building the systems to help them think about the impact of what they’re building,” adds Isbel. “It is at least as important, perhaps more important that we teach people who are not going to build those systems, but are going to be impacted by those systems, to think about what those implications are. And that has to start as early as possible.”

Even how we speak about AI should be taken into consideration. Tech-speak and programming jargon only serve those who are entrenched in the development of AI products and services.
A common understanding of AI and its capabilities that reflects different cultures, countries, and beliefs will help us better interpret and understand how AI is impacting our lives. This should be baked into education in the form of AI literacy so that consumers of all ages can better understand and harness AI’s potential without falling for the hype.

“Awareness and education for consumers is absolutely critical, but it goes beyond that,” says Helena Leurent, Director General, Consumers International. “It’s about actually engaging with consumers in the design of these new technologies or approaches or services. It’s about bringing consumer advocacy into the upfront stage, as opposed to it being at the backstage of the process. It’s about having principles that think about vulnerable consumers at the very start. It’s about making a level playing field so that the best practice becomes closer to the norm.”