AI is more than automation on steroids, it amplifies human innovation
Artificial intelligence has a lot of promising applications, especially for scaling complex tasks — be it within IT infrastructure or within business processes — to mass-production levels. At the same time, AI shouldn’t be looked upon as automation on steroids — it succeeds where it amplifies human activities and creativity, and needs to be designed accordingly.
This needs to be a guiding principle as AI goes forward, especially since there is a yawning gap between ambition and execution at most companies, as found in recent research from MIT Sloan Management Review and Boston Consulting Group. Everyone is bullish on AI — 85% of executives surveyed say AI will provide their companies competitive advantage, and three-quarters believe AI will enable their companies to move into new businesses.
At the same time, only about one in five has actually incorporated AI in some offerings or processes, and less than 39% of all companies have an AI strategy in place. So, there’s a lot of work and planning ahead of us.
A big piece of the challenge is that AI is more than allowing machines to take over processes. It means new ways of thinking about how things get accomplished, and what people need to do to make this happen. It doesn’t just mean replacing human tasks, but rather, while freeing humans from rote tasks, also helping to amplifying their strengths and capabilities. It’s a two-way street. A forward-looking, well-managed organization is capable of building incredibly revolutionary AI just as much as well-designed AI can help the business.
Perhaps Shan Carter, of Google Mind, and Michael Nielsen, of YC Research, put it best in their recent highly cited paperon the topic: AI systems “can help develop more powerful ways of thinking, but there’s at most an indirect sense in which those ways of thinking are being used in turn to develop new AI systems.”
This two-way process may depend on good interface design that enables human operators to build, direct and even intervene in AI. There are a lot of misconceptions about this as well, as human-oriented designed is often seen as a squishy, feel-good concept that is peripheral to the heavy lifting systems are doing. “Many in the AI community greatly underestimate the depth of interface design, often regarding it as a simple problem, mostly about making things pretty or easy-to-use,” Carter and Nielsen state, adding that interface design is seen as “a problem to be handed off to others, while the hard work is to train some machine learning system.”
They urge AI developers focus more on human interface design as part of their work, noting that it has been key for every technology since the invention of the wheel. “At its deepest, interface design means developing the fundamental primitives human beings think and create with,” they state.
This is an emerging view within the systems design community as well.
