After decades working in the Artificial Intelligence (AI) and Big Data spaces, I find it curious how quickly many of the people with whom I speak have a strong visceral reaction to what I do. As a result of starting our company, DimensionalMechanics, I have had dozens of conversations over the past couple of years about AI. Typical conversations begin the same, but conclude a certain way based on the inquirer’s background. For example:
Person: ‘What do you do, Dave?’
Me: ‘I work at a tech startup that is developing AI technology. You know, artificial intelligence.’
Non-techy person: ‘Oh. . . So do you think machines are going to take over the world someday? . . . That is scary stuff.’
Person working in general big data or enterprise role: ‘I don’t understand how it works, but it sounds like I will need an army of PhDs to use it. I am worried about what this will do to us, to my business. I don’t even know where to start.’
Or, as someone close to me recently put it, ‘I’m not sure that what you’re creating won’t result in death!’
AI is a strange and growing beast in the minds of many people. It ignites innovative thought and intrigue, while at the same time brings fear, apprehension or general confusion, whether you are close to or distant from the underlying technology. Despite the general perceptions or misperceptions of AI, one thing remains true: AI holds the potential to radically transform businesses and dramatically impact the bottom line.
Based on my many conversations, I can’t escape the idea that there is a broad cultural response to AI that has far-reaching effects, negatively impacting how businesses approach its use and benefits, and even shaping the way developers craft solutions. I would assert that AI’s true potential will not be realized unless the technical and cultural obstacles making it unapproachable are overcome.
This response impacts adoption and development in many ways:
- Take, as just one example, potential enterprise users buried in data. I believe this is an extension of the ongoing Big Data conversation and its potential to deliver positive long-term results. Major challenges remain, as recently opined by Gary Marcus and Ernest Davis of New York University. Many business types have an inkling that AI could help unbury them, but the how-to evades them. They can’t get their head around it, and there hasn’t been a straightforward solution yet.
- For AI developers, running into resistance and passion toward a subject like AI can insert bias into the development process itself, impacting the quality of the end result. I am referring to the response an AI technologist can have to valid concerns voiced regularly by both the pundits and the businessperson, that AI could be a threat to the human race rather than a tool to be embraced. The result can be the avoidance of innovation because of the fear of people’s responses.
Why do we need to overcome this cultural reaction?
- So that we don’t overlook what we can gain by adopting AI and avoid throwing out the good with the bad.
- So that we won’t be distracted by things like anthropomorphism, the process of giving things human-like characteristics to make them less scary and more approachable.
- So that we can keep the focus on solving real business and enterprise problems. This drives our work at DimensionalMechanics, where we’re building an enterprise AI platform to address challenges that will help business users operate smarter, more efficiently and ultimately answer complex questions about the mountains of media content or data they’re amassing. Our system is robust but it doesn’t have a gender-based personality, and it certainly won’t morph into HAL 9000.
I’m not alone in eschewing the hand-wringing, but it’s clear that as the discussion around AI expands, so too does the need for information.
Knowing the high stakes, it’s important that we better understand the factors that make AI such a flashpoint, so that we can address them. There are numerous and complex contributors which I’ll explore in a series of posts here on the DimensionalMechanics blog. Check back soon to read more about the origins of AI, the ethos and pathos spurred by everything from research science to science fiction movies, and more.