Artificial intelligence has generated a great deal of interest from the business world and beyond, but there is also a great deal of misunderstanding about this significant leap in technology.
When most people hear the words "artificial intelligence," the first thing that comes to mind is an all-knowing, sentient machine that can outsmart and overpower any human being. Artificial intelligence is something big and scary. It's a threat that will take away our jobs and livelihoods, replace us all, and ultimately obliterate the human race.
Even if that ultimately ends up being true, I do not believe we are anywhere close to that scenario. I also believe that these powerful misconceptions around AI actually prevent us from building a positive relationship with it.
Misconception #1: AI is actively looking to replace people.
AI, in and of itself, is technology with no volition. It does not seek to replace the workforce for a smarter and cheaper machine alternative. It is post-industrial tech capitalism at its finest doing that, not AI. It may seem like a subtle difference, but it's huge. AI gets all the blame, but the capitalistic paradigm is a lot more accountable for the threat to our livelihoods than the technology itself. [Read related story: How AI and Machine Learning Are Changing Cybersecurity]
Misconception #2: AI is ridiculously smart or savvy.
AI could be ridiculously simple in its applications. It can be fragmented and disjointed, as opposed to a microchipped, perfected version of the human mind. AI can do simple things, like learn how to play checkers, identify patterns in large data sets, or any straightforward activity that just requires crunching more data than a human can. AI is not necessarily a competitor trying to outperform the human mind, but possibly an extension of our senses and capabilities.
Misconception #3: AI is complex and difficult to understand.
Coding for AI can get very complex, but the concept of it is simple: It's any technology that mimics our natural cognitive abilities. The misconception here for most non-tech people is that, once AI enters the conversation, we are talking about either stereotyped sci-fi or scientific concepts way over our heads. But AI can be very straightforward. If you can understand the mind as a cognitive processor, you can understand AI.
Think of it this way: The mind is powerful in that it not only learns rules, but makes these rules and improves them over time based on experiences. Let's say one day you try to add water to a pan full of oil and you create an explosion in your kitchen. You will learn that this is something you do not wish to repeat. No one will have to formally instruct you not to do this moving forward. You will know from the undesirable outcome that, next time you are in the kitchen, you will try a different path that has a greater probability of a desirable outcome. So all AI is doing is mimicking what we do naturally.
Misconception #4: AI will achieve singularity.
We have no idea how much AI will evolve over time. We do not know how heavily regulated the industry will become and whether or not the industry will continue to focus on direct applications for AI as opposed to consciousness in terms of heavy funding. While it is logical to predict this natural continuous evolution of AI toward singularity, the truth is that we do not know.
Due to the range of applications and sophistication of these applications, AI is really not a thing, but many things. Our negative bias toward uncertainty, compounded by the threat of the unknown, gives us awe but also a lot of fear about the long-term social consequences of super-disseminated AI.
From my perspective, I can certainly see the changes introduced by AI slowly rippling throughout my microverse, but I do not see it replacing or obliviating anything. Instead, I see AI transitioning my team to tasks that leverage the best of human abilities as opposed to doing things that slowly deprive us of creativity, spontaneity and deep critical thinking,
In my scenario, there is room for everything – AI and natural cognition working together. But this scenario also requires a more self-reflective view and a more transformational attitude to life in general that is more at ease with change and discontinuity.