Why hasn’t Artificial Intelligence been democratized?
The potential impact of AI on society can be compared with that of nuclear power. On the one hand, it is able to create a massive boost in productivity and quality of life for human societies. On the other hand, it also has the potential to fall in the wrong hands and create weapons of mass destruction that will endanger billions of lives.
That’s why, before the full onset of the AI revolution, it is important for us as a society to consider ways to prevent the potential negative effects of AI from becoming a reality.
Elon Musk, a thought leader in predicting the effects of AI on society, proposed democratization of AI as the solution to its potential risks in an interview with YCombinator founder Sam Altman.
His view can be summarized by the following snippet:
Democratization of AI, that is, making AI technologies widely available to all businesses and individuals at an affordable cost, is becoming one of the most popular topics of discussion in recent years. However, while OpenAI has gained much traction since its establishment, the progress we have made towards AI democratization has been at most uninspiring.
According to a recent survey by McKinsey Global Institute, only 20% of companies are using AI technologies in their day-to-day operations. Given the respondents of the survey are mostly the larger enterprises in their industry, AI adoption in small and medium sized businesses is even more bleak.
This article is going to explore three primary factors preventing companies, large and small alike, from adopting AI technology in their day-to-day operations:
For each of the factors, I will also propose potential solutions that we can use to bypass the adoption hurdles of AI and make its democratization truly possible.
Just like with any other challenge in democratic societies, the democratization of AI requires a critical mass of informed citizens for a robust public discourse to form. These citizens can in turn create solutions to maximize its benefits while mitigating the harms.
This does not currently exist for AI.
According to a survey conducted by Qualtric, only 10% of the internet users surveyed (compare with 34% for 3D printing) consider themselves experts of AI (i.e. they understand the ins and outs of the technology). On the other hand, over 30% of respondents have only heard of AI, but don’t really know what it entails.
Honestly, I am not surprised by the result of this survey since the term “Artificial Intelligence” is very general and covers such a wide range of computer innovations that began in the 1950s.
According to Merriam Webster, AI can be defined as the “science and engineering of making intelligent machines, especially intelligent computer programs.”
Based on this definition, even some of the simplest things in everyday life, such as vending machines and gas pumps, can be included in some categories of AI because they do mimic certain tasks that were previously accomplishable only by human intelligence.
Even if we are only talking about well-known AIs that are “changing the world,” they can be further broken down into many categories such as game-playing (Deepblue and AlphaGo), natural language processing (Amazon Alexa), anomaly detection (fraud detection technology), and computer vision (facial recognition technology).
Each of these categories has their own distinctive impact on our society. For example, computer vision systems and game-playing systems are the main technology behind self-driving cars. On the other hand, natural language processing is the potential disruptor of many reading-heavy jobs, such as financial analyst jobs.
Therefore, without a deep-level understanding of the history and components of AI, it is really hard for a lay-person to carefully consider the impacts of each individual category of AI technology, and to offer their own informed opinions on how to prevent their negative effects.
So, how do we solve this knowledge gap of AI? I propose a two-prong solution.
