The concept of Artificial Intelligence (AI) is almost as old as the field of modern computer sciences. From the early days in the late 1950s to the shape it has transformed into, computer scientists have inspired, and at times, bamboozled humankind with its seemingly infinite capabilities.
Having said that, it seems that there is hardly any field in computer sciences that has remained so misunderstood as AI. There have been varying distinctions in the understanding of artificial intelligence based on comprehension, wit, exposure (to the media mostly), and the field of association.
For instance, the general comprehension of the layman is generally mixed: precisely 34% according to the Department of Technological Policy Management, but slightly negatively skewed because of the exposure to sci-fi movies, media, and interviews from the tech tycoons, such as Elon Musk, who has generally been pessimistic about its uncontrolled development (Independent, 2020).
But no matter what these perceptions are, humans have reached a point where they can no longer avoid or go back from where we started. Thus, there is and would always be imperative to use AI.
We have and would continue to see steady (and at times, exponential) development in how Artificial Intelligence continues to change our lives in fields.
Generally, and particularly in the context of the EU, one of the biggest challenges is getting to know which jobs are at stake and how we can minimize risking our jobs before robots or even centaurs take over.
Though there are tons of research papers and journalists commenting about the possible impacts of AI on the job market, one of the most relevant ones comes from Oxford Martin, which states that almost 47% of the jobs in the US are going to be replaced because of the AI (Sandberg, 2020).
However, this is just the economic impact. How our lives are going to be radically transformed is just another story.
Perhaps one of the most convincing reasons to build trust in AI is the way it’s filling in the gaps where humans haven’t or are incapable of bridging the gaps. And at many points, humans might realize that they might not have developed AI sufficiently to help them overcome the issues that could be potentially avoided (had there been a smarter technology in place).
We have witnessed some of the most remarkable feats in AI development, such as medical sciences. The development of a prosthetic arm, which could be controlled by a brain-computer user interface and can work when would detect a combination of signals in particular parts of the brain, is one of the best examples in this case (Marco Aiello, Yujiu Yang, Yuexian Zou · 2018). Though this may still be a work in progress, as with all things, AI has made exponential strides within the last decade. It is likely that it would take on filling in more gaps within the next decade and making us smarter than ever before.
Though it may be exhaustive to cover up the scope and the ability of AI within various fields in a single essay, one of the finest examples regarding a glimpse of what AI could look like in the future comes from IBM Watson, whose ability to integrate blockchain, AI and analytics helps it to supplement the capabilities within the health sciences better than any human or organization (IBM, 2020).
On the other hand, AI’s potential has also seeped into the hands of a few data giants, such as Facebook, Google, and Amazon. With their ability to amass more data, there has been a consequential upgradation in the algorithms. When combined with their access to ultra-modern and sophisticated computing power has and continues to build artificial intelligence to the level that was or is imagined by only a few people. While this has helped them identify, develop and improve the impact and delivery of their products and services at various touchpoints, from production and distribution to marketing and upselling it, it has also created a wider chasm where the power to influence the development has concentrated in a few hands, which isn’t healthy.
Dealing with the Consequences
Many experts have suggested that though artificial intelligence may trump us with its ability to know more and act faster and smartly than ever before. What it might never become is the facet through which we define our humane side of ourselves. Humane traits such as empathy, compassion, and self-service are things that AI might not be able to catch up with, no matter how strong it becomes.
I generally disagree with the opinion. Though this may be something that might not be happening soon, as robots get smarter, so does their ability to build upon the emotional side of things.
There are also debates regarding whether or not AI would ever be able to overshadow human biases. For example, when it comes to screening candidates for an interview, can AI bypass the human benchmarks or prejudices that we set up for ourselves because that’s how quintessential they need to be? Though this might be a data problem, a part of the onus also lies on the algorithms and their output. There is a need for more inclusion and diversification in the data and its outreach (free from the biases) to fix this.
Despite the critics naysaying about the fatal development of AI technology, let’s accept that the world could not have been where it is today without the role of AI. And as humans continue to find gaps in their potential and their ability to synergize with the inclusion of Artificial Intelligence in their lives, they would continue to do so.
As with our mundane human interactions, the development of AI requires solid policymaking and legislation. However, it may never be simple. There would always be a need to draw a line between what we, as humans, would possibly do against the areas where AI could supplement our potential. But at some point, boundaries have to be drawn: not to keep AI out of our lives, neither to fence us in. But to ensure that when it’s time to exercise control, we are willing to roll up our sleeves and step ourselves in.
Aiello, M., Yang, Y., Zou, Y. and Zhang, L., 2018. Artificial Intelligence And Mobile Services — AIMS 2018. 7th ed. Seattle, WA, USA, p.268.
IBM.com. 2020. Watson Health: Get The Facts | Solving Health Challenges Thru AI. [online] Available at: <https://www.ibm.com/watson-health/about/get-the-facts> [Accessed 11 November 2020].
Sandberg, D., 2020. “Artificial Intelligence: Examining The Interface Between Brain And Computers[online] Oxford Martin School. Available at: <https://www.oxfordmartin.ox.ac.uk/videos/artificial-intelligence-examining-the-interface-between-brain-and-machine/> [Accessed 11 November 2020].
The Independent. 2020. Elon Musk Claims AI Will Overtake Humans ‘In Less Than Five Years’. [online] Available at: <https://www.independent.co.uk/life-style/gadgets-and-tech/news/elon-musk-artificial-intelligence-ai-singularity-a9640196.html> [Accessed 11 November 2020].